The Malta Consumer Trends Market Research Report 2024

Organised & Led

by

Gordon Theobald B2BMALTA Advisory

B2B Malta Ltd offers a comprehensive range of services, including feasibility studies, ongoing compliance, and flexible workspace solutions. It supports businesses at all stages of development, fostering growth for startups and established enterprises alike. Its emphasis on collaboration between academia and business promotes innovation and entrepreneurship. With over 20 years of market research experience, B2B Malta Ltd is dedicated to making market research more accessible and affordable in Malta. It has collaborated with a number of renowned local research agencies, major international research agencies and undertaken a variety of ad-hoc research projects in Malta. It provides critical insights and data that enable businesses to make informed choices and strategies.

Gordon Borg Urso Digital Marketing Consultant

A seasoned digital marketing consultant dedicated to transforming businesses through powerful online strategies. With 20 years of hands-on experience, he has collaborated with thriving local and global brands across diverse sectors. As your digital guru, he specialises in crafting tailored solutions to boost your online presence and supercharge sales.

Table of Content

Disclaimer & Limitation of Liability

B2BMALTA LTD (“the Company”) endeavours to ensure the accuracy and reliability of information provided in its reports, drawing from validated sources and utilising established research methodologies. Despite these efforts, the Company does not warrant the absolute accuracy or completeness of the information contained within its reports. The Company shall not be held responsible for any misinterpretations or incorrect use of the data, except in relation to the specific insights and advice provided for the scope of contracted projects. This report is exclusively prepared to support research for the Malta Consumer Trends Event.

B2B MALTA LTD expressly disclaims any liability for the application of this report beyond the specified terms of use. Users are cautioned to apply due diligence and seek further verification when relying on historical data for business decisions. Furthermore, B2BMALTA LTD, including its directors, employees, agents, consultants, and successors in title, shall be fully indemnified against any claims arising from third parties due to the direct or indirect disclosure of the report’s content to any unauthorised party. By utilising this report, the recipient acknowledges and agrees to the terms set forth in this disclaimer.

Executive Summary

Consumer Trends 2024 in Malta

The Malta Consumer Trends 2024 initiative delves into the evolving consumer behaviours in Malta against a backdrop of global trends. Refer to Annex 5 - Desk Research Findings & Observations for a detailed overview of international insights and qualitative data collected during the event.

This analysis aims to bridge the gap in understanding Maltese consumers’ preferences and behaviours, facilitating local businesses in strategizing more effectively in alignment with both local and international consumer dynamics. Employing a robust dual-method approach combining Computer-Assisted Telephone Interviewing (CATI) and ComputerAssisted Web Interviewing (CAWI), the study surveyed a stratified sample of 403 respondents. This provided a broad overview of purchasing behaviours across 19 market categories, focusing on the dichotomy between large, one-time

purchases and recurrent buying patterns. The global consumer landscape is increasingly influenced by technology, service quality, and sustainability. Brand loyalty is evolving, with a pronounced preference for brands offering superior service and innovative digital experiences.

Key global trends include the rise of AI in marketing, the growing demand for immersive experiences, and heightened consumer awareness regarding health and sustainability.

Findings & Observations

Dominant market categories reveal that for recurrent acquisitions, expenditures related to food, encompassing ‘Meat and Seafood’, ‘Frozen, Refrigerated, Canned, and Packaged Goods’, and ‘Fresh Produce’, predominate in consumer spending. This indicates a robust and steady demand for food products, with a specific focus on quality, convenience, and fresh produce. Categories related to household and lifestyle such as ‘Vacation, Travel & Wellness’, ‘Household and Non-Food Items’, ‘Consumer Electronics’, and ‘Large Home Appliances’ denote substantial consumer expenditure on enhancing both experiences and the home environment. The preliminary analysis of outlets with the highest footfall, emphasises the central role supermarkets play in consumer lives, serving as primary destinations for a diverse range of needs. This underlines the potential for supermarkets to act as key players in influencing consumer behaviour and preferences.

Categories such as ‘Vacation, Travel & Wellness’, and ‘Consumer Electronics’ stand out as particularly significant among consumers, signifying industries with potentially high levels of consumer engagement and expenditure. Of interest is that in the context of major purchases, the relevance of physical retail remains noteworthy. Despite the ascent of online platforms, physical retail environments like stores and showrooms are essential in the consumer decision-making journey, particularly for significant acquisitions. This highlights the persistent importance of tactile and visual product interactions, implying that businesses should sustain a harmonious balance between.

Digital platforms are integral to the consumer information search process, with company websites and social media platforms like Facebook and Instagram serving as key information sources. The reliance on digital channels varies by age, indicating younger demographics are more

inclined toward social media for information gathering, whereas older demographics show a preference for company websites and physical stores. The usage of social media platforms varies significantly across demographics, emphasising the need for platform-specific content strategies. Understanding the audience on each platform allows businesses to craft engaging and informative content that resonates with the target audience, whether through visual storytelling on Instagram for younger consumers or informative content on YouTube for a more mature audience.

The findings advocate for a multi-channel strategy that integrates digital and physical customer experiences. This suggests that businesses should leverage data analytics to understand consumer behaviours across channels and personalise marketing and sales strategies accordingly.

Personal desires and requirements, alongside price and affordability, are central to consumer decision-making processes across various demographics. This underscores the importance of offering products and services that not only meet individual needs but are also competitively priced. The emphasis on product features and quality, particularly among consumers with higher education and specialised occupations, highlights a segment that values functionality and long-term value. This suggests businesses need to focus on high-quality, durable products to attract this demographic.

Price sensitivity is a significant factor, especially among younger consumers, students, and larger households, highlighting the need for competitive pricing strategies to attract these segments. Competitive pricing is a critical factor across age groups, with a slightly higher emphasis among females. This suggests that businesses need to carefully consider their pricing strategies to attract and retain customers, especially in market segments where price sensitivity is

high. Moreover, tailoring pricing strategies to reflect the economic context and consumer expectations in specific regions can enhance competitiveness.

Despite the digital shift, physical retail experiences, such as viewing products in person and physical stores’ advice, remain paramount in the consumer decisionmaking process, especially for substantial purchases. This is particularly true for older demographics and certain geographic regions, indicating the continued relevance of physical retail environments. Digital channels play a critical role in information gathering and evaluation, with younger consumers and those with higher education levels showing a preference for online reviews, ratings, and detailed product specifications. This points to the necessity of a strong online presence and digital engagement strategy for businesses. Therefore, the consumer’s journey involves a mix of traditional and digital evaluation methods, indicating the need for an integrated, omni-channel approach that combines the strengths of physical retail experiences with digital engagement to cater to diverse consumer preferences effectively.

Word of mouth and social proof remain a significant factor in consumer decisionmaking, highlighting the importance of customer satisfaction, engagement programs, and positive customer advocacy in driving purchase decisions. Tailored marketing and product development strategy approaches that consider demographic nuances, such as age, gender, household size, and geographic location, can enhance customer engagement and market penetration.

The analysis of frequent purchase groups offers insights into broader lifestyle and consumption trends, such as the increasing importance of health and wellness, the need for convenience, and the value of social dining experiences. Businesses are in a

position to leverage these trends to develop products and services that resonate with consumer lifestyles and preferences. Regional differences, such as higher food category purchases in the Northern Harbour and South Eastern Districts, suggest localised consumption patterns that could inform targeted inventory and marketing efforts. Larger households tend to prioritise convenience (‘Frozen, Refrigerated, Canned, and Packaged Goods’), while smaller households or those living alone show varied priorities, underscoring the need to cater to different household needs and sizes.

The amalgamation of data from significant and regular purchases offers a nuanced view of the market, revealing not just what consumers are buying, but also how demographic, geographic, and lifestyle factors influence these choices.

An ensuing phase to this research project aims to further distil these insights, identifying underlying market dynamics and consumer segments with shared attributes. This will facilitate a more targeted approach for businesses looking to engage with specific consumer demographics effectively. Businesses can leverage these insights to tailor their product offerings, marketing messages, and distribution strategies to meet the specific needs and preferences of different consumer segments. Understanding, for instance, the central role of supermarkets in the consumer purchase journey presents opportunities for brand positioning and partnerships within these key retail spaces. The emphasis on both product quality and convenience across several categories suggests a dual focus for businesses aiming to cater to the contemporary consumer’s needs.

The varied recall rates across demographics, with younger consumers (18 to 29 age group) having the highest recall for advertisements, emphasise the need for targeted advertising strategies that cater to the specific media consumption habits

and preferences of different age groups. The mixed recall rates across traditional and digital advertising channels suggest the effectiveness of a multi-channel approach that combines the reach and familiarity of television with the engagement and personalization capabilities of digital platforms. The differences in ad recall between genders and among various household sizes indicate the importance of tailoring advertising strategies to the preferences and behaviours of specific demographic groups. Personalization and relevance of content can enhance ad recall and effectiveness.

The significant recall of advertisements on social media among younger demographics highlights the importance of digital platforms, particularly social media, as effective channels for engaging with Generation Z. Businesses should leverage these platforms through tailored content that resonates with these demographic values and interests.

Generation Z’s (Gen Z) exposure to a vast amount of information online can lead to information overload, making it challenging for businesses to capture their attention. To counteract this, companies need to focus on creating memorable, engaging, and authentic content that stands out amidst the noise. Gen Z’s strong inclination towards sustainability and authenticity suggests that businesses should highlight these aspects in their marketing efforts. Transparency about sustainable practices, product origins, and the social impact of purchases can appeal to Gen Z’s desire for ethical consumption. Given Generation Z’s digital nativity and shorter attention spans due to information overload, businesses need to explore innovative advertising strategies that engage this demographic. This might include interactive ads, influencer collaborations, or personalised marketing efforts that foster a genuine connection with the brand.

While Malta’s Gen Z shows a keen interest in sustainability, there’s a gap between aspirations and actions. Businesses can play a significant role in bridging this gap by making sustainable options more accessible, educating consumers on the impact of their choices, and encouraging a sense of community around sustainable practices. For sectors like sustainability, where there’s a noted gap between interest and action among Gen Z for instance, businesses can invest in educational initiatives and community-building efforts that empower consumers to make informed choices that align.

The paramount importance of convenience, particularly in location or accessibility, across various demographics underscores the necessity for businesses to optimise their physical and digital presence. Ensuring easy access to products and services can significantly influence consumer choice, making convenience a strategic priority for retailers and service providers alike.

The emphasis on superior product quality, especially among males and the 50 to 59 age group, indicates that quality is a significant factor in purchasing decisions. For businesses, focusing on high-quality products can foster customer loyalty and differentiate them from competitors, particularly in segments valuing long-term value and satisfaction. The analysis reveals regional variations in the importance of these factors, with Gozo & Comino showing a higher emphasis on product quality, while the Northern Harbour District places more importance on competitive pricing. The data highlights demographic nuances in purchase habit formation, with older age groups and larger households placing more importance on convenience and quality. This suggests that businesses targeting these segments should emphasise these factors in their product offerings and marketing messages. Enhance convenience by optimising location accessibility, improving online shopping experiences, and ensuring efficient

customer service. Implement dynamic pricing strategies that offer competitive value while catering to the specific needs and sensitivities of targeted demographics. Focus on product development strategies that prioritise quality, leveraging this as a key differentiator to attract qualityconscious consumers.

The adoption rates and comfort levels with AI technologies show a low to moderate engagement across the consumer base, with younger demographics, particularly those aged 18 to 29, demonstrating a higher comfort and usage level. This suggests a generational divide in technology adoption, emphasising the need for businesses to tailor their AI integration strategies to align with the preferences and expectations of different age groups.

Males report a higher comfort level with using AI for information gathering than females, indicating potential gender disparities in technology adoption. The analysis also highlights regional variations in online shopping and technology usage, suggesting localised differences in digital infrastructure, access to technology, and consumer preferences. Businesses are therefore to ensure that they cater to the specific needs and preferences of consumers when deploying technologydriven solutions. While online shopping preferences vary across product categories, there’s a significant inclination towards online purchases in specific categories such as “Fashion & Apparel” and “Served Foods & Beverages.” This indicates the growing importance of e-commerce platforms in facilitating consumer purchases, especially among younger consumers who show a higher propensity for online engagement. The moderate to high level of technology usage among consumers, particularly in the mid-life groups, often characterised by stability in career and personal life, as well as an increased focus on family, relationships, and achieving long-term goals. This group is frequently targeted as

a key demographic because they are often at a peak in their earning and spending capacity. Additionally, from a health perspective, it’s a time when individuals are encouraged to pay more attention to lifestyle. The data suggests that technology has become an integral part of their daily routines and professional lives.

This underscores the importance of businesses integrating user-friendly technological solutions that enhance productivity and customer interaction without alienating those less familiar with digital tools. Perceived complexity, necessity, privacy, and security concerns emerge as significant barriers to broader technology engagement. Addressing these barriers through user education, simplified interfaces, and transparent privacy policies could enhance technology adoption and trust among a wider demographic. Technology should focus on enhancing the consumer experience, personalised marketing strategies, and streamlined purchasing processes. Tailoring these solutions to cater to the technological comfort levels of different demographics can significantly improve consumer satisfaction and loyalty. Conversely, providing comprehensive training and support for employees on the use of advanced technologies is also crucial, where staff competence in utilising these tools effectively can foster more alignment between company and consumer.

Conclusion

The Malta Consumer Trends 2024 study offers an analysis of the local consumer landscape, providing insights for businesses aiming to navigate the dynamic market effectively. By aligning with both local preferences and global trends, businesses can develop strategic initiatives to meet consumer demands, foster loyalty when and where possible, and drive growth in the competitive Maltese market.

Executing a detailed examination of the present situation constitutes the primary phase in discerning dominant trends. Such a fundamental review is crucial, as it affords a comprehensive understanding of the current landscape, thereby aiding in the recognition of both nascent opportunities and forthcoming obstacles within the specified domain. Transitioning from this initial phase necessitates the astute employment of these findings, leveraging them to drive forward development. It is important to note that perfection is not a prerequisite at this juncture; the essence lies in establishing a solid base. A preliminary step, no matter how modest, lays the groundwork upon which further enhancements can be methodically constructed, provided the foundation is robust and well-defined.

A noteworthy point of discussion, based on comments during the conference, stems from the most recent population data for Malta, which state that Malta’s total population is composed of 404,675 (75%) people are Maltese citizens while 137376 (25%) are foreign residents. The demographic shifts due to significant migration, particularly from third-country nationals, alongside a minimal natural population increase, underscore the need for future focus on adapting market

strategies, consumer engagement, and policy-making to address the evolving demographic landscape and its implications for the economy and society. Traditional data collection techniques might not fully reflect the nuanced the evolving demographic landscape. Therefore, there exists a pressing need to enhance or supplement these methodologies with more targeted research strategies. These could include mixed-method approaches that integrate qualitative insights, localised surveys tailored to capture the experiences and preferences of migrant populations, and advanced data analytics to better understand the socio-economic impacts of these demographic shifts.

As we navigate the Malta Consumer Trends 2024, our success hinges on our adaptability, innovation, and a profound commitment to understanding and meeting the evolving needs of the Maltese consumer. This moment presents not only challenges but significant opportunities for growth and differentiation in the market. Embracing these changes with strategic foresight and a consumer-centric approach will enable us to not only thrive but also drive meaningful progress towards a sustainable and prosperous future for all stakeholders involved. Let us move forward with determination and a collaborative spirit, leveraging insights to shape a resilient and forward-thinking business landscape in Malta.

Background Introduction

As the global consumer landscape undergoes significant transformations, companies are increasingly inclined to explore consumer behaviour more thoroughly, adjusting their strategies to align with the changing patterns of consumer decision-making. However, access to information in Malta is limited and many businesses struggle to convert an international understanding into a strategy well-suited to Malta’s local context.

The Malta Consumer Trends 2024 initiative was designed to examine how consumer trends in Malta align with those around the world, highlighting both similarities and differences. By gaining insight into these subtleties and modifying strategies to fit these observations, local businesses can more adeptly manoeuvre through the dynamic market environment, enhancing their prospects for success.

Throughout this research process we were guided by questions such as: What are the salient Maltese consumer trends and how are they interacting with your market? Are international consumer trends relevant to the Maltese context? If so, do local businesses integrate them into their marketing strategies? If not, which consumer trends do Maltese businesses need to be aware of?

Strengthening an understanding of international consumer trends through a thorough desk research effort, presenting the results of a nationally representative study assessing consumer behaviour in Malta, and bringing together private industry, the public sector and academia for a series of exploratory panel discussions is our way of starting to address this gap.

The Malta Consumer Trends Conference 2024 is an initiative co-organised by Gordon Borg Urso, a digital marketing consultant, and B2B MALTA LTD (B2B). Gordon is an experienced digital marketing expert committed to revolutionising businesses with impactful online tactics. Boasting 20 years of direct experience, he has worked alongside successful brands both locally and internationally, spanning various industries. B2B, an advisory firm with over 25 years of experience, provides an extensive array of services, encompassing feasibility studies, continuous compliance, and adaptable workspace options. The company supports businesses throughout their development journey, encouraging the growth of both startups and well-established firms.

The report that follows has been prepared by B2B, leveraging decades of experience in market research. B2B focuses on commercialization assistance and development, meaning that amongst other services, Market Research falls within the direct scope of our mission and services.

Scope

The overarching scope of the study is to address the gap between the desire for an understanding of the Maltese consumer’s behaviour to inform strategic decisions and the availability of quality data acquired through primary research. Whilst the effort in its initial iteration is meant as an overview of the Maltese consumer market in general, it is structured to facilitate an ongoing cross-market research effort that factors in the variance in consumer behaviour across a broad array of markets.

Purpose, Procedures & Method

The purpose of the study

The study aims to provide an initial, broad overview of the consumer market in Malta, laying the groundwork for an informed analysis of prevailing consumer trends and preferences within the country. Nevertheless, the scope of this study extends beyond providing a mere snapshot of the Maltese consumer landscape. It is meticulously designed to serve as a foundational piece for an ongoing, comparative analysis across various markets. This approach acknowledges and addresses the diverse nature of consumer behaviour, recognizing that preferences and trends can vary significantly from one market to another.

In facilitating this comprehensive crossmarket effort, the study seeks not only to highlight the unique characteristics of the Maltese consumer but also to uncover potential parallels and contrasts with consumer behaviours in other markets. Such insights are invaluable for businesses

aiming to refine their strategic planning and operational decisions to better align with the needs and expectations of their target consumers, both in Malta and beyond.

Research Method and Procedures

This study employs a detailed methodology which focuses on understanding the patterns of significant one-time purchases versus frequent buying behaviours, both online and on-site, across 19 market categories. Data was gathered from a representative sample of 403 respondents, stratified by age, sex, and location, providing us with observations on 806 markets distributed naturally based on the categorisation of purchases as either ‘largest’ or ‘most frequent’. The distribution of markets for which we collected data, therefore, provides us with a clear snapshot of the frequency of largest purchases, and most frequent purchases, across the Maltese population.

This approach also allows for a granular analysis of consumer trends giving scope for the furthering of the research effort to eventually encapsulate a total of 250 responses for each category. The selection criteria for these categories are designed to encompass a broad spectrum of consumer interactions, ranging from Auto and Parts to Vacation, Travel & Wellness.

When designing the research method, we departed from the perspective that consumer behaviour differs depending on two fundamental aspects of the purchase:

(a) the size of the purchase (in euros), and (b) the frequency at which purchases are made. It is an assumption of this study that consumers making larger purchase decisions will tend toward a more discerning purchasing process that approximates popular conceptions of the ‘buyer’s journey’. On the other hand, smaller (more frequent) purchases will tend to be more a matter of habitual tendency which, when established, requires some external motivator to initiate a habitual change. In sum, large single purchases map onto a predictable purchase process, whilst when a habit is formed within a specific market category that encapsulates frequent purchases

that habit is maintained unless an external factor motivates an alternation in the habit, eventually resulting in a new habit being formed.

The research portion dealing with larger purchases is therefore structured around the Engel-Blackwell-Miniard Model, which outlines a seven-point purchase decision process. This model serves as a framework for the research instrument, guiding the exploration from Problem Recognition to Loyalty and Advocacy. On the other hand, when considering frequent purchases, we looked to gauge key elements such as what initiated the start of the habit, and if this has changed, identifying the main driver that caused the change.

To ensure a comprehensive understanding of consumer behaviours, the study utilised a dual-method approach incorporating Computer-Assisted Telephone Interviewing (CATI) and Computer-Assisted Web Interviewing (CAWI). These methods facilitate a wide-reaching demographic engagement, enhancing the depth and representativeness of the collected data. The data for this study was collected between February and March 2024.

Post-collection, the data passed through a rigorous cleaning and preparation phase, ensuring its readiness for analytical processing. The analysis includes basic descriptive statistics for numerical variables and frequencies and percentages for categorical variables. This report also comes with visual representations to explain the distribution and relationships within the data, supported by cross-tabulation and statistical tests to ascertain significant differences or associations between variables. By adopting a meticulous methodological approach, this study is intended to deliver a multi-faceted view of the current consumer landscape in Malta.

Limitations, Precautions & Mitigation

It is important to acknowledge the inherent limitations that accompany this research. Firstly, the reliance on self-reported data through CATI and CAWI methods may introduce biases, as respondents’ perceptions and recollections can affect the accuracy of the data collected.

Another constraint involves the sample size and the distribution of responses across the 19 selected market categories. Despite intentions for comprehensive representation, the 403 participants may not sufficiently capture the entire spectrum of consumer behaviours within each sector, particularly in specialised niches or emerging markets. Consequently, this could result in the underrepresentation of certain segments, attributed to an inherent inclination towards the categories of largest and most frequent purchases. While the study documents 1,612 purchasing events, its objective extends to achieving marketwide representativeness, aiming for a total of 4,750 purchasing instances, or 250 per market category. Furthermore, the inclusion of market categories has been intentionally limited to 19 from a broader universe, with the remaining categories earmarked for examination in subsequent phases of market research.

Moreover, specific consumer segments that are not reachable through this data collection method; for instance, while study takes into consideration demographic shifts in Malta and Gozo, migration trends might not be entirely picked up by the samples. It highlights that third-country nationals constituted a significant majority (83.1%) of the net migration figure in 2022, underpinning the population growth for that year. The net migration influx was quantified at 21,798 individuals, propelling the total population to 542,051, marking a 4.2% increase compared to the preceding year. Notably, the period witnessed the lowest natural population increase in

fifteen years, a mere 79, derived from the balance of 4,309 live births and 4,230 deaths. This data underlines the critical role of migration in population dynamics and suggests potential shifts in market demographics, consumer profiles, and workforce composition, presenting both challenges and opportunities for businesses and policymakers.

The segmentation of categories, though extensive, might also omit specific consumer trends not encompassed within the predefined sectors. Given the general scope of the study, we feel that the approach adopted is the appropriate balance of comprehensiveness and broadness that optimises the insights across sections and market segments.

Additionally, the research framework based on the Engel-Blackwell-Miniard Model, while comprehensive and informative, is still simply a model, and therefore might not fully account for the rapid evolution of consumer behaviours. Whilst this may lead to gaps in capturing real-time shifts in consumer behaviour, it is outside the scope of the current study to redefine the steps in the buyer’s process.

To mitigate these limitations and ensure the validity and reliability of the study’s findings, several precautions have been implemented. Rigorous data cleaning and preparation protocols are in place to address inconsistencies and errors in the dataset, enhancing the accuracy of the analysis. The study employs a mix of both quantitative and qualitative analysis techniques to provide a more nuanced understanding of consumer behaviours, reducing the reliance on any single methodological approach.

In recognizing the potential for bias in self-reported data, the research design includes measures to minimise its impact,

such as the use of neutral wording in survey questions and the inclusion of validation questions to cross-check the consistency of responses. Additionally, B2B has conducted periodic reviews of the survey implementation process to identify and address any methodological challenges that arise, ensuring continuous improvement in data collection and analysis techniques.

To address the limitations associated with the sample size and market category segmentation, the study has employed statistical techniques to extrapolate findings to broader populations, where applicable. We have also done our utmost to remain vigilant to emerging trends and sectors, adapting the study’s framework as necessary to reflect the evolving consumer landscape.

By acknowledging these limitations and implementing targeted precautions, this report aims to provide a robust and comprehensive analysis of Maltese consumer behaviours, offering valuable insights while maintaining a critical awareness of the study’s scope and boundaries.

1 https://nso.gov.mt/world-population-day-11-july-2023/

Survey Findings & Observations

Market Categories

The survey’s selection of categories for evaluation serves as an introductory framework for scrutiny, with the provision to expand or modify the scope in future research iterations. This foundational methodology is crafted as an exploratory step, adaptable yet structured to preserve the integrity of longitudinal trend analysis and to mitigate potential biases. The chosen categories are reflective of internationally recognized market segments that

demonstrate significant online presence and consumer engagement. This focus on popular online categories is intentional, stemming from the ubiquitous nature of digital platforms which consistently inform and influence consumer choices and preferences. The intent is to establish a robust baseline from which to understand consumer behaviour, while retaining the flexibility to adapt to emerging trends and shifts within the digital marketplace.

A summary of the categories included in this research effort:

[Auto Purchase, Rental and Parts]

[Banking, Insurance & Investment Services]

[Consumer Electronics]

[Entertainment]

[Fashion & Apparel]

[Fresh Produce]

[Frozen, Refrigerated, Canned, and Packaged Goods]

[Gambling and lottery services]

[Health and Wellness]

[Home Improvement, Ironmongery, DIY, and Hardware]

[Household and Non Food Items]

[Internet, TV & Telephone Service]

[Large Home Appliances]

[Meat and Seafood]

[OTC Health & Personal Care and Beauty]

[Real Estate Purchase or Rental Agreement]

[Served Foods & Beverages]

[Transport Services - taxis, bus & other services]

[Vacation, Travel & Wellness]

Large/Expensive Purchases

As outlined in more detail above, a part of our method was to ask different sets of questions for different types of purchases.

Below are the insights garnered from the purchases that fall within the categorisation of ‘large’ or ‘expensive’.

Large / More Expensive Purchase Groups - Frequency & % of Purchase Events

The aggregate count response for this section amounted to 806, with an annotation or correction factor of 1, attributable to the survey design wherein each respondent was prompted to disclose two significant purchase instances. It is pertinent to note that the sampling methodology employed was stratified by demographic attributes such as gender, age, and geographical location, rather than by specific purchase categories. This allowed respondents the flexibility to select any categories for their responses, devoid of predefined segmentation constraints.

The research methodology has been meticulously crafted with a pre-emptive consideration of potential constraints. In the data collection we anticipate the introduction of self-reporting biases, which are characteristic of such methodologies. The current sample encompasses 403 respondents, yielding 1,612 instances of purchasing behaviours across 19 distinct market categories. This sample, while robust, from a participant profile (gender, age and location) perspective, it was not designed to capture the full diversity of consumer actions or purchases.. Acknowledging this, the study does not purport to offer an exhaustive representation but rather a strategic crosssection of prevalent purchasing patterns, with an overture to sectors of significant and frequent transactions. Therefore, general observations or statistically valid results from the market research effort, are being set out in this report.

The research’s scope has been deliberately circumscribed to these categories, from a vaster potential set, to ensure methodological precision and manageability within the initial phase. The robustness of the exercise lies in the coverage encompassing a comprehensive range of categories, with a benchmark of documenting 4,750 purchasing events— approximately 250 per market category. This approach is calculated to incrementally mitigate the noted limitations, enhancing representativeness with each successive phase of data collection. The approach will also require to skew the sample in line with consumer profiles for each market category.

Top-Level Snapshot: Large/Expensive Purchases

During the data collection phase, variations in how different demographics perceive what constitutes a ‘large’ or ‘expensive’ purchase became apparent. This diversity in interpretation was not curtailed but rather allowed to evolve organically, providing nuanced insights into each demographic’s economic landscape and their subjective thresholds for what they consider affordable or indicative of a significant expenditure. Indeed, “Large or Expensive Purchases” is a subjective term shaped by a confluence of financial capabilities, perceived value based on product attributes, consumer psychology influenced by personal and societal factors, and the broader economic environment that dictates market prices.

Such variances in perception contribute valuable information regarding the relative financial flexibility across consumer segments. This understanding underscores the subjective nature of economic assessment within different demographic groups, revealing the multifaceted concept of ‘expense’ that interweaves with personal financial standing, value assessment, and individual prioritisation of spending.

By allowing these natural disparities in perception to surface, the study gleaned a deeper layer of consumer behaviour— insights into the psychological and socioeconomic factors that influence purchasing decisions. This aspect of the research illuminates the intricacies of affordability and its implications for market segmentation, providing businesses with a more textured understanding of their target audiences’ spending capacities and how they classify and approach their purchasing priorities.

Vacation, Travel & Wellness tops the list with 139 counts, suggesting a high consumer engagement and interest in products and services related to travel, leisure, and personal well-being. This could reflect a consumer trend towards valuing experiences and self-care, perhaps influenced by a growing emphasis on the importance of work-life balance and mental health. Consumer electronics ranks second with 104 counts, indicating a robust consumer interest in electronics. This may be driven by continual innovations in technology, the integral role of electronics in modern life, and the steady demand for the latest gadgets and tech solutions. Large Home appliances showed 107 counts, which is reflective of significant consumer transactions. The investment in large home appliances typically involves considerable thought and financial commitment, indicating this market’s relevance to everyday domestic life and long-term household planning. Household and Non-Food Items, with 92 counts, also indicates a strong consumer focus, possibly because these items are essential for home maintenance and living standards.

Vacation, Travel & Wellness seem to attract marginally higher responses from females (18.1%) when compared to males (16.2%), possibly reflecting leisure and self-care trends. The 40 to 49 age group (23.4%) leads in this category followed by those aged 30 - 39 and those aged 50 - 59, which may be related to mid-life leisure pursuits, family vacations, and a stronger and more stable financial position. The Northern District (20.4%) and Married/Partnered individuals (19.4%) also show high percentages, suggesting that this area may have a higher disposable income or that couples are more likely to invest in travel and wellness together.

Consumer electronics purchases were more popular amongst males (15.7%), who seem to be more inclined towards consumer electronics than females (10.6%). The 18 to 29 age group (20.3%) shows the highest incidence rate, indicating a youthful attraction to the latest tech and their somewhat restricted disposable income. The Western District (15.7%) has the highest probability of indicating this market as one of their expensive purchases, suggesting tech-savviness or availability in the area. Single individuals (17.2%) and students (20.4%) also demonstrate high rates, perhaps due to lifestyle or educational needs.

Large Home Appliances attracted higher response rates from females (14.5%) than their male (11.8%) counterparts, possibly due to household management considerations. The 50 to 59 age group (16.7%) leads in this category, which may correspond to home upgrades or replacement cycles. Interestingly, the Gozo & Comino District (25.0%) shows a notably high percentage, indicating either a recent surge in appliance purchases or a smaller sample size impacting the percentage.

Household and Non Food Items were slightly higher amongst females (11.1%) than males (11.8%), which may relate to the traditional

role of women in home management. The 50 to 59 age group (14.6%) has significant interest, potentially reflecting a stage of life with a focus on home maintenance or improvement. Retired/Pensioners (13.2%) also show substantial interest, possibly due to having more time for home affairs or downsizing needs.

Frozen, Refrigerated, Canned, and Packaged Goods purchases are relatively balanced between males (8.2%) and females (7.9%). The 60+ age group (12.1%) shows the highest response rate, which could be due to convenience, dietary needs, or the fact that traditionally larger purchases (such as real estate, automobiles, appliances, and so on) have already been made. Larger households with 4 members (9.8%) and 5 members (9.4%) also show higher response rates, possibly for bulk purchasing or family meal planning.

Served Foods & Beverages attracted higher responses from females (9.7%) than males (5.2%). The age group with the most interest is the 60+ (12.1%), which might indicate a preference for convenience or social dining experiences. Home Carers/ Non Gainfully Occupied (16.1%) show a considerable percentage, suggesting that this demographic may frequently opt for ready-to-eat options and dining out.

Meat and Seafood attracted higher responses from females (7.0%) who might have a slightly higher incidence rate of large purchases in meat and seafood compared to males (5.2%). The data shows a clear trend that the likelihood of significant purchases being made in meat and seafood increases with age, with those aged 60+ (10.8%) having the highest percentage, followed by the 50 to 59 age bracket (9.0%).

Residents of the Northern Harbour District (8.1%) and the South Eastern District (7.5%) report more significant purchases than other districts, which might be indicative of regional preferences or higher availability of such products in these areas. Larger

household sizes, specifically households of two (7.4%) and one-person households (6.8%), show more substantial purchase activity.

Auto Purchase, Rental and Parts received higher responses from males (9.6%) who were far more likely to have made a large purchase in this category than females (2.3%). The age group of 18 to 29 years old shows the highest percentage (11.4%) of significant auto-related purchases. This could indicate a trend of early acquisition of cars among the younger population or that this age group is actively engaged in automobile maintenance, perhaps after having bought or been given a second hand automobile. The Southern Harbour District leads in auto-related large purchases (8.4%), followed closely by the Western District (6.9%).

Fashion & Apparel purchases were higher amongst females (6.3%) who show more response rates than males (3.3%), aligning with common retail trends. Young adults, particularly the 18 to 29 age group (11.4%), show the most response rates, likely due to fashion being a form of self-expression for this demographic and the greater propensity to utilise online purchasing means. The 5+ household size category (10.4%) indicates a possible requirement for larger purchases due to more significant family needs.

The diversity in large purchase categories, from essentials to luxuries, highlights varied consumer priorities, offering businesses insights into potential market segments for focused engagement and product offerings. Understanding the subjective nature of what constitutes a significant expenditure for different demographics enables businesses to tailor their marketing messages more effectively. For instance, products categorised under “Vacation, Travel & Wellness” show higher engagement from females and particular age groups, suggesting that marketing efforts for these

services should emphasise emotional benefits, such as relaxation and family bonding, which resonate with these segments. This overlays onto the trend towards valuing experiences, and may indicate an opportunity for businesses to position their products and services not just as purchases but as integral components of the consumer’s lifestyle. This may involve emphasising the experiential aspects of products or incorporating lifestyle elements into the brand narrative.

Furthermore, gender-specific preferences in categories like fashion & apparel and auto purchases underscore the importance of tailored marketing strategies to effectively reach and engage target demographics. A consideration of these tendencies provides businesses with a valuable indication on how to align their strategies with consumer demands, identify growth opportunities in specific market segments, and tailor offerings to meet the evolving needs and preferences of consumers. For example, The diversity in financial flexibility and value assessment across consumer segments highlights the need for varied pricing strategies (where possible). Companies may consider offering a range of product options catering to different budgetary constraints while emphasising value for money to appeal to more price-sensitive consumers.

Information Search Dynamics for Significant Purchases [Large Purchases]

In the intricate process of consumer decision-making, especially concerning significant purchases, the mechanisms through which consumers seek and evaluate information play a pivotal role. A core component of this study has been to attempt to illuminate the most crucial resources consumers rely on when exploring their options. Our objective is to dissect the array of influential factors guiding consumer preferences, aiming to construct a well-defined hierarchy of informational resources. This analysis spans from the ubiquity of online platforms, including reviews and company websites, to the enduring value of personal recommendations, each medium offering distinct advantages in influencing consumer decisions.

This section endeavours to delineate the prominence of these information channels, delving into the rationale behind their varied impacts. By doing so, we aim to furnish businesses with actionable insights, enabling them to optimally position their offerings within the consumer decision-

making landscape. Respondents were asked to select the resources they utilise from a gamut of information sources, spanning both digital and physical realms—ranging from company websites and comparison platforms to social media, industry reports, and the invaluable word of mouth from close acquaintances, as well as direct interactions at shops, showrooms, and through sales representatives.

The findings reveal a marked preference for Offline Channels, particularly shops and showrooms, as the predominant method for information gathering before making substantial purchases. This preference is especially notable in sectors identified as leading in the Large Purchases category: Consumer Electronics, Vacations, Travel & Wellness, and Large Home Appliances. Such a trend underscores the enduring importance of physical retail environments in these industries, suggesting that despite the digital age, the tactile and visual experience of viewing a product in person remains an invaluable part of the consumer journey.

For businesses operating within these sectors, the implication is clear: while digital presence and online marketing efforts are undeniably important, the physical showroom or shop continues to hold significant sway in the consumer’s decisionmaking process. This insight prompts a strategic reevaluation of how businesses can integrate and optimise their offline channels to complement their online efforts, ensuring a seamless and holistic consumer experience that effectively bridges the gap between digital exploration and physical purchase.

With this said, it is essential for businesses to understand their specific target audience prior to reaching conclusions on whether or not to maintain or establish brick and mortar stores. Below, we delve more deeply into the difference between demographic profiles that we observe in the data focusing on how they gather information from various channels, both online and offline.

Information Search [Large Purchases] - Frequency & % of Response within Group

Taking the most popular channel (Offline - Shops, etc.), males and females seem to utilise this means of gathering information fairly equally (34.3% and 35.7% respectively). Interestingly, when considering age, all ages seem to utilise this means fairly equally (ranging from 25.9% to 28.2%), whilst those aged 60+ mentioned this means of information gathering a staggering 54.2% of the time, indicating that a majority of these consumers utilise this information channel when considering whether or not to make substantial purchases.

Considering the second most popular channel for information gathering (Online - Company Websites), we find that whilst there is some more variance in the mention of this mode of information gathering across age groups, there is still a striking inverse relationship when considered with the aforementioned offline channel. In fact, this channel was only mentioned 13.3% of the time among those aged 60+ when compared to 37.1% by those aged 30 - 49, 36.1% by those aged 18 - 29 and 32.3% by those aged 50 - 59.

The youngest demographic (18 to 29) is more inclined towards utilising social media (32.9%), while older age groups show varied preferences, with those aged 60+ mentioning this means of information gathering just 7.1% of the time, those aged 50 - 59 mentioning it 15.3% of the time, and those aged 40 - 49 and 30 - 39 mentioning it 23.4% and 30.7% of the time. This reflects the growing importance of digital platforms in reaching younger demographics. Meanwhile, older demographics have varied preferences, indicating the need for a multichannel approach to cater to all age groups effectively.

Consumer preferences varied by locality, suggesting that geographic location influences information-gathering behaviours. Half (50%) of those from Gozo said that they use Offline - Shops, etc. when compared to 32.4% of those from the Western District, 33.8% of those from the Northern District, 36.0% of those in the Southern Harbour District, and 42.5% of those living in the South Eastern District. On the other hand, the Western District indicated that they use the company’s website most frequently (35.3%), followed by those in the Southern Harbour District (30.1%), Gozo (30.0%), the Northern Harbour District (29.7%), the Northern District (23.9%) and the South Eastern District (21.6%).

This analysis suggests that smaller households might have different information-seeking behaviours compared to larger ones, possibly due to the differing complexity in decision-making. Respondents from smaller households seem to tend to use offline means more than larger households, whereby respondents who live alone use this means 39.8% of the time, and those who live with one other person use it 46.5% of the time. On the other hand, respondents in households of 5 or more use this 25.0% of the time, and those in households of 4 and of 3 use this mode of information gathering 26.8% and 32.0% of the time, respectively. On the other hand, larger households were more likely to use the company website as a source of information, whereby those in households of 4 came in at 35.3%, those in household of 5 or more 31.3%, with those who live alone being at 26.1%, and those living with one other at 24.3%. Understanding these

dynamics can help in crafting messages that resonate with the target household size.

For businesses, a demographic indication for a preference for online channels underscores the need to strengthen online presence, improve website usability, enhance content quality on digital platforms, and actively manage social media and review sites. On the other hand, the importance of word of mouth suggests investing in customer satisfaction and loyalty programs to encourage positive advocacy among family and friends. This second factor is indicated as fairly important across all age groups, with those aged 50 - 59 coming in at 31.9%, followed by those aged 18 - 29 at 26.6% and those aged 60+ at 25.8%.

Overall, the above indicates the need for an integrated consumer journey which in turn calls for an optimised omni-channel strategy, ensuring consistency and synergy between online information availability and offline experiences. The use of analytics and data to personalise marketing and sales strategies based on the preferred channels of different consumer segments can therefore enhance engagement and conversion rates. Whilst we have already seen the need for personalisation in the international trends discussed above, the variance in the tendency to gather information across the above demographics indicates the value of establishing a segmented approach to this personalisation. Businesses would therefore do well to attempt to leverage a seamless and tailored move from online to physical experiences with any internal digitisation and optimisation efforts, whilst keeping a keen eye on the measurement of customer satisfaction to maintain and grow their market standing.

Evaluation of Alternatives [Large Purchases]

Outside of understanding the mix of information resources that respondents utilise, we also wanted to ascertain the resource which respondents considered most important in their selection. Therefore, respondents who provided more than one answer to the previous question were asked to identify the most important sources of information from their responses. It is also noted that information gathering (previous section) is characterised by a broader stage that involves collecting information from

various sources to understand what options are available. Because consumers are in the exploration phase, they might engage with multiple sources extensively, leading to higher response rates. Additionally, when asking about the most important of the alternatives, some respondents insisted that all factors they selected were important in approximately equal measure. This influences the total count in the figures displayed, as in such cases, all factors selected were added to the analysis.

Offline channels, primarily the shops/ showrooms option was again revealed as the most important resource used. This is followed by Word of Mouth (another offline channel) and the company’s own website (online). This further demonstrates the importance given by the Maltese consumer to being able to go on site to gather information, and the perceived importance of reference made to others to get more information about consumer options.

Offline (shops, showrooms, etc.) was given as the most important resource for information with little variance between males (32.1%) and females (33.9%), but when considering age, those aged 60+ were significantly more likely to consider this as the most important factor, with a majority 53.3% of them doing so. This is in stark contrast to other age groups, where those aged 40-49 consider it to be most important 28.2% of the time, and those aged 5059 27.1% of the time. Interestingly, those ages 18 - 29 actually found the company’s website to be the most important (26.6%) as did those aged 30 - 39 (29.3%). These age groups indicated going on site to be the more important option 22.2% and 21.4% of the time respectively.

On the other hand, 29.9% of those aged 50 - 59 considered word of mouth to be the most important factor. Those aged 60+ also considered this to be an important factor at 23.3%, followed by those aged 40 - 49 at 21.0%.

When considering social media as a channel for gathering information, younger generations were more likely to indicate this as the most important, with those aged 30

- 39 indicating this 24.3% (more than on site visits which stood at 21.4%) and those aged 18 - 29 coming in at 19.0%.

The above analysis gives credence to the need for a multi-channel approach that balances online presence with offline experiences and leverages the power of word-of-mouth. Given the strong preference for offline channels, particularly among older demographics, businesses should focus on optimising the in-store experience, ensuring that showrooms and physical retail spaces are conducive to exploration and evaluation. For younger demographics, a compelling, informative, and user-friendly online presence is crucial. This includes optimising the company’s website for ease of navigation, comprehensive product information, and engaging content that aids in the evaluation process.

Encouraging and facilitating positive word of mouth through exceptional customer service, loyalty programs, and engagement strategies that turn satisfied customers into brand advocates, especially targeting the 50-59 age demographic who consider this to be a highly important aspect.

Social Media Platforms3

Respondents who declared to use social media platforms for information gathering were asked about the usage of various social media platforms like Facebook, Instagram, Twitter, TikTok, and YouTube for information gathering. This indicates what consumers consider to be the most important social media for gathering information.

3 The percentages in this section are an expression of the total sample of respondents (including non-social media users).

The data indicates that social media platforms are utilised differently across various demographics, with Facebook being the most used across the board. Instagram sees its highest use among younger demographics. YouTube is notable for its use among the 30 to 39 age group and individuals with higher education, highlighting the platform’s value for detailed information and educational content. Facebook is used by females (16.1%) slightly more than males (14.3%) used Facebook to gather information. The 18 to 29 age group uses Facebook the most for information gathering (28.5%), which gradually decreases with age. Larger households, especially those with five or more members (20.8%), seem to use Facebook more for information gathering. Females (5.4%) used Instagram more than males (2.7%), possibly reflecting the platform’s popularity among women, and younger users, especially those between 18 to 29 (10.8%), are most active on Instagram, aligning with the platform’s demographic trends.

A slightly higher percentage of males (4.7%) used YouTube compared to females (2.0%), perhaps reflecting different content consumption preferences. The 30 to 39 age group (7.9%) shows the highest use of YouTube, which may suggest that this platform’s informative content resonates with this demographic.

TikTok’s overall usage for information gathering is minimal, and therefore any differences must be taken with a grain of salt. Where it is used, however, it tends to be among younger, single individuals.

For businesses aiming to enhance their digital marketing strategies, these insights emphasise the importance of platformspecific content creation. Understanding the demographic alignments in terms of platform use intention (in this case, for searching for information prior to making

a large purchase) of each social media platform can help in crafting messages that resonate with the target audience, whether it be through engaging visual content on Instagram for younger consumers or informative videos on YouTube for a more mature audience seeking educational content.

With its widespread use across age groups and households, Facebook remains a critical platform for marketing and information dissemination. Businesses should maintain a strong Facebook presence. Ad campaigns, informative posts, and community engagement can be tailored to the demographic nuances observed. Given Instagram’s popularity with the younger demographics, businesses in visual or lifestyle industries can leverage this platform for branding and marketing. Instagram stories, posts, and reels should be visually appealing and could be used to showcase products, behind-the-scenes content, or educational material that resonates with this audience.

As YouTube is popular for its detailed content among individuals aged 30 to 39 and those with higher education, businesses can use this platform for tutorials, product demonstrations, and educational content. Sectors like science, engineering, and specialised professions might benefit from expert-led webinars or how-to videos on YouTube.

Factors Influencing Product/Service Selection

This section highlights the multifaceted nature of consumer decision-making and underscores the importance of a strategic approach that addresses diverse consumer needs and preferences. Personal desires and requirements, along with price and affordability, are universal priorities across demographics, emphasising the need for products and services to meet personal needs and be priced competitively.

Participants were first asked what factors they consider when looking to make their purchasing decision, allowing for multiple responses, following which they were asked to identify the most important factor. The importance of personal desires and requirements is fairly consistent across demographics. Product features and quality are most critically viewed by consumers with higher education and those in specialised occupations, who may prioritise functionality and long-term value. Price sensitivity is notably significant among younger consumers and students, emphasising the need for competitive pricing strategies to attract these segments.

Both males (39.6%) and females (39.4%) show a similar emphasis on personal desires and requirements in their decision-making process, but the importance of Price and Affordability is a very close second to both (38.7% and 38.9% respectively). The 60+ age group (46.3%) is the most likely to prioritise personal desires and requirements, followed by those aged 30 - 39 (45.7%). The Northern District (45.8%) and Gozo & Comino District (40.0%) place a high importance on personal needs, indicating potentially diverse local consumer cultures or market offerings in these areas.

The importance of Price and Affordability is most pronounced in households with 5 or more people (47.9%), decreasing steadily in importance across household sizes to 35.2% for those living alone. On the other hand, price was an important factor to those who said they are single (48.0%), but less so for those who are Married/Partnered (36.4%).

When asking about the most important factor, some respondents insisted that all factors they selected were important in approximately equal measure, which influences the total count in the figures displayed, as in such cases, all factors selected were added to the analysis. A slightly higher percentage of males (33.5%) than females (32.8%) considered personal desires and requirements as the most important factor. The 60+ age group (42.1%) most considered personal desires and requirements, which could indicate that as people age, their personal preferences become more pronounced in purchasing decisions. Consumers in the Gozo & Comino District (40.0%) and the Western District (37.3%) highly valued personal desires and requirements, potentially reflecting regional characteristics or lifestyle choices that emphasise individual needs.

The consideration of price as a determining factor in consumer decision-making underscores a fundamental aspect of consumer behaviour: the quest for value across different markets and consumer segments, price sensitivity often emerges as a pivotal consideration, influencing not only the choice between competing products or services but also shaping broader purchasing patterns and brand loyalty. For the Maltese consumer, budget limitations are a highly important consideration. This of course becomes especially prominent in economies facing inflationary pressures or among demographics with limited disposable income. In fact, this was the most important factor for those aged 1829 (33.5%), as this age group tends to have a lower disposable income. Interestingly, however, it was also the most important factor when considering those aged 50 - 59 (32.6%). Those who live in the Southern Harbour District also marginally considered this factor to be the most important (30.7%), as did those in the Northern Harbour District (31.1%).

The third most important factor on average is that of the product features and quality. Those aged 18 - 29, however, find this to be the second most important (27.2%) second to price and before personal desires and requirements. It is also ranked as the second most important for those in the South Eastern District (32.8%), and by those living in Gozo (35.0%). Finally, those in households of 5 or more individuals considered this factor to be the most important of the lot (35.4%).

The consistent emphasis on personal desires and requirements across various demographics underlines a critical insight for businesses: the imperative to design products and services that are not only adaptable but are deeply aligned with the nuanced preferences of individual consumers. This trend suggests that success in today’s competitive market is intricately linked to a company’s ability to understand and cater to the unique desires of its customers, transcending the traditional one-size-fits-all approach.

The data indicates that consumers universally prioritise products and services that resonate with their personal needs and desires. This is especially pronounced among the older demographics, where there is a significant inclination towards products that cater to specific personal preferences and requirements. For businesses, this signals a need for a nuanced understanding of their target markets, suggesting that product development and marketing strategies should be finely tuned to address the specific needs of different age groups, lifestyles, and possibly even cultural contexts.

Interestingly, the analysis also points out that consumers with higher education show a marked preference for product features and quality, indicating a segment of the market where functionality and long-term value are paramount. This insight suggests that for certain consumer segments, the appeal of a product or service is significantly enhanced by its ability to deliver on specific, high-level requirements and quality standards.

The aspect of price sensitivity, particularly pronounced among younger consumers and larger households, unveils a complex yet pivotal dimension of consumer behaviour. This trend highlights a robust demand for competitively priced offerings, signalling an essential strategy for businesses aiming to capture and retain these key segments. It underscores not merely the necessity of competitive pricing but also the strategic nuance required in structuring price points that appeal to these demographic groups.

Younger consumers, often characterised by a lower disposable income, exhibit a heightened sensitivity to price, which significantly influences their purchasing decisions. This group’s price-conscious behaviour suggests a market segment that is continuously seeking the best value for money, underlining the importance for businesses to position their products and services as economically viable options without compromising on quality. For companies, this necessitates a delicate balance between maintaining affordability

and ensuring profitability, possibly through the optimisation of costs, economies of scale, or innovative pricing strategies such as subscription models or tiered pricing plans.

Similarly, households with five or more members present a distinct market dynamic where the aggregate cost of products and services becomes a critical factor in decision-making. The economic pressures of supporting a larger household size amplify the need for products and services that offer practical solutions at accessible price points. For businesses, this demographic’s pronounced price sensitivity offers an opportunity to design bulk purchase discounts, family plans, or bundled offerings that provide tangible value, thereby appealing to the economic sensibilities of these consumers.

The significance of price sensitivity among these groups also highlights the broader implication of strategic pricing in building brand loyalty and consumer retention. By effectively meeting the price expectations of younger consumers and larger households, businesses can not only attract these segments but also cultivate a loyal consumer base that values the brand for its alignment with their financial realities and needs.

Furthermore, the strategic importance of pricing extends beyond mere cost competitiveness to encompass the perception of value. This involves a sophisticated understanding of how price points are interpreted by consumers in terms of quality, value for money, and brand positioning. Companies that succeed in this arena are those that manage to communicate the inherent value of their offerings, thereby justifying their price points in the eyes of their target consumers.

The emphasis on product features and quality, particularly among consumers with higher education, illuminates a discerning consumer segment that places premium value on functionality and longterm viability. This preference underlines a significant market opportunity for

businesses that can deliver high-quality, feature-rich products. Such consumers are not merely looking for products that meet basic needs; they are in pursuit of offerings that provide enhanced performance, superior quality, and innovative features that justify a higher price point.

This demographic’s sophisticated demands reflect a broader trend towards informed consumerism, where purchases are made with a keen eye on the product’s ability to deliver value over time. For businesses, this translates into a compelling directive to invest in research and development, pushing the boundaries of what their products can offer. The focus on quality and features demands a commitment to excellence, where product development is guided by a deep understanding of consumer needs, technological advancements, and the potential for innovation to drive user satisfaction and engagement.

Engaging this discerning consumer base requires more than just high-standard manufacturing; it necessitates a holistic approach that encompasses the user experience from product design to postpurchase support. Companies that succeed in capturing the attention and loyalty of this segment are those that can clearly articulate the unique value proposition of their products, demonstrating how the features and quality of their offerings stand out from the competition.

Assessment & Final Purchase Decision

The final step in the buyer’s journey which we looked to assess is the final purchase decision, which encapsulates a final assessment of the options available to the consumer. Here we specifically asked respondents how they assessed between the different options in order to make their final decision.

Seeing products in person is the most popular method, with a significant number of respondents (both male and female)

indicating they assess products this way. Seeking advice from friends, family or experts also shows a considerable count, though less than seeing products in person. The third most popular mode of assessment was through comparing product reviews and ratings online, followed closely by reading product specifications and descriptions.

Seeing Products in Person was observed amongst more females (52.5%) than males (48.6%), which may indicate a preference for tangible shopping experiences among women. The trend increases with age, with the highest percentage among those 60+ (61.7%). This suggests older consumers may value the in-person evaluation of products more than younger consumers. With that being said, this mode of assessment was the most prevalent one across all age groups, regions, and household sizes, indicating a strong general tendency to rely on it.

The South Eastern District (53.7%) and the Northern Harbour District (53.2%) had the highest response rates for this mode of assessment as regions, possibly indicating accessibility in these areas. Married or partnered individuals (53.6%) and separated or divorced individuals (51.9%) are more likely to see products in person, which could be tied to household decisionmaking for shared use items.

Larger households, especially those with 3 members (30.7%), tend to seek advice more, which could be due to the collective input needed in purchasing decisions for the household. Older age groups, particularly those over 60 (27.1%), also value advice from personal networks, which may reflect a preference for trusted opinions over impersonal sources.

Younger age groups, particularly 18 to 29 (24.1%), and 30 to 39 (22.9%) engage more with online reviews and ratings, reflecting the digital savvy of these demographics. Those with MFQ 7&8 qualifications (31.5%) also make more use of online reviews, potentially reflecting a higher research inclination. Reading product specifications and descriptions was more popular amongst higher education levels than lower ones, correlating with a greater reliance on reading specifications and descriptions, with MFQ 7&8 at 29.0%.

The final purchase decision, as a crucial juncture in the consumer’s journey, involves a multifaceted assessment of available options, incorporating both traditional and modern evaluative methods. The findings

indicate a diverse array of strategies employed by consumers, with a notable preference for tangible, experiential assessments alongside the utilisation of digital resources for informed decisionmaking.

The preference for seeing products in person as the most popular method of assessment highlights a significant insight: despite the digital revolution, physical interaction with products remains paramount in the Maltese consumer’s decision-making process when it comes to substantial purchases. This trend is more pronounced among females and increases with age, suggesting a demographic tilt towards tangible shopping experiences. The highest preference among those aged 60 and above underscores a potential market strategy for businesses to enhance their physical retail experience, especially for products targeting older demographics.

Interestingly, the geographical variations in preferences, with higher rates in the South Eastern District and the Northern Harbour District, may indicate regions with better accessibility to physical retail outlets or a cultural inclination towards in-person shopping experiences. This geographic insight suggests a tailored approach to retail presence and marketing strategies, emphasising the importance of physical store locations in these areas.

The reliance on advice from friends, family, or experts, particularly among larger households and older age groups, signifies the continued value of personal recommendations and trusted opinions in the decision-making process. This finding indicates an opportunity for businesses to leverage word-of-mouth marketing strategies and to engage with consumers in a way that encourages them to share positive experiences with their personal networks, giving credence to traditional key metrics such as the Net Promoter Score and Customer Satisfaction surveys.

The engagement with online reviews and ratings, especially among younger demographics and those with higher education levels, reflects the digital literacy

and research inclination of these segments. It also may indicate a strong reliance on the social validation of a product/service, and the power of brand ambassadors and influencer marketing. This insight into consumer behaviour underscores the critical role of online presence and digital marketing strategies for businesses. Ensuring a strong, positive online footprint through reviews, ratings, and detailed product information can significantly influence the purchasing decisions of these tech-savvy consumers.

Moreover, the preference for reading product specifications and descriptions, notably higher among consumers with advanced education, points towards a segment of the market that seeks detailed information and values transparency. For businesses, this underscores the importance of providing comprehensive and accessible product information, both online and in physical formats, to meet the demands of informed consumers who base their purchasing decisions on thorough research and comparison. Today, consumers are more informed and ready to do the leg work that traditionally has been the remit of the company’s sales person. Therefore, providing the right information (even at the right time) can improve the consumer’s perception of particular businesses as they make their final assessment.

The assessment and final purchase decision stage in the consumer’s journey reveals a landscape where traditional and digital evaluation methods converge. Businesses must adopt a hybrid approach, optimising both their physical retail experiences and digital marketing strategies to cater to the diverse preferences and needs of their target markets. Understanding these nuanced consumer behaviours and preferences is essential for crafting strategies that resonate with and effectively influence the final purchasing decisions of different consumer segments.

Frequent Purchase Groups

In this next stage of the study, the focus pivoted from examining large purchases to those occurring more frequently. Similar to the patterns observed with larger expenditures, it became evident that perceptions of ‘large’ or ‘expensive’ purchases are not uniform across demographics. This diversity was deliberately left unconstrained, even when exploring the most frequent purchases, leading to an organic collection of data. This approach uncovered rich insights into the various purchase frequencies characteristic

of different consumer groups. The findings of the study further highlighted the subjective elements influencing how often purchases are made and underscored the varied financial capabilities within distinct demographic profiles. This overview offers businesses a guiding framework on which markets are thriving and where consumer priorities lie, which can be instrumental in devising targeted strategies for product development, marketing, and customer service enhancements.

Starting with the category with the highest count, ‘Meat and Seafood’ category shows a high count of 211, reflecting a significant consumer spend in this area, unsurprising given its status as a staple in many diets. 27.6% of females indicated this category as the most frequent purchases compared to 24.5% of males. The highest purchase rates come from the 60+ age bracket (37.1%%) and those aged between 50 to 59 (30.6%), with this decreasing with the younger age brackets with a sudden drop to 5.1% in those aged 18 - 29, suggesting that older age groups either prioritise these food categories more, or are simply more frequently in charge of these purchases. The Gozo & Comino region indicated this category as the most frequently purchased (30.0%), followed by the Northern District (28.2%).

‘Frozen, Refrigerated, Canned, and Packaged Goods’ stands out in the frequently purchased category with 190 counts, underscoring the essential nature of these items in daily consumer life. This category’s prevalence suggests that groceries and food items remain the most frequently purchased items by consumers. Rather similar engagement was observed among females (24.4%), and males (22.5%). Those aged between 50 and 59 were most likely to indicate this category as one of their most frequent purchases (27.8%) followed by those aged 40 - 49 (26.4%) and those ages 30 - 39 (also 26.4%). From a regional perspective, the South Eastern District demonstrates high engagement with this category (26.9%), followed by the Northern Harbour District (25.7%).

Fresh produce was the third most popular category with a total of 102 counts, keeping the theme of food-related products being the most frequent purchases by the Maltese consumer. For the first time when it comes to food, however, males (14.6%) were more likely than females (11.1%) to indicate this

as a frequent purchase. When considering age, those between the ages of 30 - 39 indicated this category most frequently (15.7%) followed closely by those aged 5059 (14.6%) and those aged 40 - 49 (14.5%), again with the least mentions being those aged 18 to 29 (8.9%). Gozo and Comino was the most likely region to indicate this as a frequently purchased category (17.5%), followed by the Southern Harbour District at 16.9%. From a household perspective, those living in households of 4 people at 17.1%, followed by those that live alone (15.9%).

Served Foods & Beverages came in with a count of 93 (or 11.6% the total category mentions). Females (13.3%) were more likely to indicate this category than males (9.3%), and those aged 60+ (15.0%) and those aged 18 - 29 (14.6%) were the most likely in terms of age. Interestingly, those aged 30 to 39 were the least likely at only 5.7%. It is worth noting that the age bracket between 18 - 29 indicated this as their most frequent purchase in general (14.6%), tied with expenditure on Transport Services. From a regional perspective, the Western District was the most likely to select this category (14.7%), followed by those living in the Southern Harbour District (14.5%).

The category for Household and Non Food Items is worth observing given the difference between males (9.3%) and females (5.2%), though a low overall count for this category should also be noted.

The examination of frequent purchase groups provides invaluable insights into consumer behaviour, particularly in terms of the items that command a regular share of consumer purchase instances. This analysis therefore offers a comprehensive view of purchasing patterns, revealing not only the products that see frequent buying but also hinting at broader lifestyle and consumption trends within different demographic segments.

The pronounced expenditure in the ‘Meat and Seafood’ category, with a notable preference among older demographics, suggests a traditional approach to diet and meal preparation prevalent among these age groups. This preference indicates a potential market opportunity for businesses in the food sector to cater to the dietary habits and preferences of older consumers, particularly through targeted product offerings and marketing strategies that emphasise quality, health benefits, and convenience. The regional distinction, with higher purchase frequencies in Gozo & Comino and the Northern District, may reflect regional dietary preferences or the availability of fresh produce, signalling the importance of localised supply chains and marketing efforts.

The significant count in the Frozen, Refrigerated, Canned, and Packaged Goods category underscores the essential nature of convenience and longevity in consumer food purchases. The relatively uniform engagement across genders and the notable preference among middleaged demographics highlight an expected widespread reliance on these products. This trend suggests a robust market for convenient, long-lasting food items that cater to the busy lifestyles of consumers, particularly those balancing work and family obligations. Regional variations point to the necessity of ensuring accessibility and availability of these products across different areas, optimising distribution channels to meet consumer demand effectively.

The preference for fresh products, particularly among males and middle-aged consumers, aligns with a growing trend towards health and wellness, emphasising the importance of fresh, quality ingredients in meal preparation. The regional and household size data further suggest that accessibility to fresh produce and the capacity to store and utilise these products

may influence purchasing patterns. This insight offers businesses in the food sector a directive to enhance the visibility and appeal of fresh products, possibly through initiatives that promote the health benefits of fresh food consumption and ensure widespread availability.

The popularity of served foods and beverages, especially among the youngest and oldest demographics, seems to reflect a dichotomy in lifestyle preferences. Younger consumers might prioritise convenience and social experiences, while older consumers may seek leisure and ease. The disparity in preferences between age groups, with a significant drop among those aged 30 to 39, may indicate lifestyle transitions that influence dining habits, such as family commitments or health considerations. This category’s popularity suggests opportunities for the food service industry to tailor offerings and marketing strategies to appeal to the distinct preferences of these age groups, enhancing accessibility and appeal across diverse consumer segments.

These insights into frequent purchase groups illuminate key areas for strategic focus among businesses aiming to meet consumer needs effectively. Tailoring product offerings, marketing messages, and distribution strategies to align with the nuanced preferences of different demographic groups can enhance customer engagement and loyalty. Moreover, understanding the underlying lifestyle and consumption trends that drive these purchasing patterns can inform long-term product development and innovation strategies, ensuring businesses remain aligned with evolving consumer expectations.

Aggregated Market Category Data

To synthesise the research, we amalgamated data from both singular, large-scale purchase events and habitual, repetitive buying instances. This amalgamation aimed to distil a holistic picture of consumer behaviours, incorporating both episodic and regular transactions across diverse market categories. The purpose of this methodological integration was to garner a multidimensional understanding of consumer behavioural dynamics— encompassing both the impact of significant, infrequent outlays as well as the cumulative effect of smaller, routine purchases. By examining the consolidated counts, we can elucidate prevalent consumer trends and preferences, facilitating a comprehensive analysis of market engagement. This fusion of data points allows for a more nuanced appreciation of the consumer marketplace, one which yields a more enriched dataset conducive to identifying dominant market forces and consumer segments of interest.

It is essential to note that certain segments exhibited limited response counts. These categories have been deprioritized in the analytical narrative due to their lower prevalence in the dataset. This exclusion is a statistical decision to enhance the robustness of the findings, as underrepresented categories may not provide a reliable basis for drawing broad market conclusions. Consequently, when interpreting the provided tables, analytical focus should be maintained on those categories with sufficient data density to ensure statistical significance and avoid skewed insights.

Starting with the category with the highest count, ‘Meat and Seafood’ category shows a high count of 261, reflecting a significant consumer spend in this area, likely due to its status as a staple in many diets and the

tendency of consumers to invest in quality food products for health and culinary reasons. Females lead the purchases (17.3%) over males (14.8%). The highest purchase rates come from those aged 60+ (24.0%), followed by the 50 to 59 age bracket (19.8%) with those aged 18 - 29% coming in with a significantly lower rate of 3.8%, suggesting that older age groups might prioritise these food categories. The Northern Harbour District (17.8%) shows a high interest, and those living alone mentioned this category the most at 19.3%.

‘Frozen, Refrigerated, Canned, and Packaged Goods’ stands out with 255 counts, underscoring the essential nature of these items in daily consumer life. This category’s prevalence suggests that groceries and food items remain a top priority for consumers, pointing towards a steady and reliable market demand. Rather similar engagement was observed among females (16.2%), significantly more than males (15.4%). The 60+ age group leads with 19.0%, possibly due to the convenience factor of these goods, with those aged 50 - 59 following closely at 18.1%. The South Eastern District demonstrates high engagement (20.1%), indicating a reliance on or preference for these products. Interestingly, households with five or more people tended to mention this category more (18.2%), possibly indicating a preference for convenience.

Served Foods & Beverages attained 155 counts. Higher interest from females (11.5%) than males (7.3%), indicating possible dining or convenience preference. The 60+ demographic (13.5%) leads, which could point towards social dining or convenience in meal preparation. The Western District has the highest rates (12.3%), possibly pushed up through a prevalence for online orders.

‘Vacation, Travel & Wellness’, with 149 counts, ties with ‘Household and Non-Food Items’, which also shows 149 counts. This equivalence highlights two very different yet important aspects of consumer spending: the desire for experiences and wellness, and the necessity for home-related products. More engagement was observed from females (10.0%) than males (8.4%) in terms of ‘Vacation, Travel & Wellness’. The 30 to 39 age group shows considerable interest (13.2%), which might indicate a demographic with disposable income for travel or wellness. Gozo & Comino shows the highest count (11.3%), followed by the Northern District (10.9%), perhaps reflecting regional economic status or preferences for wellness and travel. Female engagement (8.1%) is slightly less than males (10.6%) for Household & Non Food Items. The 40 to 49 (11.3%) and the 50 to 59 (11.1%) age groups shows considerable interest, possibly due to home ownership and maintenance needs. The South Eastern District stands out with a high count (11.6%) in the Household & Non Food Items category.

‘Consumer Electronics’ follows next with 119 counts, indicating a fairly robust interest in technology and gadgets. This could be driven by the continuous innovation in this sector and the increasing reliance on electronic devices in both personal and professional spheres. More popular among

males (8.9%) than females (6.1%). The highest interest is among the younger age groups, with 18 to 29-year-olds leading at 13.3%. In fact, this category was the most popular category for this age group across all amalgamated categories within this study. Southern Harbour District has the highest count, suggesting a regional preference or greater availability.

Interestingly, ‘Fresh Produce’ has a count of 114, which is relatively high and suggests a focus on fresh food, possibly related to health consciousness or a preference for cooking with fresh ingredients. Slightly more popular among females (6.3%) compared to males (8.0%). The 18 to 29 age group (5.4%) is less engaged compared to consumer electronics and fashion. Southern Harbour District residents (9.0%) show significant interest, potentially due to accessibility to fresh markets or healthconscious communities.

Large Home Appliances’ have a count of 110, indicating significant investments in home equipment. This suggests a market with less frequent but more substantial purchasing decisions, possibly linked to long-term household setup and maintenance.

Categories like ‘Fashion & Apparel’ and ‘Household and Non-Food Items’ with counts of 81 and 149 respectively, reflect a solid consumer interest in personal style and home essentials, suggesting these are active areas for consumer engagement.

Fashion & Apparel is more popular among females (6.1%) than males (3.7%). Again, the younger demographic (18 to 29 years) shows the highest interest (11.7%), and the South Eastern District has a particularly high engagement (8.6%).

Large Home Appliances attained slightly higher responses from females (7.4%) than males (6.2%). The 50 to 59 and the 60+ age groups both have a higher interest, tying at 8.3%, which seems to align with life stage needs for durable household goods. Gozo and Comino also indicate a higher rate of mention at 12.5% for this category.

The lower counts in categories such as ‘Banking, Insurance & Investment Services’ (31), ‘Internet, TV & Telephone Service’ (20), and ‘OTC Health & Personal Care and Beauty’ (26) might indicate that while these are important services, the frequency of transactions and/or the value per transaction within the sample size may be lower compared to the more essential goods and services.

The prominence of the ‘Meat and Seafood’ and ‘Frozen, Refrigerated, Canned, and Packaged Goods’ categories underscores a fundamental consumer emphasis on food as a primary spending category. This reflects not just a basic need but potentially a preference for quality and convenience, especially among older demographics who prioritise these categories significantly more than younger consumers. The geographical distinctions, notably high interest in the Northern Harbour and South Eastern Districts, hint at regional consumption patterns that could guide localised inventory and marketing strategies by keeping in mind that these categories tend to make up a proportionally larger total of the purchases made within these categories.

The contrast between high engagement in ‘Served Foods & Beverages’ and ‘Vacation, Travel & Wellness’ indicates a bifurcation in consumer spending towards both convenience and experiential pursuits. The preference for served foods, particularly among females and the 60+ demographic, aligns with a broader trend towards convenience and social dining experiences. Meanwhile, the equal emphasis on ‘Vacation, Travel & Wellness’ suggests a significant consumer segment prioritizing experiences and self-care, especially among the 30 to 39 age group. This age group’s

interest potentially reflects a lifestyle phase where disposable income is available for travel and wellness, presenting opportunities for businesses in these sectors to target marketing efforts and product offerings.

Consumer electronics and fresh produce categories exhibit interesting demographic trends, with a stronger preference among younger consumers for technology, suggesting a tech-savvy generation keen on the latest innovations. Conversely, the fresh produce category, though popular across the board, is substantially lower in the youngest demographic, potentially indicating that whilst these age groups are less involved in the buying process of the latter, they tend to take charge of the purchasing decisions when it comes to electronics.

The considerable counts in ‘Large Home Appliances’ and ‘Household and NonFood Items’ categories reveal a consumer segment focused on home investment and maintenance, showing a propensity for significant, infrequent purchases. The engagement in these categories is more pronounced among older age groups and females, suggesting a demographic in a life stage of establishing or upgrading their living spaces. This insight presents a strategic opportunity for businesses in these sectors to focus on quality, durability, and value as key selling points with a target market that is a demographic fit with the observations above.

The ‘Fashion & Apparel’ category, with notable popularity among females and the younger demographic, highlights a consumer interest in personal style and expression. The higher engagement rate in the South Eastern District may reflect regional fashion trends or the availability of retail options, suggesting potential for targeted fashion marketing and retail expansion in this area.

This aggregated data analysis elucidates key consumer spending behaviours and preferences, offering strategic insights for businesses across sectors. The emphasis on food, both for home cooking and convenience dining, alongside significant investments in home and lifestyle, presents clear directives for market positioning, product development, and marketing strategies. Understanding these dynamics enables businesses to tailor their offerings more closely to consumer needs and preferences, enhancing engagement and fostering loyalty in a competitive marketplace.

Outlets Attracting Higher Consumer Purchases

The analysis encompasses data from 460 distinct outlets, revealing a significant degree of market fragmentation across various categories. This preliminary examination has begun to spotlight potential leading brands and outlets within Malta. A key insight from this data is the identification of outlets that garner the most visits, indicative of both high-value and frequent transactions. As we progress through this comprehensive market research initiative, we anticipate developing a more nuanced understanding of consumer behaviours within each market segment.

This stage of the research highlights the outlets that command the highest footfall, which in turn suggests trends in consumer preferences for both premium and regularly purchased items. It is important to note, however, that this analysis currently excludes purchases made by tourists and may present a skewed perspective in terms of the preferences of Maltese nationals compared to those of foreign residents (as discussed in the Research Limitations, Precautions & Mitigation Section). Despite these considerations, the findings already begin to sketch out the vast potential of this project to delineate trends by Shop, Outlet, Brand, and Location.

In progressing with this research, we aim to refine our understanding of consumer behaviour across different market categories. This endeavour not only seeks to chart the most frequented outlets but

also to parse the intricacies of consumer loyalty and choice within a fragmented market landscape. The insights garnered thus far lay the groundwork for a deeper exploration into the dynamics that drive consumer engagement with these outlets. As we move forward, adjusting for the noted biases and limitations, the full scope of this market research promises to offer valuable perspectives on the prevailing and emerging trends that shape consumer interactions with brands and outlets in Malta.

The analysis, focusing on the top 30 suppliers based on visit frequency, reveals a pronounced dominance of supermarket outlets. This finding underscores the central role that supermarkets play in the daily lives and purchasing habits of consumers, serving as primary destinations for a wide range of needs from basic groceries to specialty items. The prominence of supermarkets in the frequency data highlights their significance not only as retail spaces but also as integral components of consumer routines and preferences.

Upon the completion of the data collection, encompassing 4,750 purchasing events, a comprehensive analysis will be undertaken. This analysis aims to streamline the 19 identified market segments into distinct, well-defined factors. Leveraging factor analysis, this process will unravel the complex patterns embedded within the dataset, categorising outlets, brands, and market categories into unified groups that

Outlets/Brands Attracting Higher Purchases Within Sample - Frequency & % of Purchase Events

share similar attributes. A key expectation is the emergence of supermarkets as a prominent cluster, potentially encompassing specific consumer behaviours or market dynamics. It serves to dissect the observed variability among correlated variables, distilling them into a more manageable set of latent variables, or factors. This methodology will be used to uncover the fundamental relationships underlying the dataset, thereby transforming a multitude of variables into a concise set of influential factors that dictate data patterns. In the supermarket sector, convenience and accessibility, the broad spectrum of product offerings, brand trust and loyalty and/ or cultural and social influences could be elements that describe such factors.

The strategic employment of factor analysis will enable the extraction and explanation of similar dimensions, offering a deeper insight into the distinctive consumer segments and their market behaviours. The outcome of this analysis promises to streamline the inherent complexity of the 19 market segments, providing a solid framework for data interpretation. Through this analytical prism, the resultant clusters will unveil crucial insights into the market’s structural dynamics and interpretation of results by such factors which can be described as latent variables that are inferred from the observed correlations among a set of measured variables. These factors represent underlying dimensions or constructs that explain the patterns of correlations in the data4

Advertisements or Promotions

This question was intended to offer a nuanced view of advertising effectiveness across different segments and was asked to respondents based on their large purchases. A significant portion of respondents (30.6%) recalled seeing advertisements or promotions before making their purchase. Conversely, a substantial portion of respondents do not recall seeing any advertisements or promotions before making their purchase, indicating no recollection. This suggests that a significant number of purchases are made without the influence of direct advertising, or that the advertising efforts did not make a lasting impression on these consumers. The presence of a substantial group not recalling any advertisements before their purchase raises questions about the role and impact of advertising on consumer

behaviour. It suggests that factors other than direct advertising, such as product quality, or word of mouth (as seen in earlier sections), might be more influential in these consumers’ purchase decisions. With this said, it is important to keep the caveat in mind that the response relies heavily on recall. Moreover, it is outside of the scope of the exercise to assess the veracity of those who claim that they did see ads prior to purchase.

It is not a revelation that advertisers need to consider tailoring their strategies to better capture the attention of their target demographics, especially considering the differences in recall rates between genders and age groups. Both males and females indicated they remembered seeing ads, reflecting a notable engagement with marketing efforts across both genders although the data shows a marginal difference in recall rates between males and females.

• Males reported a 29.1% recall rate of seeing advertisements, while females had a slightly higher recall rate at 31.9%. This suggests that advertising may be slightly more memorable or targeted towards females.

• The 18 to 29 age group had the highest recall of advertisements at 38.6%, which could indicate that younger consumers are more influenced by ads or that they are the primary target for many advertising campaigns. Recall steadily decreases with age, with the lowest recall in the 60+ age group at 27.9%, possibly reflecting different media consumption habits or a lower susceptibility to advertising.

• The Southern Harbour District had the highest recall rate at 38.0%. Recall rates were generally lower in the Northern Harbour District and Gozo & Comino District at 26.6% and 27.5%, respectively, suggesting varying effectiveness of advertising by region. Smaller one-person households reported the lowest ad recall at 20.5%, while households of four members had the highest recall at 37.8%.

• Larger households may be exposed to more varied advertisements due to the diverse needs and interests of the members, with households of 4 having a recall rate of 37.8%, and those with 5+ having one of 36.5%. Singles had a higher ad recall rate (32.0%) compared to married/partnered individuals (31.1%), separated/divorced (29.6%), and widowed (15.6%). This could suggest that single individuals are a significant target demographic for advertisers or that they are more receptive to advertising.

• Individuals with MFQ level 7&8 qualifications showed the highest ad

recall at 46.0%, potentially indicating more targeted advertising towards higher-educated demographics or a greater engagement with media where ads are present. The recall generally decreases with the lowering level of education, with MFQ 5 level reporting a 23.8% recall rate.

• Science, Engineering, and Other Specialized Professionals, and Associate Professional Occupations showed relatively high recall rates of 34.9% and 38.4%, respectively. These professions might engage more with media platforms where advertisements are prevalent or be targeted due to their specific professional interests. Recall rates were notably lower for elementary occupations (20.0%) and retirees/ pensioners (24.6%), possibly due to less exposure to or interest in the advertised products or mediums.

Given the mixed recall rates, there is room for marketers to explore more innovative, engaging, and memorable advertising strategies that feed into the brand voice more deeply to create a long lasting impression. Could interactive ads, influencer collaborations, or personalised marketing efforts be more likely to resonate with consumers? In either case, this analysis underscores the importance of understanding consumer behaviour and the varied impact of advertising across different segments.

Tailoring advertising strategies to the preferences and behaviours of specific demographic groups could enhance the effectiveness of marketing efforts and ultimately influence purchasing decisions more strongly.

Recall of Ads & Channel Effectiveness

The data underscores the varied effectiveness of different advertising channels, with traditional media like television still playing a crucial role in consumer recall, while digital platforms, particularly social media, emerge as increasingly important. There are clear differences in advertisement recall across demographics, indicating that gender and age significantly influence the effectiveness of different advertising channels. Television commercials remain a significant advertising medium, especially for older age groups, social media advertisements are more effectively recalled by younger audiences and females. This suggests that for broader reach, a cross-platform approach combining traditional media with digital platforms could be effective. Meanwhile, sponsored content has lower overall recall but is noticed more by specific demographic niches, like larger households, indicating opportunities for targeted online marketing strategies within these segments.

Social Media Advertisements (e.g. Facebook, Instagram) attracted higher recall, with Females (22.2%) are more likely to recall ads on social media than males (12.6%), possibly due to higher engagement with these platforms among women. The 18 to 29 age group has the highest recall for social media ads (27.8%), reflecting the younger generation’s consumption of digital media. Consumers in the Southern Harbour District (20.5%) and Gozo & Comino District (20.0%) recall social media ads well, perhaps indicating active social media use or targeted campaigns in these regions. Individuals with MFQ level 7&8 education show a significant recall of social media ads (31.5%), suggesting that higher education correlates with higher engagement in social media environments.

A slightly higher percentage of females (7.5%) recall seeing TV ads compared to males (6.3%). Consumers aged 60+ have the highest recall rate for TV commercials (11.3%), which aligns with traditional media consumption patterns favouring older demographics. The Northern District has the highest percentage of consumers recalling TV ads (12.0%), suggesting television’s effectiveness in this region. Single-person households have a higher recall rate (9.1%) for television ads, which could reflect more individualised viewing habits.

Again, females (3.6%) have a slightly higher recall rate than males (2.7%) for sponsored content on websites or blogs. Those aged 30 to 39 show the highest recall rate (7.1%) for sponsored content, possibly due to this group’s online literacy and browsing behaviour. Households with five or more members (9.4%) have the highest recall, which might be due to diverse interests and online activities leading to more exposure to sponsored content.

The notable recall of ads seen on digital platforms, including social media and online banners reflects the ongoing shift in consumer media consumption habits. Advertisers must continue to adapt by allocating resources towards these channels, leveraging their targeting capabilities to reach specific consumer segments.The differences in recall rates between males and females, particularly in digital channels, suggest that personalization and relevance are key to enhancing ad recall. Advertisers should focus on creating personalised and relevant content that resonates with their target audience to maximise the impact of their advertising efforts.

Recall of Ads & Channel Effectiveness - Frequency & % of Response within Group

This analysis highlights the importance of a multi-channel advertising strategy that considers the changing media landscape and demographic preferences. Advertisers must remain agile, continuously adapting their approaches to meet consumers where they are most engaged and receptive to advertising messages.

The analysis of advertising channel effectiveness, demographic preferences, and changes in media consumption habits yields several insights for businesses aiming to optimise their advertising strategies. The main takeaway and recommendation for businesses based on the varied effectiveness of different advertising

channels is that businesses should adopt a multi-channel approach catered specifically to particular market segments. This strategy allows for broader reach and engagement with diverse demographic groups, leveraging the strengths of each channel to maximise overall impact.

Inferences on a Trending Demographic - Gen Z5

As seen in the international trends, information overload is intricately tied to the overcrowded marketing landscape, especially in the context of targeting Generation Z. As brands and marketers vie for the attention of this demographic amidst a saturated market, the sheer volume and velocity of information presented to consumers can lead to information overload. In the realm of marketing to Gen Z, information overload manifests in several key ways and has distinct implications for both consumers and brands.

In the context of Malta, Generation Z, totals over 100,000 persons. This significant segment represents a notable portion of Malta’s population, emphasising the potential impact and importance of Gen Z in the local market. With the population of Malta and Gozo being around 542,051 at the end of 2022, Gen Z constitutes a substantial demographic, underlining their potential as consumers, influencers, and future leaders within the Maltese context. Their preferences, consumption habits, and values are likely to shape market trends, cultural shifts, and economic policies in Malta in the coming years. Globally, Generation Z is estimated to comprise about 30% of the world’s population.

This demographic is distinctive for several reasons: they are digital natives, highly socially and environmentally conscious, and possess significant purchasing power and influence over household spending. However, as more companies recognize the value of targeting Gen Z, there is a growing concern about the marketing space becoming too crowded.

5 Generational Segmentation:

Nevertheless, while this trend is also seen throughout the data, it is a clear reflection of international trends that show that today there are manifestations of information overload through a constant digital bombardment. Gen Z spends a significant amount of time online across various platforms. The constant exposure to ads, branded content, social media posts, and emails can result in an overwhelming amount of information to process. Moreover, with an abundance of products, services, and brands vying for attention, Gen Z consumers may experience choice paralysis, where they find it difficult to make purchase decisions due to the overwhelming number of options. More so, the overflow of marketing messages contributes to shorter attention spans among consumers. Faced with a deluge of information, Gen Z individuals may find it challenging to focus on any single message, making it harder for brands to make a lasting impact. Finally, as Gen Z is bombarded with contradictory messages and aggressive marketing tactics, they may become cynical about the authenticity and reliability of the information they receive creating a thirst for authenticity and truth.

While Malta’s Generation Z shows an inclination towards sustainability, bridging the gap between their aspirations and actions is essential. Through education, improved accessibility to sustainable options, and fostering a sense of community and efficacy, it’s possible to transform interest into action, enabling Gen Z to play a pivotal role in driving sustainability forward in Malta and beyond.

Generation Z (Gen Z) - Birth Years: Mid-1990s to early 2010s, Age Range (as of 2024): Approximately 10 to 29 years old

Millennials (Gen Y)- Birth Years: Early 1980s to mid-1990s, Age Range (as of 2024): Approximately 29 to 44 years old

Generation X (Gen X) - Birth Years: Mid-1960s to early 1980s, Age Range (as of 2024): Approximately 44 to 59 years old

Baby Boomers - Birth Years: Mid-1940s to mid-1960s, Age Range (as of 2024): Approximately 59 to 79 years old

Silent Generation - Birth Years: Mid-1920s to mid-1940s, Age Range (as of 2024): 79 years old and older

Post Purchase Behaviour & Need of Customer Support

For larger purchases, we also asked respondents if they ever needed customer support/service relating to this product or service. A portion (13%) of the respondents have needed customer support or service related to their product or service. This suggests that a notable number of consumers encounter issues or have inquiries post-purchase that require direct engagement with customer support teams. Both male (14.0%) and female (12.2%) consumers report needing customer support at comparable rates, with no significant difference in the likelihood of seeking support. The age group 40 to 49 was the most likely group to have needed

customer support. This could suggest that consumers in this age bracket are either more likely to experience issues requiring support or are more inclined to reach out for assistance when needed. This could be indicative of high product/service quality choice (as indicated in the results) or other consumers’ ability or the necessity to resolve minor issues independently. Scope for further exploration of these factors may come in the form of a cross tabulation between demographics and different markets to gauge the propensity of consumers to request assistance based on the purchase category.

A significant majority of respondents have not needed to contact customer support/ service, indicating no need for such engagement. This could reflect positively on the overall satisfaction with the products or services, suggesting that most consumers do not encounter issues necessitating support intervention.

This section also provides data on consumer satisfaction with the overall support experience related to the product or service they purchased were respondents were asked to rate their satisfaction levels based on a 5-point scale. This information is crucial for understanding how effectively customer support teams are meeting consumer needs and expectations. Satisfaction is quantified through mean scores, and the data is segmented by demographic attributes, offering insights into how different groups perceive their support experiences.

Males reported a mean satisfaction score of 4.3, while females reported a slightly higher mean score of 4.3. This indicates a generally high level of satisfaction among both genders, with females being marginally more satisfied. The age group 18 to 29 reported the highest satisfaction score of 4.6, suggesting that younger consumers are notably more satisfied with their support experiences compared to other age groups. The age group 30 to 39 follows closely with a mean score of 4.4.

The satisfaction scores range from a minimum of 1 to a maximum of 5, indicating a broad spectrum of consumer experiences with customer support. However, the reported minimums and maximums vary across different segments, reflecting the diverse nature of consumer expectations and experiences.

The standard deviation values, such as 0.82 for males and 0.73 for females, indicate the variability in satisfaction scores. Lower

standard deviation values in certain groups, like the age group 18 to 29 with a standard deviation of 0.50, suggest more consistency in satisfaction levels within these groups.

The generally high mean satisfaction scores across all demographics indicate that customer support teams are effectively addressing consumer needs, leading to positive support experiences. This is a critical factor in maintaining customer loyalty and promoting positive wordof-mouth. Thigher satisfaction scores among younger consumers could reflect their preferences for digital-first support channels, which may be more effectively implemented by companies.

This suggests that aligning support channels with consumer preferences can significantly impact satisfaction levels. While the satisfaction scores are generally high, the presence of scores across the entire 1 to 5 range indicates room for improvement. Feedback from lower-scoring respondents could provide insights into specific areas where support experiences could be enhanced. The variability in satisfaction scores, as indicated by standard deviation, highlights the importance of providing consistently high-quality support experiences to all consumers. Efforts to minimise variability in support experiences could further improve overall satisfaction scores.

This analysis underscores the importance of customer support as a critical component of the post-purchase consumer experience. Continuous monitoring and improvement of support services, informed by detailed satisfaction data, are essential for maintaining high levels of consumer satisfaction and loyalty.

Changing Purchasing Behaviours

This section discusses the portion of the study that pertains to consumers’ purchasing habits when it comes to frequent purchases, and whether they have changed in the last year with regards to specific products or services. While budgetconscious behaviour is fairly consistent across most demographics, there are marked differences in how often consumers make purchases and their willingness to try new products.

28.7% of the respondents reported a change in their purchasing habits over the last year, with 91 males (25.0%) and 140 females (31.7%) affirming this change on some product or service. The overall response, combining both males and females, shows that 231 individuals reported a change in their purchasing habits, while 575 indicated no change. This overall pattern reinforces the observation that while changes in purchasing habits are evident among certain demographic groups, the majority of consumers maintain their existing purchasing behaviours.

Therefore, despite these changes, a significant majority of respondents reported no change in their purchasing habits, with 273 males (75.0%) and 302 females (68.33%) indicating stability in their buying behaviour, giving credence to the assumption that most frequent purchases fall within specific purchase behaviour until some external factor influences a change. This means that while some consumers are adjusting their habits, a larger portion continues to purchase products or services in the same manner as before, creating an opportunity for businesses to focus on customer acquisition and retention strategies and enhancing loyalty programs to capitalise on the preference for stability among the majority of consumers.

Changes in Purchasing Behaviour - Frequency & % of Total Response

The data also indicates a noticeable shift in consumer behaviour, with a slightly higher propensity among females to change their purchasing habits. Within the age group 18 to 29, 32.9% reported a change in their purchasing habits, which is close proportionally to other age groups such as those between 30 - 39 (32.1%) and those aged 50 - 59 (33.3%), suggesting a fairly equal propensity throughout. However, when considering the oldest group (60+), this propensity dropped to 20.0%, indicating that older consumers have a lower tendency to alter their purchasing habits.

This section also provides a consolidated overview of how consumers’ purchasing habits have changed in the last year regarding specific products or services, categorised into various behavioural shifts. For those respondents that said that their habits changed, we asked them how these changed. Of those whose habits changed, the most significant change

reported is an increased price sensitivity or budget-conscious behaviour, constituting approximately 40.3%. Males (45.1%) said that they are more price sensitive more frequently than females (37.1%). When considering age, those between 4049 were most likely to indicate an increase in price sensitivity (57.9%), followed by those aged 50 - 59 (50.0%) and those aged 60+ (43.8%). Interestingly, those aged 18 - 29 were the least likely to cite this as the main way in which their habits changed (19.2%).

From a regional perspective, those in the Southern Harbour District were most likely to cite price sensitivity as the main way in which their habits changed (48.9%), followed by those living in Gozo and Comino (45.5%) and those in the Western District (44%).

The second most cited way in which purchasing behaviour changed was a decrease in the frequency of purchase, with a total of 21.6% of those having changed their habit indicating this as the main

change. Males (24.2%) indicated this more frequently than females (20.0%), and this change was the most prevalent one given by those aged 18 - 29 (36.5%), far above the second age group that cited this reason which was those aged 60+ (25%). Similarly, this was the most cited change for those in the South Eastern District (35.5%), followed by the Northern Harbour District (25.8%).

An increase in purchase frequency was another way in which consumer habits changed (10.8%), one which females (13.9%) were most likely to give when compared to males (6.6%). Those aged 18 - 29 were also the most likely to cite this change (17.3%), as were those in the Northern Region (17.6%).

Finally, 9.5% of respondents whose habits changed said that they started experimenting with other brands, with females (10.0%) being slightly more likely to do so than males (8.8%). Those aged between 30 - 39 were also more likely to do so (17.8%) as were those who live alone (19.2%).

The data presents a dual landscape where a significant majority of consumers exhibit stability in their purchasing habits, while a noticeable portion has adapted their behaviours. This stability, observed in 75% of males and 68% of females, underscores a predominant consumer preference for familiar purchasing patterns, highlighting the importance of reliability and consistency in product and service offerings. However, the 28.7% of respondents reporting changes in their purchasing habits reflect a segment of the market that is responsive to external factors, suggesting that businesses need to remain agile and responsive to evolving consumer needs.

A slightly higher propensity among females to change their purchasing habits, coupled with a fairly uniform distribution of adaptability across the age groups of 18-59, indicates that the willingness to adjust purchasing behaviors spans across demographics. However, the reduced tendency among the oldest consumers (60+) to alter their habits underscores the value of tradition and routine in this demographic’s purchasing decisions. This demographic disparity again suggests that businesses may need to adopt different strategies to engage with various age groups, balancing the introduction of new products and services with the maintenance of core offerings that appeal to consumers’ existing preferences.

The notable shift towards increased price sensitivity, particularly among males and certain age groups (40-49 and 50-59), highlights the impact of economic factors on purchasing decisions. This heightened price awareness suggests that consumers are not only looking for value but are also willing to adjust their purchasing patterns to manage their budgets more effectively. For businesses, this trend underscores the importance of competitive pricing, value for money, and clear communication of product benefits to cater to budgetconscious consumers who perhaps are feeling the pinch of a higher than usual inflation rate.

The decrease in purchase frequency, especially pronounced among the 1829 age group and in certain regions, points towards a selective approach to spending. This trend offers businesses an opportunity to focus on customer retention and increasing the perceived value of their products and services, encouraging continued engagement even as consumers reduce their overall purchase frequency. Conversely, the increase in purchase frequency among younger consumers and females, as well as the openness to experimenting with other brands, signals a segment of the market that is exploratory and receptive to new experiences. This presents an opportunity for businesses to introduce innovative products and services, engage consumers with trial offers, and build brand awareness among potential new customers.

The data therefore suggests a balanced approach that honours the value of stability and tradition for a majority of consumers while also accommodating the evolving preferences of a significant minority. Businesses can leverage these insights to refine their product development, marketing, and customer engagement strategies, ensuring they meet the diverse needs of their consumer base. Again, tailoring offerings to address increased price sensitivity, facilitating exploration of new products, and reinforcing the value proposition of existing products are key strategies to engage both stable and adaptive consumer segments. In doing so, businesses can enhance customer loyalty, attract new segments, and adapt to the changing dynamics of consumer purchasing behaviours.

Changes in Consumer Purchasing Habits

After asking how habits have changed, we asked consumers what their perceived source or cause of the change was. This section provides an overview of the reasons behind changes in consumers’ purchasing habits, categorised by various factors. The most significant factor influencing changes in purchasing habits is changes in personal preferences or lifestyle, making up 39.4% of the total responses, followed by changes in the financial situation or budget making up 26.4%. This highlights a dual influence between the changing situation of consumers and the impact of economic factors on consumer behaviour, suggesting that preferences and financial considerations together make up the bulk of the reasons for changes in purchasing decisions today. Price changes or discounts also play a significant role, with 22.5% of the total, suggesting that promotions and pricing strategies are effective in influencing consumer purchasing behaviour. Between then, these categories make up almost 90% of total responses for the reasons for the change.

The data suggests that while financial situations or budget changes have a notable impact across various demographics, personal preferences and lifestyle shifts are particularly influential among females and middle-aged consumers. Price sensitivity and responsiveness to discounts are more pronounced among females and older age groups

Males are substantially more affected by financial changes (37.4%) than females (19.3%), which could indicate men’s purchasing decisions are more sensitive to budgetary shifts. On the other hand, females (41.4%) were more likely to indicate a lifestyle change as the main driver when compared to males (36.3%), and interestingly, were substantially more likely to respond with Price Changes or Discounts (27.9%) than males (14.3%).

Changes in personal preferences were most important for those aged 60+, potentially indicating an adaptation to a retired or elderly lifestyle. In fact, 50% of those who

said that they are retired provided this as the main reason for the change in their purchasing behaviour. On the other hand, those aged 30 - 39 cited this reason 42.2% of the time, perhaps indicating a lifestyle shift that pertains to starting a family, purchasing a home, or focusing on ones career. From a regional perspective, the South Eastern region gave this reasons the most frequently (64.5%), followed by the Westerb District (60.0%), both of which are far above the lowest frequency region which was the Northern Harbour District at 24.2%.

When considering the reasons of Changes in Financial Situation or Budget, we found that those aged 30 - 39 (37.8%) and those aged 40 - 49 (31.6%) cited this reason the most, again potentially indicated lifestyle changes that tend to come with this phase of life in terms of child rearing and home purchases. In fact, when considered by age, those in 3 person households were the most likely to cite this reason at 32.5%, which tied as the most important reason for these households with lifestyle changes (32.5%). From a regional perspective, Gozo & Comino cited Changes in the financial situation or budget the most (45.5%) followed by those in the Northern Harbour District (39.4%).

Price changes or discounts was most prevalent in those aged 50 - 59 (33.3%), followed by those aged 60+ (29.2%) indicating that older generations are more sensitive to price changes and/or more receptive to discounts. The Southern Harbour District was far above the others in selecting this reason at 34.0%, compared to the second district that selected it most, which was the Northern Harbour District at 24.2%. Finally, a significant number of respondents who selected this option reside in households with five or more people (37.9%), followed by those residing in two person households (27.3%).

Cause of Changing Purchasing Habits - Frequency & % of Total Response

Availabilty of new products or brands

The above analysis uncovers a complex interplay between personal preferences, financial circumstances, and responsiveness to market incentives like price changes or discounts, each playing a distinct role in influencing consumer decisions. The prominence of changes in personal preferences or lifestyle as the leading cause of shifts in purchasing habits underscores the fluid nature of consumer desires and lifestyles. Accounting for 39.4% of the reasons cited, this factor reflects a significant alignment of purchasing behaviour with evolving personal identities, values, and life stages. Notably, this reason is most influential among the 60+ age group and those undergoing major life transitions such as retirement, starting a family, or career advancements. The regional variance, with the South Eastern and Western Districts reporting the highest frequency, suggests that certain locales

may experience more pronounced lifestyle shifts, potentially due to socio-economic factors or demographic trends.

Changes in financial situation or budget, cited by 26.4% of respondents, highlight the economic underpinnings of consumer purchasing behaviour. This factor is particularly salient among individuals in the 30-49 age range, reflecting significant life phases such as child-rearing and home ownership that inherently affect financial priorities and constraints. The fact that 3-person households frequently cite this reason alongside lifestyle changes suggests a link between family dynamics and financial management. The regional insights, with Gozo & Comino and the Northern Harbour District leading, could indicate regional economic disparities or variations in cost of living impacting consumer financial situations.

The influence of price changes or discounts on purchasing habits, noted by 22.5% of respondents, emphasises the importance of pricing strategies in consumer decisionmaking. Older age groups (50-59 and 60+) and households with five or more people show heightened sensitivity to price adjustments, suggesting that for these demographics, financial prudence and value maximisation are paramount. The higher receptiveness to discounts in the Southern Harbour District points to regional variations in price sensitivity, possibly driven by local economic factors or consumer demographics.

This analysis offers several key takeaways for businesses navigating the changing consumer purchasing landscape:

• Personalization and Flexibility: Once again, tailoring products and services to meet the evolving lifestyles and preferences of diverse demographic groups is crucial. Businesses should leverage consumer data to anticipate and respond to shifts in lifestyle, offering solutions that resonate with the personal values and needs of their target segments.

• Financial Sensitivity: Understanding the financial pressures faced by consumers, especially those in significant life phases, is vital. Companies can differentiate themselves by offering flexible pricing, financing options, or value propositions that address consumers’ financial concerns, enhancing brand loyalty among budget-conscious shoppers.

• Pricing and Promotions: Developing dynamic pricing strategies and targeted promotional offers can effectively capture the attention of price-sensitive consumers. Given the particular responsiveness of older consumers and larger households to discounts, businesses should consider strategic

discounting as a tool for both customer acquisition and retention.

• Regional Tailoring: The variance in reasons for purchasing habit changes across regions underscores the need for localised marketing and product strategies. Businesses should adapt their offerings and communications to reflect regional preferences, economic conditions, and lifestyle trends, ensuring relevance and appeal to local consumer bases.

Purchase Habit Formation (Origin)

For respondents who said that their habits had not changed, we asked them to recall what had initiated their current purchasing habit, with reasons ranging from competitive pricing and superior product quality to exceptional customer service and innovative technology.

The leading factor is ‘Convenient location or accessibility,’ with 43.2% indicating that physical proximity or ease of access plays the most significant role in initiating a purchase. This is followed by ‘Competitive pricing’ and ‘Superior product quality,’ with 35.4% and 28.8% respectively, suggesting that value for money and the quality of the product are also key determinants.

Both males and females find convenience in location or accessibility important at nearly equal rates, with 28.4% of males and 27.9% of females citing it as a reason for their purchasing decisions. The factor of ‘Convenient location or accessibility’ is more influential for older age groups, particularly those over 60, where it affects 31.0% of consumers. It progressively impacts younger age groups less, with the lowest in the 18 to 29 range at 23.8%. The Gozo & Comino District shows the highest percentage of consumers (33.9%) who consider ‘Convenient location or accessibility’ important, potentially due to fewer physical shopping options. Other districts follow closely, with the Western District coming in at 31.3%, and the Northern District at 29.5%..

Single-person households report ‘Convenient location or accessibility’ as a significant factor at 46.6%, suggesting that individuals living alone may prioritise convenience more than larger households. ‘Convenient location or accessibility’ is especially important for widowed consumers, influencing 51.2% of their purchasing decisions. This could reflect

mobility or transportation concerns that make nearby options more appealing. The influence of convenience declines slightly with higher education, with those holding MFQ 6 qualifications reporting the highest impact at 36.0%. This might reflect the busy lifestyles of more educated consumers who value the time saved by convenient locations.

The percentage of males (22.3%) and females (23.8%) who consider competitive pricing important when making a purchase is relatively similar, with females slightly more inclined to factor this into their decision-making. Competitive pricing seems to have a fairly consistent influence across all age groups, with the 30 to 39 age group being the most influenced (27.6%). It suggests that this age range, potentially in the midst of career building and family raising, is more sensitive to price. The Northern Harbour District values competitive pricing the most (24.9%), followed closely by the Northern District at 24.4%, which could reflect a more pricecompetitive environment or a higher cost of living in that area. Conversely, the South Eastern District shows the least influence by competitive pricing (18.8%).

Interestingly, single-person households are least influenced by competitive pricing (15.3%), possibly indicating a general greater emphasis on other factors like quality or convenience for this demographic. Single individuals (20.8%) are less influenced by competitive pricing compared to married or partnered individuals (25.4%). This might reflect differing financial responsibilities, with those supporting a family more sensitive to price points. All education levels show concern for competitive pricing, with the least influence seen in those with the lowest (MFQ 2, 25.0%) and the highest education levels (MFQ 7&8, 21.8%).

Males (20.2%) are slightly more influenced by superior product quality than females (17.3%), which could suggest that men prioritise product quality slightly more, or it could reflect their purchasing habits in specific product categories. The 50 to 59 age group places a slightly higher value on quality (23.8%), with those aged 18 to 29 coming in second (21.0%).

The Gozo & Comino District places the highest importance on product quality (28.6%). Other districts, like the Southern Harbour District, show a lower percentage (17.1%), which may indicate a wider

availability of choices or different purchasing priorities. The importance of product quality appears to be less for households with one person (16.1%) and most significant for households with four or more members (19.5% for households with four people and 23.6% for 5+). This could reflect a greater need for durable and high-quality items in larger households due to shared use. Married or partnered individuals (19.7%) have shown a notable preference for quality, which could be due to a focus on long-term value and satisfaction in products that will be used by more than one person.

The analysis of purchase habit formation among consumers who have maintained their purchasing habits offers insightful revelations into the foundational aspects that influence consumer loyalty and decision-making. This synthesis explores the origin of these purchasing habits, identifying key factors such as convenient location or accessibility, competitive pricing, and superior product quality as primary initiators of consumer purchasing patterns.

The emphasis on convenience highlights a strategic consideration for businesses to optimise their physical and digital presence, ensuring they are easily accessible to their target consumers. At the same time, the regional disparities in price sensitivity underscore the necessity for businesses to tailor their pricing strategies to align with the economic context and consumer expectations within specific locales. Finally, the slight male predominance in prioritising quality, along with its particular importance among the 50 to 59 age group and larger households, indicates a nuanced consumer segment that equates quality with longterm value and satisfaction. This insight suggests that businesses focusing on quality can foster strong customer loyalty, especially among demographics that consider product longevity and performance as paramount.

Online Purchases Frequency

For the ‘frequently purchased’ categories, we asked respondents whether or not they made any of these purchases online. The intent of this set of questions was intended to quantify online shopping frequency, assess e-commerce adoption, evaluate online vs. offline preference, be able to identify trends over time with further iterations of this study, provide demographic segmentation and personalization options and understand how online shopping influences broader consumer behaviour.

A total of 157 respondents reported making purchases online out of 806 respondents (sum of counts provided for male and female, and assuming ‘Yes’ and ‘No’ counts for age groups add up to total responses), suggesting a participation rate in online shopping.

Examining the age demographics, the data reveals a pronounced preference for online shopping among consumers aged 30 to 39, with a participation rate of 35.0%, surpassing that of the younger cohort (18 to 29) at 32.9%. This trend indicates a gradual decrease in online shopping engagement with advancing age, with the oldest groups demonstrating notably lower participation rates.

This aligns with the expectation that digital familiarity and the inclination to use online platforms for purchases are stronger among the younger population. The elevated online purchasing activity observed in the 30 to 39 age group could be attributed to factors such as higher disposable income, a stage of life that often involves the accumulation of household goods and child-rearing necessaries, greater technology adoption rates, and possibly higher levels of education. These findings underscore the variance in e-commerce adoption across age groups, with a marked predilection for online shopping among younger demographics, particularly those in the early to mid-adulthood phase, potentially due to lifestyle, economic, and educational factors. We also observed slightly elevated rates for those in the Western District (23.5%) when compared with other regions.

The 19.5% of respondents who purchased the products online were asked to state how many out of every 10 purchases were made online. The mean response for such purchases is 5.99, indicating a relatively high frequency. The standard deviation of 3.48 points also indicates a significant diversity in consumer behaviour concerning online purchase intensity.

Notably, younger consumers who shop online (18 to 29) tend to shop online more frequently than older demographics, where the mean score of the former is 7.69 as opposed to a mean score of 3.67 for those 60+, highlighting generational differences in shopping preferences and behaviours.

The 30 to 39 age group shows a frequency of 5.24 and this more or less continues to decrease as age increases, suggesting that as age increases, the preference for online shopping slightly diminishes. Whilst it is consistent with previous questions and international trends that younger consumers (18 to 29) are more engaged in online shopping compared to other age groups, caution should be exercised in that this age

group also tended to purchase product that are generally purchased online more frequently in the Maltese context, such as consumer electronics and fashion apparel. Nonetheless, this demographic’s high online engagement level reflects their comfort and familiarity with digital platforms.

Respondents from the Northern District (7.77) and Gozo & Comino District (7.14) also showed higher inclination towards online shopping than their respective counterparts.

While purchasing online is concentrated in 19.5% of all purchase events examined in this study, the result reveals a substantial reliance on digital platforms for purchasing amongst these groups. This trend underscores a significant shift towards e-commerce - especially within certain product/service categories - reflecting these consumer group preferences for the benefits that online shopping offers. Of those who said they sometimes purchase online, nearly 60% of these purchase events occur online. This trend highlights the growing

comfort and trust these consumers have in digital shopping environments. It suggests that for a majority of their shopping needs, these consumers prefer to leverage the accessibility and ease that online platforms provide.

This trend also points towards a hybrid shopping model where consumers blend online and offline shopping experiences. While online shopping is prevalent, the remaining 40% of purchases made by individuals who sometimes purchase online are made offline, potentially indicating that physical stores still play a crucial role in the consumer purchase journey, especially for items where tactile feedback or immediate availability is important, or larger type purchases.

Therefore, while the overall percentage of online shopping (19.5%) seems low at face value, it seems that there is a profile of customer that is more ready for the online experience. With the high engagement in online activities among younger demographics, optimising for mobile shopping is crucial. Ensuring that websites and online stores are mobile-friendly can enhance accessibility and convenience, catering to the shopping preferences of a mobile-savvy consumer base. This implies that businesses would benefit from tailoring their digital marketing strategies to appeal to specific demographics, leveraging platforms and communication styles that resonate with these specific audiences, including the utilisation of an omni channel approach.

The contained shift towards online purchasing contrasts sharply with the global trend of rapid digital transformation in retail. This discrepancy might reflect specific market conditions such as digital infrastructure development, consumer access to online shopping platforms, or cultural preferences for in-store shopping experiences. Despite the global surge in e-commerce driven by convenience and health and safety concerns, the low response rate suggests that in some markets, the transition to online shopping might be occurring at a slower pace, possibly due to these local factors, adapting to the broader trend of digital transformation in retail spurred by convenience or health and safety concerns at a staggered pace.

Online Purchases

[Frequent Purchases]

The data specifically highlights the presence of online purchases across various market categories. This section compares frequent purchase behaviours in various categories with the specific question of whether these purchases are made online.

This section is structured to provide insights into consumer preferences for online versus offline (in-person) shopping across a range of product and service categories. When considering the total instances of frequent purchases from the perspective of the overall sample, we found that only 19.5% of these purchases were sometimes made online. Of these, respondents said that they purchased online 6 times out of every 10 times on average.

As a recap, of all those who purchased online, it was observed that males and females are equally likely to purchase online, whilst those aged 30 - 39 were the most likely, followed by those aged 18 - 29 and those aged 40 - 49. In terms of location, those in the Northern Districts were the most likely to make purchases online, and those in the South Eastern District were the least likely. Interestingly, 29.5% of single consumers made some of these purchases online, far ahead of 15.3% of Married/ Partnered respondents.

Based on the above observations, we try to provide an additional outlook to this data by providing the market categories with the highest interactions by the observed sample.

While high engagement categories related mainly to Food and Supermarket Items for frequent overall purchases, online purchase

preferences were mainly towards “Fashion & Apparel” and “Served Foods & Beverages” having notably higher counts of online purchases compared to other categories, suggesting a strong preference for online shopping in these areas.

Categories with the online purchases included Vacation, Travel & Wellness with 8 out of 10 (80.0%) events, Fashion & Apparel with 27 out of 41 (65.9%) events, Transport Services - taxis, bus & other services with 17 out of 27 (63.0%) events, Auto Purchase, Rental and Parts with a count of 3 from 7 (42.9%), Entertainment with a count of 6 from 16 (37.5%) events, Served Foods & Beverages with a count 29 from 93 (31.2%) events, Consumer Electronics with 4 counts of 15 events (26.7%), Internet, TV & Telephone Service with a count of 3 from 13 (23.1%) events, Frozen, Refrigerated, Canned, and Packaged Goods with a count of 27 from 190 (14.2%) events, Household & Non Food Items with a count of 7 from 57 (12.30%) events, Fresh Produce with a count of 12 from 102 (11.8%) and Meat and Seafood with a count of 11 from 211 (5.2%).

Health and Wellness, Home Improvement, Ironmongery, DIY, and Hardware, Large Home Appliances and OTC Health & Personal Care and Beauty attained no counts, while Gambling & lottery services and Real Estate Purchase or Rental Agreement have been omitted from these observations in view of the low counts.

Online Purchases by Product/Service Category - Frequency & % of purchases

While some categories, like Consumer Electronics and Vacation, Travel & Wellness, have a presence in online purchases, others, particularly those related to fresh or perishable goods like Fresh Produce, might see relatively lower online engagement, highlighting consumer preferences for in-person shopping in certain categories.

In light of the significant purchasing habit changes that COVID-19 brought about, this observation may give scope to study further whether individuals have ever tried to make these purchases online, but then reverted back to their usual shopping habits.

As noted, similar percentages of males and females engage in online shopping. This suggests a gender-neutral trend in the acceptance of online shopping, though preferences for product categories vary by gender. Younger demographics show higher engagement in online shopping due to greater familiarity with digital platforms. Older demographics were seen to prefer traditional shopping methods but a small minority are moving online for certain categories.

Contrary to the typical trend observed in larger countries, Malta’s unique geographical context influences its online shopping patterns distinctly. In this island nation, the propensity for online shopping may not align with conventional urbanrural divides. It appears that higher online shopping engagement may actually occur in areas with fewer physical retail options, brands, or less commercial activity, where consumers find themselves relying more on delivery services to access a broader range of products. This deviation from the norm can be attributed to Malta’s compact size, where the difference in delivery logistics between urban and rural areas is minimised, yet access to diverse shopping options remains a challenge in less commercially dense regions. Consequently, consumers in areas with limited retail presence might turn to online shopping to fulfil their needs, leveraging the convenience of home delivery to overcome local retail limitations. For businesses, this pattern underscores the importance of understanding Malta’s specific retail landscape and consumer behaviour, emphasising the need to cater online services not just to traditionally dense urban markets but also to those in less saturated areas, ensuring equitable service delivery across the island to tap into underserved markets.

The variation in online shopping behaviour across Malta might also be influenced by the demographic composition of certain areas, particularly those with a higher concentration of foreign residents. Areas with more diverse populations, including expatriates and international workers, might exhibit increased online shopping activity due to several factors (different consumer preferences, they might be accustomed to online shopping, familiarity with digital platforms, use online shopping to purchase goods from abroad or from international brands not present on the island).

Higher education levels correlate with higher online shopping engagement, potentially due to higher income levels and comfort with digital platforms, although today it does not seem to have influence on the types of products purchased online. No significant differences were observed between groups relating to higher income (based on higher education and expected higher paid occupations) and more frequent online purchases across a wider range of categories. Moreover, no significant differences are observed by household size, and the possible types of products bought online, with larger households potentially buying more bulk goods or children’s products.

In categories where both online and offline purchases are significant, offering hybrid shopping experiences, such as online ordering with in-store pickup, could cater to a wider range of consumer preferences. Understanding the categories with higher online shopping preferences allows for targeted marketing efforts, especially in promoting online sales channels for those more inclined towards online purchases. This may also help tailor marketing strategies, such as targeting younger consumers with online ads for tech products or offering special online shopping incentives to highincome demographics. Ensuring that online shopping platforms are accessible and appealing to all demographics can help businesses capture a wider market, potentially including features that cater to less digitally savvy consumers or offering diverse payment and delivery options to suit different needs.

For demographics showing a strong preference for offline shopping in certain categories, improving the in-store experience and integrating online elements (like check-in-stock online before visiting) could enhance overall satisfaction.

Artificial Intelligence (AI) & inferences on Advanced Technology

Specific kinds of technology (e.g. social media platforms, smart home devices, fitness trackers, etc.) are used to provide insights into the interests and needs of consumer groups. Different technologies serve different aspects of life, from health and fitness to entertainment and social connectivity. For the purposes of this study it has been opted to explore engagement and comfort towards advanced technologies, which are also trending in terms of interest on the global stage.

Advanced technologies, such as artificial intelligence applications, virtual reality (VR), augmented reality (AR), blockchain, and the Internet of Things (IoT), are reshaping various aspects of daily life and work. This approach was intended to understand the dynamics of technology adoption and usage; mainly the adoption rates and comfort levels. Respondents were asked to rank their comfort level in using AI technologies to achieve specific goals within the buyers journey, from researching information about a product/ service, to booking a meeting with a human representative, ordering a product/service, purchasing the product/service, and getting support on an issue pertaining to the product/service.

The mean score of 3.76 from 806 responses indicates a low to moderate level of AI usage for researching product/service

information among the broader population. This suggests a baseline acceptance and utilisation of AI technologies, but also indicates some general scepticism. When it comes to booking meetings with sales representatives, the mean score rises to 4.12, illustrating a slightly higher use and pointing towards a slightly greater acceptance of AI in facilitating human interactions. The activities of ordering (mean = 3.78) and purchasing (mean = 3.74) products/services via AI are engaged at low to moderate levels, highlighting potential areas for growth in consumer trust and utilisation. The mean score of 3.54 for using AI to get support on issues once again suggests low to moderate use in customer service applications, indicating room for improvement in this area.

Younger respondents (aged 18 to 29) show a significantly higher comfort and usage level of AI across all purchasing stages, from research to post-purchase support. This demographic trend underscores the importance for businesses targeting younger consumers to integrate AI technologies to align with their expectations and preferences. For younger consumers (18 to 29), there’s a notable inclination towards being more comfortable in utilising AI, with higher mean scores reported for researching (6.14), booking meetings (6.35), ordering (6.08), purchasing (5.96), and getting support (5.77). These figures highlight the

potential for a significant role for AI to play in the shopping and transaction process for younger demographics, especially in facilitating automated scheduling, interactions, and customer service solutions. This engagement drops substantially as age increases.

Males report a higher mean score (4.33) than females (3.29) for using AI to research product/service information, potentially revealing gender disparities in AI adoption for information gathering.

The moderate level of technology utilisation across the purchasing process indicates both its current value and potential for growth. Businesses can explore expanding functionalities and improving user experiences to increase adoption. With technology playing a noticeable but not dominant role in purchasing activities, efforts to build consumer trust and demonstrate the reliability and benefits could encourage wider acceptance and use. Businesses could consider tailoring their customer user technology strategies according to demographic preferences, especially focusing on younger consumers who show a higher propensity to engage with automated (non-human) interactions for various purchasing activities.

Nevertheless, it is understood that AI operates in the background and does not require active consumer usage to be effective, which is a crucial aspect of how artificial intelligence is transforming the consumer experience. This subtle

integration of AI into various stages of the consumer journey—from product discovery and personalised recommendations to automated customer service and operational efficiencies—underscores its pervasive influence. For consumers, the benefits of AI manifest in personalised experiences, improved service, and enhanced product offerings, often without their direct involvement. As AI continues to evolve, its integration into business operations will likely become more seamless, further transforming the consumer landscape.

We are led to the conclusion that businesses would benefit from continually investing in technologies that enhance the consumer experience, even in non-interactive ways. The focus should be on solutions that add value seamlessly without requiring direct consumer engagement. While AI may operate in the background, businesses should communicate the benefits and safeguards of their AI systems to consumers. Educating consumers on how such technologies improve their experience and protect their interests can foster trust and acceptance.

AI for Personal Use

A significant portion of the dataset includes respondents who indicate they never use such technologies, with this sentiment being particularly strong among older demographics. There’s a clear distinction in daily technology usage between different age groups and sexes, with younger demographics and males showing higher daily usage counts. Across demographics, there are varying degrees of less frequent technology usage, indicating diverse engagement levels with technology. Younger demographics, particularly the 18 to 29 age group, show a higher propensity for using technology several times a day.

These insights suggest a significant variation in technology engagement across different demographic groups, with age and sex being prominent factors in technology usage frequency. The higher engagement among younger demographics could influence marketing strategies, product development, and digital services targeting.

There are notable differences in technology usage frequencies between males and females, with males showing higher engagement in certain categories. Younger demographics (18 to 29) are more engaged with technology on a daily and multipletimes-daily basis, while older demographics (60+) are more likely to never use certain technologies or use them less frequently.

AI for Work Environment

A sizable portion of respondents, particularly in the older age groups, indicate they never use the technologies in question. Both male and female demographics show equal daily technology usage (32 counts each), with younger demographics (particularly 18 to 29) demonstrating higher daily engagement. Variability in less frequent technology usage (less than every month, one or two times a month) is observed across demographics, highlighting diverse engagement levels with technology. Again, the 18 to 29 age group shows a higher tendency to use technology several times a day, with a significant count indicating high engagement.

Indeed, we find an equal distribution in daily technology usage between males and females, suggesting a balanced engagement level for daily technology use. Younger individuals (18 to 29) are more actively engaged with technology on a daily and several-times-daily basis. Conversely, the older demographic (60+) shows a notable disengagement, with a large number never using certain technologies. The inclusion of locality data (e.g., Southern Harbour District) suggests potential for geographic differences in technology usage patterns, which could be further explored for localised insights.

Of interest is the use of such technologies by respondents aged 30 to 49. Weekly or several times per month usage indicates a moderate to high level of engagement, suggesting that the technology has become part of their routine or lifestyle. This level of engagement could be driven by the technology’s perceived benefits, ease of use, or its role in fulfilling specific needs. The 30 to 49 age group is quite diverse, often encompassing individuals in various life stages, including early career, mid-career, and those with young families.

Interestingly, students also seem to be more likely to use AI tools in their professional lives, possibly foreshadowing an increase in the use of such technologies when these individuals enter the workforce. Moreover, it may be interesting to assess the differences in student disciplines for such technologies so as to assess whether there is higher prevalence in the language, mathematical or coding/software development based areas of study given the substantial capabilities of large language models within these areas. Understanding this may indicate professions that may likely see greater diffusion of such technologies in the near future.

As a general statement, the most pronounced barriers to technology engagement appear to be perceived complexity and necessity, coupled with concerns about privacy and security. Addressing these perceptions through user education, simplifying interfaces, and transparent privacy policies could enhance engagement across broader demographic groups, particularly among older consumers and those less familiar with digital technologies.

In today’s landscape, optimising consumer engagement and trust with technologically enhanced processes necessitates businesses to employ strategies that are tailored to the specific preferences and technological comfort levels of different age demographics. Data indicates that younger consumers exhibit a higher propensity for engaging with digital and AI-based solutions in areas such as marketing, product recommendations, customer service, and the overarching shopping experience. In contrast, strategies aimed at older demographics should prioritise the deployment of user-friendly technology solutions. Furthermore, the refinement of AI-driven tools, including chatbots and virtual assistants, is may aid in enhancing product research and purchasing processes, with a notable appeal among male and younger consumer segments.

Addressing the moderate utilisation of AI in customer support services through enhancements can potentially elevate consumer satisfaction. Crucially, fostering trust through the dissemination of information on the advantages of technology and data privacy measures, coupled with the personalization capabilities of AI, is essential for broadening technology acceptance. Seamless integration of these technologies into business operations is imperative for enriching consumer experiences, emphasising usability without requiring extensive technical knowledge, thereby narrowing the technological engagement gap across consumer demographics. Additionally, acknowledging and addressing the varied technological engagement levels among employees by providing comprehensive training and support is vital. This ensures staff competency in utilising technology effectively, which seemingly would enable them a better product and services to their consumers. Moreover, balancing technology adoption within the workplace is essential to prevent potential alienation or overwhelm ensuring technology serves as an enabler rather than a barrier to engagement and satisfaction.

Annex

Southern Harbour District

Birgu (Vittoriosa)

Bormla (Cospicua)

Fgura

Floriana (Furjana)

Senglea (Isla)

Kalkara

Luqa (Ħal Farruġ)

Marsa

Paola (Paola)

Santa Luċija

Tarxien

Valletta

Xgħajra Żabbar

South Eastern District

Birżebbuġa

Ħal Għaxaq

Il-Gudja

Ħal Kirkop

Marsaskala (Wied il-Għajn)

Marsaxlokk

L-Imqabba

Il-Qrendi

Ħal Safi

Iż-Żejtun

Iż-Żurrieq

Northern District

Ħal Għargħur

Il-Mellieħa (Manikata)

L-Imġarr

Il-Mosta

In-Naxxar (Baħar iċ-Ċagħaq)

San Pawl il-Baħar (Bugibba, Burmarrad and Qawra)

Northern Harbour District

Birkirkara (Fleur-de-Lys and is-Swatar)

Il-Gżira

Il-Ħamrun

L-Imsida

Pembroke

Tal-Pietà (Guardamangia)

Ħal Qormi

San Ġiljan

San Ġwann (Il-Kappara)

Santa Venera

Tas-Sliema

Is-Swieqi (Madliena)

Ta' Xbiex

Western District

Ħ'Attard

Ħal Balzan

Ħad-Dingli

L-Iklin

Ħal Lija

L-Imdina

L-Imtarfa

Ir-Rabat (Baħrija and Tal-Virtù)

Is-Siġġiewi

Ħaż-Żebbuġ

Gozo & Comino District

Il-Fontana

Għajnsielem (Comino)

L-Għarb

L-Għasri

Ta' Kerċem

Il-Munxar

In-Nadur

Il-Qala

San Lawrenz

Ta' Sannat

Ix-Xagħra

Ix-Xewkija

Ir-Rabat (Victoria)

Iż-Żebbuġ

Annex 3 - Education Segmentation - Malta Qualifications Framework (MQF) Level

Classifications Used:

MQF 2 - Primary education

MQF 3 - Secondary - Ordinary level (e.g., SEC/O-Level certificate)

MQF 4 - Secondary - Advanced level (e.g., SEC/A-Level certificate)

MQF 5 - Post-Secondary Certificate (e.g., MCAST certificate)

MQF 5 - Post-Secondary Diploma (e.g., MCAST diploma)

MQF 5 - Vocational education and training (e.g., MCAST certificate/diploma)

MQF 6 - Undergraduate degree (e.g., Bachelor's degree)

MQF 7 - Master's degree

MQF 7 - Postgraduate diploma/certificate

MQF 8 - Doctoral degree (e.g., Ph.D.) MQF 2 MQF 3 MQF 4 MQF 5 MQF 6

Undergraduate Diploma

Undergraduate Certificate

Doctoral Degree

Master’s Degree Post-Graduate Diploma Post-Graduate Certificate

Bachelor’s Degree

General

Introductory Level A*

Note

These are not yet included in legislation:

I. A Full VET Level 1 qualification should enjoy the same parity of esteem as a Full Secondary School Certificate and Profile (SSC&P) Level 1.

Ii A Full VET Level 2 qualification should enjoy the same parity of esteem as 4 Secondary Education Certificate (SEC) subjects at Grade 6 and 7.

Iii A VET Level 3 qualification should enjoy the same parity of esteem as 6 Secondary Education Certificate (SEC) subjects at Grade 1 to 5.

iv A VET Diploma should enjoy the same parity of esteem as the Matriculation Certificate.

Annex 3 - Tables

Demographic Segmentation

Annex 4 - Classification of Market Categories

Auto Purchase, Rental, and Parts

This sector covers the buying, leasing, and renting of vehicles, as well as the purchase of spare parts and accessories. Consumer trends may include a shift towards electric vehicles, online car buying, and subscription-based models for vehicle use.

Household and Non-Food Items

This includes furniture, home textiles, cleaning products, and other non-food items for household use. Trends could involve sustainable and eco-friendly products, smart home gadgets, and a rise in online shopping for home goods.

Banking, Insurance & Investment Services

This sector encompasses financial services, including banking, insurance, investments, and advisory services. Digital banking, personalised insurance products, fintech innovations, and robo-advisors for investments are key trends.

Internet, TV & Telephone Service

This refers to telecommunications services. Trends include the expansion of 5G networks, cord-cutting in favour of streaming services, bundled packages, and the rise of alternative communication platforms.

Consumer Electronics

Involves devices such as smartphones, tablets, and wearables. Trends are driven by technological innovations, brand loyalty, and consumer demand for connectivity and convenience.

Large Home Appliances

This sector includes refrigerators, washers, dryers, and ovens. Energy efficiency, smart appliances compatible with home automation systems, and durability are significant factors influencing consumer choices.

Entertainment

Covers movies, music, video games, and live events. The rise of streaming platforms, esports, virtual and augmented reality experiences, and personalised content are transforming this sector.

Meat and Seafood

Concerns the purchase of fresh, frozen, or processed meat and seafood. Trends include a growing demand for organic, locally sourced, and ethically raised products, as well as plant-based alternatives.

Fashion & Apparel

Involves clothing, footwear, and accessories. The industry is seeing shifts towards fast fashion alternatives, sustainable and ethical brands, online shopping, and personalised fashion tech solutions.

OTC Health & Personal Care and Beauty

Includes over-the-counter medications, health supplements, and beauty products. Consumer trends are moving towards natural and organic products, telehealth services, and personalised skincare routines.

Fresh Produce

Refers to the purchase of fresh fruits and vegetables. There’s a growing preference for organic, locally-grown produce, and direct-toconsumer models like subscription boxes and farmers’ markets.

Real Estate Purchase or Rental Agreement

This sector covers the buying, selling, and renting of property. Trends include online real estate platforms, virtual tours, and a focus on sustainable and smart homes.

Frozen, Refrigerated, Canned, and Packaged Goods

Encompasses a wide range of food products. Convenience, health-conscious options, and eco-friendly packaging are influencing consumer preferences.

Served Foods & Beverages

Refers to meals and drinks served in restaurants, cafes, and bars. The sector is seeing a rise in delivery services, health-focused menus, and experiential dining.

Gambling and Lottery Services

Involves betting and gambling activities. Online platforms, mobile apps, and responsible gambling measures are key trends.

Transport Services - Taxis, Bus & Other Services

Covers public and private transportation services. Trends include the rise of ride-sharing apps, electric and autonomous vehicles, and improvements in public transport systems.

Health and Wellness

Includes services related to physical and mental health. There’s an increasing focus on preventive healthcare, wellness apps, and holistic health practices.

Vacation, Travel & Wellness

Covers the tourism industry, including hotels, flights, and travel packages. Trends include eco-tourism, personalised travel experiences, and wellness retreats.

Home Improvement, Ironmongery, DIY, and Hardware

This sector is about products and services for home renovation and repairs. The DIY movement, smart home upgrades, and online tutorials are driving consumer engagement.

Annex 5

1. International Trends8

Background to the Assessment

The desk research conducted above results in the following international trends, which serve as a part of the basis for the primary research effort.

Considerations for Changing Consumer Behaviour

• Instant Access and Speed with consumers expect instant access to websites, platforms, and services online, with minimal loading times and no downtime. The tolerance for delays and disruptions is lower than ever, emphasising the need for robust network infrastructure. Seamless Omnichannel Experiences as the consumer navigates across multiple digital channels, they expect a seamless experience whether they are on a mobile app, website, or a social media platform. This requires an integrated backend infrastructure that supports omnichannel strategies. High-Quality Content Streaming with the rise of video streaming services, online gaming, and virtual reality experiences, there’s a growing demand for high-bandwidth networks that can deliver high-quality content without lag or buffering issues. Secure Transactions as more financial transactions occur online, from e-commerce purchases to digital banking, consumers demand secure, fast, and reliable transaction processes, necessitating advanced security measures integrated into the network infrastructure.

• AI technology is becoming increasingly sophisticated, enabling businesses to create more targeted and responsible marketing strategies. AI is contributing to this transformation in several ways. Personalization at Scale with AI algorithms analyses vast amounts

of data to understand consumer behaviour, preferences, and purchase history, allowing for personalised marketing messages tailored to individual consumers. This level of personalization enhances the consumer experience and can significantly improve conversion rates. By predicting future consumer behaviour based on past actions, AI helps businesses anticipate needs and preferences, allowing for proactive rather than reactive marketing strategies. This can enhance customer satisfaction and loyalty. AI-powered chatbots and virtual assistants provide consumers with instant, 24/7 assistance, answering queries, providing recommendations, and even facilitating purchases. This not only improves customer service but also frees up human resources for more complex tasks. AI enables more responsible marketing by ensuring that ads are not only targeted but also placed in appropriate contexts, reducing the risk of brand damage through association with unsuitable content. Moreover, AI can help ensure that marketing practices are inclusive and free from biases by auditing data and algorithms for fairness. The rise of immersive technologies and Enhanced Product Visualisation creating new opportunities for digital marketing. The use of AI for Engaging Brand Experiences, Event and Location-Based Marketing, Storytelling and Content Marketing and the integration of AI with immersive technologies presents even greater opportunities. AI can personalise AR and VR experiences based on the user’s history and preferences, making immersive experiences not only engaging but also highly relevant to each consumer.

• Enhancing these digital support systems with more efficient, personalised, and user-friendly interfaces can significantly improve the overall customer

8 Sources: While we know that unfortunately information is limited in the local context, we were able to access various sources to map out the international context. Market research firms: Nielsen, Euromonitor, McKinsey & Company that publish global and regional trend reports.

- Academic journals in marketing and consumer behaviour detailed studies and analyses.

- Industry publications such as Harvard Business Review, Forbes, or Business Insider regularly discuss these trends in the context of global market dynamics.

- Government and other non-governmental organisations also provide reports and data, especially regarding regulatory changes and sustainability efforts.

experience. Traditional methods of collecting consumer feedback are becoming less effective. Companies must adopt new strategies to listen to their customers, such as leveraging social media insights, analysing behaviour patterns, and using AI-driven analytics to understand customer needs and preferences.

• Preference for natural and organic products perceived as natural, or free from artificial additives. Consumers are scrutinising labels more closely than ever, opting for products with clean, understandable ingredient lists. Increased Demand for Wellness Services, including fitness classes, meditation and yoga sessions, and wellness retreats, are seeing heightened demand. The emphasis is on holistic health, encompassing both physical fitness and mental well-being. Adoption of Wearable Technology, such as fitness trackers and smartwatches, have become popular tools for individuals aiming to take control of their health. These devices offer insights into physical activity, sleep patterns, and even stress levels, enabling users to make informed health decisions. Sustainable and Ethical Choices with Health-conscious consumers are also increasingly concerned with sustainability and ethics, choosing brands that demonstrate environmental responsibility and ethical business practices. The connection between personal health and the health of the planet is becoming more pronounced in consumer choices..

• Preference for Digital Channels with consumers increasingly prefer digital channels that offer 24/7 access to services and information. Online shopping, mobile apps, and social media platforms are favoured for their ability to provide immediate access to products, services, and support. Expectations for Quick Delivery and the demand for fast delivery services have skyrocketed, with same-day or next-day delivery becoming a standard expectation in many sectors, particularly in e-commerce. This expectation extends to the immediacy of digital products and services, where downloads and streaming are expected to be instantaneous. Use of On-demand Services: across various industries, from food delivery to ride-sharing, reflects the consumer’s desire for immediate fulfilment. These services cater to

the need for speed and convenience, allowing consumers to get what they want, when they want it. Self-service Options with consumers valuing the ability to quickly resolve issues or complete transactions independently. Self-service kiosks, online check-ins, and automated customer service tools are increasingly popular for their ability to offer speedy solutions without the need for direct human interaction.

• For online buying trends Voice search and commerce are becoming integral parts of e-commerce. Mobile-first user experience design is essential due to the prevalence of smartphone usage. Social media’s significant role in e-commerce, particularly platforms like TikTok and Instagram. Environmental and ethical considerations are increasingly influencing online shopping behaviours. The rise of VR technology in online shopping for enhanced visualisation and personalization.

• Eco-conscious purchasing decisions, where consumers are increasingly making purchasing decisions based on the environmental impact of products. This includes preferences for products made from recycled materials, products that are recyclable or biodegradable, and those with minimal packaging. Support for ethical practices, where there’s a rising demand for transparency in brand practices, including ethical sourcing, fair labour practices, and reducing carbon footprints. Consumers are more inclined to support brands that can demonstrate a commitment to these values. Willingness to pay a premium from a significant segment of consumers that is willing to pay more for sustainable products that align with their environmental and social values. This willingness, however, is often balanced by the expectation of quality and effectiveness.

• In terms of consumer preferences, a shift in values towards purpose, ethics, and social responsibility. Demand for immersive and emotionally resonant brand experiences., declining brand loyalty and the importance of collaborative and influencer marketing. For digital marketers: Emphasis on AI and machine learning for personalised marketing. The evolution of influencer marketing towards micro-influencers. The significance of SEO and Pay-Per-

Click (PPC) trends in adapting to the changing digital landscape.

• Brand loyalty is becoming less about price competitiveness and more about the quality of service. Consumers show a preference for brands that provide superior service, indicating that great service can outweigh the allure of low prices. Despite advancements in technology, digital support systems (like customer service chatbots or help centres) often remain the weakest link in the customer journey. Loyalty to Sustainable Brands: Consumers are showing increased loyalty to brands that actively promote and practice sustainability. This loyalty extends beyond purchases, with consumers also advocating for these brands within their personal networks.

• Financial concerns influenced by economic factors such as inflation are increasingly impacting consumer purchasing decisions. This shift is pushing both individuals and businesses to adjust their strategies in response to the changing economic landscape. Increased Price Sensitivity due to Inflationary pressures leading to shoppers being more likely to compare prices, seek discounts, and prioritise essential purchases over discretionary spending. Consumers may also opt for cheaper alternatives or private-label products instead of premium brands. This behaviour, known as “trading down,” helps consumers maintain their purchasing power despite rising prices. This may also lead to budget reallocation and delayed purchases: High-ticket items, including electronics, vehicles, and luxury goods, might see a delay in purchasing decisions as consumers wait for more favourable economic conditions or save up for longer periods.

Outlook on Consumer Spending based on 2023 insights

Despite economic uncertainties, consumer spending remains resilient, though cautious. Consumers continue to spend due to strong household balance sheets, especially among higher-income groups. However, there’s a noticeable trend of trading down for value while still showing a willingness to splurge on certain categories. Service spending has seen a rebound as COVID-19 concerns diminish, indicating a shift back towards experiential spending.

Lingering Post-COVID-19 Consumer Trends

The COVID-19 pandemic has accelerated digital adoption, leading to lasting changes in consumer behaviour. E-commerce has seen a significant surge, with many consumers intending to maintain their online shopping habits. There’s also been a shift in spending, with an increase in home investments during the pandemic but a renewed interest in spending on dining, entertainment, and travel as restrictions are lifted. Moreover, brand loyalty has been disrupted, with many consumers trying new shopping behaviours and brands, reflecting a desire for brands that align with their values.

Insights from Top Market Research Companies

• Euromonitor’s Top Consumer Trends for 2024 focus on adapting to evolving consumer expectations and behaviours, including the integration of generative AI for personalised experiences, seeking joy through delightful distractions amid global challenges, increasing scepticism around greenwashing with a call for genuine sustainability efforts, navigating progressively polarised societal and political landscapes, and embracing value hacks for smarter spending without compromising quality. Additionally, there’s a shift towards simplified wellness routines prioritising convenience and effectiveness.

• McKinsey & Company outlines four Major Trends in Consumer Behaviour in 2023 onwards:

• Trading Down and Splurging Selectively: Consumers are exhibiting paradoxical behaviour by both seeking value in cheaper brands or privatelabel products and splurging on premium products and services. This dichotomy highlights the importance of understanding specific consumer segments and tailoring offerings accordingly.

• Shopping everywhere and All at Once: The demand for a seamless Omnichannel experience is growing, with consumers using multiple channels for each purchase journey. Achieving Omni channel excellence is becoming increasingly important for enhancing consumer value and satisfaction.

• Finding Comfort in Familiarity and Exploring Brand Promiscuity: While big brands have traditionally dominated, there’s a noticeable shift towards trying new, smaller brands. Consumers are diversifying their purchases, indicating a blend of loyalty and curiosity in their shopping behaviours.

• Demanding Sustainability and Affordability: A significant portion of consumers prioritise sustainability in their purchasing decisions, though there is hesitancy about paying a premium for sustainable products, especially in times of inflation. This presents a challenge for businesses to balance sustainability with affordability.

• Nielsen’s insights for 2023 onwards indicate several significant trends in the marketing and consumer behaviour domains, reflecting the evolving landscape of media consumption and advertising strategies. A majority of global marketers foresee their advertising budgets increasing, highlighting an optimistic outlook on marketing investments despite concerns over economic conditions. This optimism is notably reflected in the expected growth of ad budgets, with a focus on Connected TV (CTV) and streaming, suggesting a shift towards digital media channels amidst economic uncertainty.

• The shift towards streaming is evident, with a substantial number of marketers incorporating streaming into their media planning. However, less than half regard this spending as effective, indicating challenges in assessing the value and return on investment (ROI) of streaming advertisements. This highlights a critical area for improvement in marketing analytics and effectiveness measurement within the rapidly growing streaming domain.

• There’s a noted low confidence among marketers in measuring ROI across digital channels, compounded by the use of multiple measurement solutions. This scenario suggests a complex digital marketing environment where achieving a comprehensive understanding of marketing performance is challenging.

• Shift towards CTV Advertising (taking advantage of the smart TV’s or connected device’s such as Apple TV) ability to connect to the internet, providing advertisers with

the opportunity to reach specific audiences through streaming video content, apps, and even traditional TV channels accessed digitally. The global ad budgets are increasingly leaning into CTV as audiences move towards streaming content. This trend is supported by substantial viewership data across various countries, underlining streaming content’s widereaching impact and the strategic shift in advertising budgets to capture this audience.

These trends underscore the importance for businesses to adapt to the rapidly changing consumer landscape, emphasising the need for a deep understanding of consumer preferences. The topics discussed during the conference revolved around the main international trends, with the help of the market research exercise that provided general insights into the consumer in Malta today.

Changing Demographics, Rise of Gen-Z, Globalization and Cultural Fusion.

The changing demographics, including the rise of Gen-Z and the impact of globalisation and cultural fusion, are significantly reshaping consumer behaviour and market dynamics. These factors are not only influencing current trends but are also setting the stage for the future of commerce, marketing, and product development. Here’s an elaboration on how these elements are intertwining to redefine the consumer landscape:

The Changing Demographics with many regions are experiencing an ageing population, which impacts purchasing patterns, particularly in healthcare, wellness, and leisure sectors. Brands are adapting by offering products and services tailored to older adults’ needs, emphasising ease of use, accessibility, and health benefits. There’s a move away from traditional family models towards more diverse structures, including single-parent families, child-free couples, and multigenerational households. This shift requires businesses to consider a broader range of living situations and personal needs in their offerings.

Gen-Z, having grown up with the internet and digital technology, exhibits unique consumer behaviour. Their comfort with technology influences their shopping habits, preferences for digital interactions, and expectations for online presence from brands. This demographic is also particularly values-driven, prioritising

brands that demonstrate commitment to sustainability, inclusivity, and ethical practices. Their purchasing decisions are often influenced by a brand’s social and environmental impact. Gen-Z’s consumption of media primarily through social media platforms shapes how they interact with brands. They value authenticity, engaging content, and direct communication, shifting how companies approach marketing and customer service.

Globalisation and cultural fusion have led to an increased exchange of cultural ideas, practices, and products. Consumers now have access to a wider range of global goods and are more open to trying products from different cultures, expanding market opportunities for international brands. As people from different cultural backgrounds interact more frequently and intimately, hybrid cultural identities emerge. This fusion influences food, fashion, entertainment, and more, creating demand for products that reflect a blend of cultural traditions. Despite the global exchange, there’s a growing trend towards localising products and marketing strategies to fit the cultural context of different regions. This approach acknowledges the global influences while respecting and adapting to local preferences and values.

Convenience & Speed (Instant Access and Speed above). Prioritising instant access and rapid service, have become paramount in consumer expectations, reshaping how businesses approach service delivery, product design, and customer interaction. This trend is largely driven by advancements in technology and the fast-paced nature of modern life, with consumers seeking solutions that fit their busy schedules and provide immediate gratification. Here’s an in-depth look at how convenience and speed are influencing consumer behaviour and the strategic responses from businesses.

Digital Transformation & Tech-Driven Shopping Experiences (Advanced Technologies & AI). With the advent of these technologies, consumers have come to expect a high degree of personalization in their shopping experiences. They seek recommendations and services that align closely with their preferences and purchase history. The integration of technology in shopping has raised consumer expectations for convenience. Shoppers look for easy navigation, fast checkouts, and quick delivery options as standard service attributes. Technologies like AR and VR have elevated consumer

expectations for interactive and immersive shopping experiences, leading to increased engagement and longer interaction times with brands online.

Health and Wellness with incremental preference for Health-Conscious Products. Consumers are gravitating towards products and services that promote physical health, such as organic foods, nutritional supplements, and fitness equipment. There’s a marked increase in the demand for products with health benefits, including those that are non-GMO, glutenfree, and free from artificial additives. Health and wellness are no longer viewed as mere aspects of life but as integral parts of a lifestyle. This includes regular exercise, meditation, mindfulness practices, and prioritising mental health, driving demand in sectors like fitness classes, mental health apps, and wellness tourism. The health and wellness trend overlaps significantly with sustainability, with consumers showing a preference for eco-friendly products and practices. The link between personal well-being and environmental health is increasingly recognized, leading to choices that are both health-conscious and sustainable. The adoption of digital health solutions, such as fitness trackers, health apps, and telehealth services, has skyrocketed. Consumers are leveraging technology to monitor their health, track their fitness progress, and access health services remotely, reflecting a blend of health consciousness and digital savviness.

Information Overload or ‘Decision Paralysis’ is when the consumer is faced with too many choices or excessive information, leading to difficulty in making decisions. This paralysis is not just limited to purchasing decisions but extends to all facets of digital interactions. The constant barrage of information has contributed to reduced attention spans. Consumers often skim content rather than engaging deeply, making it challenging for businesses to communicate effectively. Many consumers now prefer simplified information and streamlined decisionmaking processes. There’s a growing demand for tools, services, and content that cut through the noise and offer curated insights. In an effort to combat information overload, consumers increasingly rely on trusted sources and authorities for information. Influencers, reputable news outlets, and expert recommendations have become go-to resources.

Personalization and the expectation for tailored experiences means that consumers increasingly expect interactions with brands

to be tailored to their preferences, history, and context. Personalization has moved beyond merely using the customer’s name in communications to encompassing curated product recommendations, customised content, and targeted marketing messages. Personalised experiences tend to resonate more deeply with consumers, leading to higher engagement rates. Customers are more likely to return to a brand that remembers their preferences and makes relevant suggestions, fostering loyalty. While privacy remains a significant concern, many consumers are willing to share personal information in exchange for benefits such as discounts, product recommendations, and personalised services, provided that brands are transparent and responsible with their data.

Regulation - Digital Services Act (DSA) that is a significant regulatory shift aimed at creating a safer digital space where the fundamental rights of users are protected and to establish a level playing field for businesses. As part of the European Union’s digital strategy, the DSA addresses the challenges posed by the rapidly evolving digital landscape, including issues related to illegal content, transparency, and the spread of disinformation online. The DSA is influencing the digital ecosystem by enhancing user safety aims to protect users from illegal content, goods, and services online by imposing stricter obligations on digital platforms to swiftly identify and remove such content. It Increases transparency requiring digital services to disclose how they moderate content, how algorithms recommend content to users, and how they target advertising, aiming for more transparency in online platforms’ operations. The DSA holds online platforms, especially very large ones, accountable for their role in disseminating illegal content and disinformation, including providing clear reporting mechanisms and ensuring the effectiveness of their content moderation systems. It seeks to ensure that users’ fundamental rights, including freedom of expression and information, are upheld in the digital space, providing mechanisms for users to appeal content moderation decisions. It also promotes fair competition by setting clear responsibilities and accountability measures for digital platforms, and aims to create a fairer digital marketplace, preventing larger platforms from using their position to disadvantage smaller players.

Sustainability and Ethical Consumption with preference for eco-friendly products. Consumers are increasingly seeking

out products that are environmentally friendly, such as those made from recycled materials, those that are biodegradable, and those with minimal packaging. There’s a growing willingness to pay a premium for products that are perceived as being less harmful to the environment. Beyond environmental considerations, ethical practices in production and supply chain management are becoming crucial in purchasing decisions. Consumers are more inclined to buy from brands that demonstrate fair labour practices, animal welfare, and a commitment to reducing their carbon footprint. There’s a rising demand for transparency from businesses about the sourcing of their materials, their manufacturing processes, and the overall environmental and social impact of their products. Consumers are using this information to make more informed choices that align with their values. In line with sustainability, there’s a growing trend towards minimalism and purchasing durable goods. Consumers are increasingly rejecting the throwaway culture associated with fast fashion and disposable products, opting instead for items that last longer and promote less waste.

The Challenge/Importance of Customer Engagement where customers are more likely to develop a strong attachment to a brand, leading to repeat purchases and long-term loyalty. Engagement helps in creating emotional connections, making customers feel valued and understood. Regular and meaningful engagement improves customer satisfaction by ensuring that customers’ needs and concerns are addressed promptly. Satisfied customers are more likely to become brand advocates, sharing their positive experiences with others. Engagement initiatives provide businesses with valuable insights into customer preferences, expectations, and areas for improvement. These insights can drive product development, marketing strategies, and service enhancements. Ultimately, engaged customers are more likely to make purchases and try new offerings. By fostering engagement, businesses can boost sales, cross-sell, and upsell more effectively, contributing to higher revenue.

The Intensification of Subscription Models with the consumer preference leaning towards having access to products and services without the burdens of ownership. This shift is driven by the desire for flexibility, reduced clutter, and the financial advantages of subscribing versus owning. Subscription services

often offer personalised experiences, curating products, and content to match individual preferences. This tailored approach enhances the value proposition for consumers, making subscriptions more appealing. Subscriptions offer unparalleled convenience, delivering products and services directly to consumers on a regular basis without requiring them to reorder. This set-it-and-forget-it model is highly attractive in today’s fast-paced world. Many consumers view subscription models as more sustainable, reducing waste through better product utilisation and, in some cases, offering eco-friendly product alternatives.

Transparency & Authenticity have become increasingly important to consumers, influencing how they perceive and interact with brands. In an era where information is readily available, consumers are more discerning and expect honesty and integrity from the businesses they support. This shift toward valuing transparency and authenticity impacts purchasing decisions, brand loyalty, and overall consumer trust. The significance in the modern market is to help in building trust between consumers and brands. When businesses are open about their practices, policies, and challenges, and remain true to their brand values, they cultivate a sense of trust with their audience. Consumers are more likely to remain loyal to brands that consistently demonstrate authenticity and are transparent in their dealings. This loyalty often translates into repeat business, wordof-mouth recommendations, and a strong brand following. In crowded marketplaces, transparency and authenticity can serve as key differentiators. Brands that openly communicate their unique values, processes, and stories can stand out and attract consumers looking for businesses that align with their personal values. Moreover, when issues arise, a transparent and authentic approach to crisis management can help mitigate damage to a brand’s reputation. Admitting mistakes and taking clear steps to address them demonstrates responsibility and can preserve consumer trust.

Trust and Privacy Concerns with consumers becoming more vigilant about the privacy policies and data handling practices of brands. They often scrutinise how their information is collected, used, and shared before engaging with a brand or making a purchase. There’s a growing demand for secure transaction methods. Consumers are more likely to trust and continue purchasing from platforms that offer transparent and robust security measures to protect their

personal and financial information. The use of privacy-enhancing tools, such as VPNs, ad blockers, and secure browsers, is on the rise. Consumers are taking proactive steps to protect their online privacy and limit the amount of personal data exposed to businesses and third parties. Brands that prioritise customer privacy and are transparent about their data practices tend to garner more trust. Consumers are gravitating towards companies that not only comply with privacy regulations but also go above and beyond in protecting user data.

2. Conference Attendee Engagement

During the conference, and after the presentation of the international trends above, attendees were asked to rank these trends according to the importance they perceive these to have for their business. Below are the top 5 categories that resulted from this question:

While keeping in mind the bias created by the profile of the attendees at the conference, it is nonetheless interesting to observe the expectations in terms of convenience and speed to be the most important aspects that businesses expect to wrangle with. Perhaps relatedly, the changing demographic profile of consumers and specifically the rise of Gen-Z was considered to be the second most important trend, followed by the challenge/importance of customer engagement, personalization, and the digital transformation & tech-driven shopping experience.

The ascendance of convenience and speed as the most critical trend reflects a universal shift towards immediacy in consumer expectations. Businesses are thus compelled to innovate continuously to streamline their operations and delivery mechanisms. This trend’s prominence amongst business decision makers and management suggests that efficiency in

service and product accessibility is seen as not just a competitive advantage but also a fundamental expectation from local consumers.

Ranking customer engagement as a paramount trend underscores the increasing complexity of building and maintaining customer relationships in the digital age. This result points towards an acknowledgment among businesses of the need to foster genuine connections and engagement strategies that go beyond traditional advertising. It also suggests a shift towards more interactive and personalised communication channels to capture consumer attention and loyalty. The prioritisation of personalization reflects a growing consumer demand for tailored experiences and products.

This trend’s prominence in the poll results reinforces the idea that personalization is perceived as a key driver of customer satisfaction and loyalty. Businesses are

recognized for needing to leverage data and technology to customise their offerings and communications, indicating a broader trend towards more individualised consumer interactions.

The focus on digital transformation and tech-driven shopping experiences as a top trend highlights the critical role of technology in reshaping retail and consumer interactions. This emphasis suggests that businesses must invest in digital platforms and innovative technologies to meet consumer demands for seamless, engaging online experiences. It may point to a future where the integration of technologies such as AI, AR, and VR into shopping experiences could become standard practice.

The highlighted trends reflect a complex interplay between technological advancement, changing consumer values, and the need for speed and efficiency in all aspects of business operations. This prioritisation indicates a clear recognition of the shifting consumer landscape and the various challenges and opportunities it presents. Businesses that can effectively adapt to these

trends, particularly by embracing digital transformation and aligning with the values of emerging consumer segments like Gen-Z, are likely to achieve a competitive edge in the evolving market landscape, so long as they are verified against a nuanced local context.

The poll results therefore underscore the importance of agility, customer-centricity, and innovation in navigating the future of business and consumer interactions. These insights offer a roadmap for businesses aiming to thrive in the dynamic and increasingly digital marketplace of tomorrow.

With these international trends set as a context, attendees were also asked about whether they feel that their company is prepared to meet future consumer expectations. Whilst a majority responded that they are, 42% of respondents gave a score of 6 or less, indicating a noteworthy lack of confidence in their company’s preparedness.

We express our heartfelt gratitude to all who contributed to this report, our collaborators for their invaluable insights and expertise, and the generous support of our sponsors, whose commitment made this endeavor possible.

Annex 6 - Tablature & Test Statistics

Table of Contents

Table 6.1a - Large/Expensive Purchases (Count & Row %) ......................................................................................................................................................................................3

Table 6.1b - Large/Expensive Purchases (Test Statistic)..........................................................................................................................................................................................4

Table 6.2a - Information Search Dynamics for Large Purchases (Count, Row Yes/ No % - Multiple Choice) ..............................................................................................................5

Table 6.2b - Information Search Dynamics for Large Purchases (Count & Row %).....................................................................................................................................................6

Table 6.2c - Information Search Dynamics for Large Purchases (Test Statistic).........................................................................................................................................................7

Table 6.3a - Evaluation of Alternatives [Large Purchases] (Count, Row Yes/ No % - Multiple Choice)......................................................................................................................8

Table 6.3b - Evaluation of Alternatives [Large Purchases] (Count & Row N %).........................................................................................................................................................9

Table 6.3c - Evaluation of Alternatives [Large Purchases] (Test Statistic) ..............................................................................................................................................................10

Table 6.4a - Social Media Platforms (Count, Row Yes/ No % - Multiple Choice) .....................................................................................................................................................11

Table 6.4b - Social Media Platforms (Count & Row %)............................................................................................................................................................................................12

Table 6.5a - Factors Influencing Product/Service Selection ....................................................................................................................................................................................14

Table 6.5b - Factors Influencing Product/Service Selection.....................................................................................................................................................................................15

Table 6.5c - Factors Influencing Product/Service Selection (Test Statistic)..............................................................................................................................................................16

Table 6.6a - Most Imp. Factors Influencing Selection (Count, Row Yes/ No % - Multiple Choice).............................................................................................................................17

Table 6.6b - Most Imp. Factors Influencing Selection (Count & Row %) ...................................................................................................................................................................18

Table 6.6c - Most Imp. Factors Influencing Selection (Test Statistic) .......................................................................................................................................................................19

Table 6.7a - Assessment & Final Purchase Decision (Count, Row Yes/ No % - Multiple Choice) ...............................................................................................................................20

Table 6.7b - Assessment & Final Purchase Decision (Count & Row %) .....................................................................................................................................................................21

Table 6.7c - Assessment & Final Purchase Decision (Test Statistic) .........................................................................................................................................................................22

Table 6.8a - Frequent Purchase Groups (Count & Row %) ......................................................................................................................................................................................23

Table 6.8b - Frequent Purchase Groups (Test Statistic)..........................................................................................................................................................................................24

Table 6.9a - Aggregated Market Category Data (Count & Row %)........................................................................................................................................................................25

Table 6.9b - Aggregated Market Category Data (Test Statistic) ...........................................................................................................................................................................26

Table 6.10a - Advertisements or Promotions (Count & Row %)...............................................................................................................................................................................27

Table 6.10b - Advertisements or Promotions (Test Statistic) ..................................................................................................................................................................................27

Table 6.11a - Recall of Ads & Advertising Channel Effectiveness (Count, Row Yes/ No % - Multiple Choice) ..........................................................................................................28

Table 6.11b - Recall of Ads & Advertising Channel Effectiveness (Count & Row %).................................................................................................................................................29

Table 6.11c - Recall of Ads & Advertising Channel Effectiveness (Test Statistic).....................................................................................................................................................30

Table 6.12a - Post Purchase Behaviour & Customer Support Need (Count & Row %)...............................................................................................................................................31

Table 6.12b - Post Purchase Behaviour & Customer Support Need (Test Statistic)..................................................................................................................................................31

Table 6.12a - Satisfaction Levels Customer Support (Count, Mean, Standard Deviation)........................................................................................................................................32

Table 6.12b - Satisfaction Levels Customer Support (Test Statistic)........................................................................................................................................................................33

Table 6.13a - Changing Purchasing Behaviours (Count & Row %)...........................................................................................................................................................................34

Table 6.13b - Changing Purchasing Behaviours (Test Statistic) ..............................................................................................................................................................................34

Table 6.14a - Changes in Consumer Purchasing Habits (Count, Row Yes/ No % - Multiple Choice) .........................................................................................................................35

Table 6.14c - Changes in Consumer Purchasing Habits (Test Statistic)....................................................................................................................................................................37

Table 6.15a - Cause of Change in Consumer Purchasing Habits (Count, Row Yes/ No % - Multiple Choice) ............................................................................................................38

Table 6.15b - Cause of Change in Consumer Purchasing Habits (Count & Row %) ..................................................................................................................................................39

Table 6.15b - Cause of Change in Consumer Purchasing Habits (Test Statistic)......................................................................................................................................................40

Table 6.16a - Purchase Habit Formation (Origin) (Count, Row Yes/ No % - Multiple Choice)..................................................................................................................................41

Table 6.16b - Purchase Habit Formation (Origin) (Count & Row %)........................................................................................................................................................................42

Table 6.16c - Purchase Habit Formation (Origin) (Test Statistic)............................................................................................................................................................................43

Table 6.17a - Online Purchases (Count & Row %)...................................................................................................................................................................................................44

Table 6.17b - Online Purchases (Test Statistic) ......................................................................................................................................................................................................44

Table 6.18a - Online Purchase Frequency/ 10 Purchases (Count, Mean & Standard Error of Mean) .......................................................................................................................45

Table 6.18b - Online Purchase Frequency/ 10 Purchases (Test Statistic) ................................................................................................................................................................46

Table 6.19a - Artificial Intelligence (AI) & inferences on Advanced Technology (Mean)..........................................................................................................................................47

Table 6.19b - Artificial Intelligence (AI) & inferences on Advanced Technology (Test Statistic)...............................................................................................................................48

Table 6.20a - AI for Personal Use (Count & Row %)................................................................................................................................................................................................51

Table 6.20b - AI for Personal Use (Test Statistic) ...................................................................................................................................................................................................51

Table 6.21a - AI for Work or Professional Life (Count & Row %) .............................................................................................................................................................................52

Table 6.21b - AI for Work or Professional Life (Test Statistic).................................................................................................................................................................................52

Table 6.1a - Large/Expensive Purchases (Count & Row %)

[Auto

[Consumer Electronics] [Entertainment][Fashion& Apparel] [Fresh Produce] [Frozen, Refrigerated, Canned,and Packaged Goods]

[Healthand Wellness]

[Home Improvement, Ironmongery, DIY,and Hardware]

[Household andNon FoodItems]

[Internet,TV &Telephone Service]

[LargeHome Appliances] [Meatand Seafood]

[OTCHealth &Personal Careand Beauty]

[RealEstate Purchaseor Rental Agreement]

[Served Foods& Beverages] [Transport Servicestaxis,bus& other services] [Vacation, Travel& Wellness]

30to39 107.1%64.3%1913.6%00.0%75.0%00.0%139.3%00.0%00.0%1812.9%10.7%1410.0%53.6%42.9%128.6%10.7%00.0%3021.4% 40to49 86.5%97.3%1612.9%00.0%54.0%21.6%54.0%10.8%00.0%1612.9%10.8%1612.9%21.6%10.8%54.0%75.6%10.8%2923.4% 50to59 32.1%32.1%1510.4%21.4%32.1%10.7%128.3%00.0%10.7%2114.6%00.0%2416.7%139.0%00.0%21.4%149.7%10.7%2920.1% 60+ 62.5%31.3%229.2%10.4%72.9%62.5%2912.1%00.0%00.0%2912.1%31.3%3916.3%2610.8%41.7%20.8%2912.1%10.4%3313.8% SouthernHarbourDistrict 148.4%31.8%2414.5%63.6%74.2%21.2%106.0%00.0%00.0%1911.4%10.6%2414.5%116.6%10.6%42.4%137.8%00.0%2716.3%

NorthernHarbourDistrict 135.9%115.0%3114.0%10.5%83.6%31.4%156.8%00.0%00.0%209.0%31.4%2611.7%188.1%31.4%73.2%188.1%52.3%4018.0%

SouthEasternDistrict 64.5%10.7%1511.2%00.0%107.5%64.5%1813.4%00.0%00.0%1611.9%10.7%1611.9%107.5%32.2%43.0%96.7%10.7%1813.4%

WesternDistrict 76.9%32.9%1615.7%43.9%76.9%00.0%54.9%11.0%00.0%1110.8%11.0%1312.7%32.9%00.0%32.9%109.8%11.0%1716.7% NorthernDistrict 53.5%107.0%149.9%00.0%74.9%10.7%128.5%00.0%10.7%2014.1%00.0%1812.7%74.9%32.1%32.1%117.7%10.7%2920.4% Gozo&CominoDistrict 00.0%00.0%410.0%00.0%12.5%00.0%512.5%00.0%00.0%615.0%12.5%1025.0%12.5%12.5%25.0%12.5%00.0%820.0% 1 33.4%11.1%1921.6%00.0%55.7%11.1%89.1%00.0%00.0%910.2%11.1%1618.2%66.8%11.1%33.4%78.0%11.1%78.0% 2 135.7%83.5%229.6%20.9%52.2%31.3%2310.0%10.4%10.4%3113.5%10.4%3113.5%177.4%31.3%52.2%2410.4%41.7%3615.7% 3 146.1%73.1%2711.8%73.1%146.1%31.3%93.9%00.0%00.0%2812.3%31.3%2812.3%135.7%52.2%62.6%167.0%10.4%4720.6% 4 74.3%74.3%2917.7%21.2%63.7%00.0%169.8%00.0%00.0%1811.0%00.0%2213.4%74.3%21.2%74.3%116.7%00.0%3018.3% 5+ 88.3%55.2%77.3%00.0%1010.4%55.2%99.4%00.0%00.0%66.3%22.1%1010.4%77.3%00.0%22.1%44.2%22.1%1919.8%

Single 218.4%104.0%4317.2%52.0%228.8%41.6%166.4%00.0%00.0%208.0%41.6%2610.4%93.6%52.0%83.2%156.0%52.0%3714.8%

Married/Partnered 194.0%143.0%4910.4%51.1%122.6%51.1%439.1%10.2%10.2%6313.4%20.4%7315.5%357.4%30.6%122.6%398.3%30.6%9119.4%

Seperated/Divorced 59.3%47.4%916.7%00.0%47.4%00.0%23.7%00.0%00.0%713.0%00.0%59.3%00.0%11.9%35.6%47.4%00.0%1018.5%

Widow/Widower 00.0%00.0%39.4%13.1%26.3%39.4%412.5%00.0%00.0%26.3%13.1%39.4%618.8%26.3%00.0%412.5%00.0%13.1%

MFQ2 00.0%00.0%38.8%00.0%411.8%12.9%411.8%00.0%00.0%38.8%00.0%25.9%823.5%12.9%00.0%514.7%00.0%38.8%

MFQ3 124.4%82.9%3111.3%31.1%62.2%41.5%248.8%00.0%10.4%3010.9%31.1%4516.4%259.1%62.2%41.5%3010.9%10.4%4115.0%

MFQ4 810.5%45.3%1013.2%11.3%810.5%33.9%22.6%00.0%00.0%1114.5%33.9%79.2%00.0%22.6%22.6%22.6%00.0%1317.1%

MFQ5 31.8%63.7%1710.4%42.4%84.9%31.8%1811.0%10.6%00.0%2213.4%10.6%1710.4%95.5%10.6%53.0%148.5%21.2%3320.1%

MFQ6 96.7%64.5%2417.9%32.2%86.0%10.7%129.0%00.0%00.0%1813.4%00.0%1712.7%53.7%00.0%43.0%21.5%21.5%2317.2% MFQ7&8 1310.5%43.2%1915.3%00.0%64.8%00.0%54.0%00.0%00.0%86.5%00.0%1915.3%32.4%10.8%86.5%97.3%32.4%2621.0% Legislators,Executives&SeniorManagers 57.2%34.3%913.0%00.0%22.9%11.4%68.7%00.0%00.0%710.1%00.0%1115.9%00.0%22.9%22.9%34.3%00.0%1826.1% Science,Eng.&OtherSpecialisedProfessionals95.9%63.9%2717.8%10.7%95.9%21.3%106.6%00.0%00.0%1811.8%10.7%2214.5%63.9%10.7%63.9%10.7%21.3%3120.4% AssociateProfessionalOccupations

56.8%22.7%1317.8%00.0%45.5%00.0%22.7%00.0%00.0%811.0%11.4%811.0%11.4%11.4%68.2%56.8%22.7%1520.5% ClericalSupportWorkers

12.2%24.4%48.9%12.2%48.9%00.0%24.4%12.2%00.0%24.4%00.0%36.7%36.7%00.0%12.2%511.1%36.7%1328.9% ServiceandSalesWorkers 57.9%00.0%46.3%11.6%11.6%00.0%711.1%00.0%00.0%1015.9%00.0%812.7%812.7%11.6%46.3%57.9%00.0%914.3% Skilledagricultural,forestryandfisheryworkers00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%150.0%150.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Craftandrelatedtradesworkers 15.0%210.0%315.0%15.0%00.0%00.0%00.0%00.0%00.0%420.0%00.0%210.0%15.0%00.0%15.0%210.0%00.0%315.0% Plantandmachineoperatorsandassemblers 00.0%00.0%16.3%00.0%16.3%16.3%16.3%00.0%00.0%212.5%00.0%318.8%16.3%00.0%16.3%212.5%00.0%318.8% Elementaryoccupations 00.0%00.0%110.0%00.0%110.0%00.0%110.0%00.0%00.0%220.0%00.0%110.0%110.0%00.0%00.0%110.0%00.0%220.0% Armedforcesoccupations 15.0%420.0%210.0%00.0%15.0%00.0%315.0%00.0%00.0%15.0%00.0%210.0%00.0%00.0%00.0%00.0%00.0%630.0% Retired/Pensioners 43.5%10.9%1210.5%10.9%21.8%43.5%1412.3%00.0%00.0%1513.2%32.6%1916.7%119.6%21.8%10.9%1210.5%00.0%1311.4% HomeCarers/NonGainfullyOccupied 00.0%43.2%86.5%00.0%54.0%10.8%1411.3%00.0%10.8%1612.9%00.0%2116.9%1512.1%21.6%00.0%2016.1%00.0%1713.7% Students 1414.3%44.1%2020.4%66.1%1010.2%33.1%55.1%00.0%00.0%66.1%11.0%77.1%33.1%22.0%11.0%66.1%11.0%99.2%

Table 6.1b - Large/Expensive Purchases (Test Statistic)

PearsonChi-SquareTests

LargePurchase

SexCode

AgeCode

LocalityCode

HouseholdSizeCode

MaritalStatusCode

LevelofEducationCode

OccupationCode

Chi-square51.283 df17

Sig. .000*,b,c Chi-square200.469 df68

Sig. .000*,b,c Chi-square103.473 df85

Sig. .084b,c Chi-square91.422 df68

Sig. .031*,b,c Chi-square107.891 df51

Sig. .000*,b,c Chi-square149.415 df85

Sig. .000*,b,c Chi-square345.065 df204

Sig. .000*,b,c

Resultsarebasedonnonemptyrowsandcolumnsineach innermostsubtable. *.TheChi-squarestatisticissignificantatthe.05level. b.Morethan20%ofcellsinthissubtablehaveexpectedcell countslessthan5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableisless thanone.Chi-squareresultsmaybeinvalid.

Q2111[A1].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Online-company websites]

Q2111[A2].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Onlinecomparison sites(thirdparty)]

Q2111[A3].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Online-reviews]

Q2111[A4].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Online-social media] Levelof

Q2111[A5].What resourcesdidyouuse whenlookingfor informationabout these products/services?

[Onlineindustry/consumer reports]

Q2111[A6].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Offline-familyand friends(wordof mouth)]

Q2111[A7].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Offline-shops, showrooms,outlet, and/orsalesreps]

YesYesYesYesYesYesYes

Occupation

SouthernHarbourDistrict 5030.1%74.2%169.6%3319.9%10.6%4828.9%4527.1%

NorthernHarbourDistrict 6629.7%73.2%2310.4%5323.9%41.8%6027.0%8036.0%

SouthEasternDistrict 2921.6%86.0%129.0%2417.9%00.0%2921.6%5742.5%

WesternDistrict 3635.3%43.9%98.8%1514.7%11.0%2827.5%3332.4%

NorthernDistrict 3423.9%85.6%1510.6%3423.9%53.5%4229.6%4833.8%

Gozo&CominoDistrict 1230.0%00.0%12.5%410.0%00.0%615.0%2050.0%

1 2326.1%44.5%78.0%1011.4%00.0%2123.9%3539.8%

2 5624.3%73.0%156.5%3013.0%73.0%5222.6%10746.5%

3 6126.8%104.4%2410.5%6126.8%10.4%7432.5%7332.0%

4 5734.8%74.3%2012.2%3722.6%10.6%4225.6%4426.8%

5+ 3031.3%66.3%1010.4%2526.0%22.1%2425.0%2425.0%

Single 8835.2%187.2%4417.6%6827.2%83.2%7530.0%7429.6%

Married/Partnered 11624.7%153.2%286.0%8217.4%30.6%11624.7%18138.5%

Seperated/Divorced 2037.0%00.0%35.6%1222.2%00.0%1324.1%1018.5%

Widow/Widower 39.4%13.1%13.1%13.1%00.0%928.1%1856.3%

MFQ2 12.9%38.8%00.0%38.8%00.0%720.6%2161.8%

MFQ3 4717.2%72.6%176.2%4616.8%00.0%6323.0%13850.4%

MFQ4 1925.0%11.3%1621.1%2836.8%00.0%2431.6%1823.7%

MFQ5 4929.9%74.3%116.7%2112.8%21.2%4426.8%4829.3%

MFQ6 5238.8%86.0%96.7%2720.1%32.2%3828.4%3324.6%

Legislators,Executives&SeniorManagers 3449.3%11.4%1318.8%2231.9%57.2%2130.4%1115.9%

Science,Eng.&OtherSpecialisedProfessionals 6744.1%127.9%1610.5%3623.7%32.0%3623.7%3321.7%

AssociateProfessionalOccupations 2838.4%34.1%912.3%2432.9%11.4%2230.1%1317.8%

ClericalSupportWorkers 1737.8%48.9%715.6%920.0%00.0%1124.4%1226.7%

ServiceandSalesWorkers 1422.2%11.6%57.9%1117.5%00.0%1625.4%2844.4% Skilledagricultural,forestryandfisheryworkers 00.0%00.0%2100.0%150.0%00.0%150.0%150.0% Craftandrelatedtradesworkers 210.0%210.0%15.0%315.0%00.0%525.0%1050.0% Plantandmachineoperatorsandassemblers 16.3%00.0%212.5%425.0%00.0%531.3%425.0% Elementaryoccupations 330.0%00.0%00.0%110.0%00.0%330.0%550.0% Armedforcesoccupations 630.0%00.0%00.0%210.0%00.0%630.0%840.0%

Table 6.2b - Information Search Dynamics for Large Purchases (Count & Row %)

Multipleresponsesadjustedto100%Q2111[A1].What resourcesdidyou usewhenlooking forinformation aboutthese products/services? [Online-company websites]

Q2111[A2].What resourcesdidyou usewhenlooking forinformation aboutthese products/services? [Onlinecomparisonsites (thirdparty)]

Q2111[A3].What resourcesdidyou usewhenlooking forinformation aboutthese products/services? [Online-reviews] Sex

Q2111[A4].What resourcesdidyou usewhenlooking forinformation aboutthese products/services? [Online-social media]

Q2111[A5].What resourcesdidyou usewhenlooking forinformation aboutthese products/services?

[Onlineindustry/consumer reports]

Q2111[A6].What resourcesdidyou usewhenlooking forinformation aboutthese products/services? [Offline-familyand friends(wordof mouth)]

Q2111[A7].What resourcesdidyou usewhenlooking forinformation aboutthese products/services? [Offline-shops, showrooms,outlet, and/orsalesreps]

YesYesYesYesYesYesYes

255100%

SouthernHarbourDistrict5025.0%73.5%168.0%3316.5%10.5%4824.0%4522.5%200100%

NorthernHarbourDistrict6622.5%72.4%237.8%5318.1%41.4%6020.5%8027.3%293100%

SouthEasternDistrict2918.2%85.0%127.5%2415.1%00.0%2918.2%5735.8%159100%

186100%

Gozo&CominoDistrict1227.9%00.0%12.3%49.3%00.0%614.0%2046.5% 43100%

12323.0%44.0%77.0%1010.0%00.0%2121.0%3535.0%100100%

25620.4%72.6%155.5%3010.9%72.6%5219.0%10739.1%274100%

36120.1%103.3%247.9%6120.1%10.3%7424.3%7324.0%304100%

45727.4%73.4%209.6%3717.8%10.5%4220.2%4421.2%208100%

5+3024.8%65.0%108.3%2520.7%21.7%2419.8%2419.8%121100%

170100%

MFQ7&85930.1%84.1%2311.7%3819.4%63.1%3718.9%2512.8%196100%

Legislators,Executives&SeniorManagers3431.8%10.9%1312.1%2220.6%54.7%2119.6%1110.3%107100%

Sc,Eng.&OtherSpecialisedProfessionals6733.0%125.9%167.9%3617.7%31.5%3617.7%3316.3%203100%

AssociateProfessionalOccupations2828.0%33.0%99.0%2424.0%11.0%2222.0%1313.0%100100%

ClericalSupportWorkers1728.3%46.7%711.7%915.0%00.0%1118.3%1220.0% 60100%

ServiceandSalesWorkers1418.7%11.3%56.7%1114.7%00.0%1621.3%2837.3% 75100%

Skilledagricultural,forestryandfishery 00.0%00.0%240.0%120.0%00.0%120.0%120.0% 5100%

Craftandrelatedtradesworkers28.7%28.7%14.3%313.0%00.0%521.7%1043.5% 23100%

Plantandmachineoperatorsand 16.3%00.0%212.5%425.0%00.0%531.3%425.0% 16100%

Elementaryoccupations325.0%00.0%00.0%18.3%00.0%325.0%541.7% 12100%

Armedforcesoccupations627.3%00.0%00.0%29.1%00.0%627.3%836.4% 22100%

Retired/Pensioners1411.7%32.5%32.5%97.5%10.8%3125.8%5949.2%120100%

HomeCarers/NonGainfullyOccupied108.1%43.3% 10.8% 97.3% 00.0%2923.6%7056.9%123100%

Students3122.0%42.8%1712.1%3222.7%10.7%2719.1%2920.6%

Table 6.2c - Information Search Dynamics for Large Purchases (Test Statistic)

PearsonChi-SquareTests

Q2111[A1].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Online-company websites] Q2111[A2].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Online-comparison sites(thirdparty)]

Q2111[A3].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Online-reviews] Q2111[A4].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Online-social media] Q2111[A5].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Onlineindustry/consumer reports] Q2111[A6].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Offline-familyand friends(wordof mouth)] Q2111[A7].What resourcesdidyouuse whenlookingfor informationabout these products/services? [Offline-shops, showrooms,outlet, and/orsalesreps]

SexCode

AgeCode

LocalityCode

HouseholdSizeCode

MaritalStatusCode

LevelofEducationCode

OccupationCode

Chi-square3.8590.68810.4120.0603.4220.0840.173 df1111111

Sig. .049 * 0.407 .001 * 0.807 .064c 0.7720.677

Chi-square38.60314.53539.73453.95311.2553.22054.683 df4444444

Sig. .000 * .006 * .000 * .000 * .024*,c 0.522 .000

Chi-square7.2804.1292.7768.0248.4565.61412.332 df5555555

Sig.0.2010.5310.7350.155 .133b,c 0.346 .031

Chi-square6.0331.8074.40120.2288.5486.44224.186 df4444444

Sig.0.197 .771c 0.354 .000 * .073c 0.169 .000

Chi-square16.6219.20028.61515.7219.2882.58018.518 df3333333

Sig. .001 * .027*,c .000 * .001 * .026*,b,c 0.461 .000

Chi-square58.3327.79633.55131.69517.2164.30964.026 df5555555

Sig. .000 * 0.168 .000 * .000 * .004*,b,c 0.506 .000

Chi-square88.58414.69157.35951.13922.5893.46980.517 df12121212121212

Sig.

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

c.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

Q2112[A1].What wasthemost importantresource youusedwhen considering options?[Onlinecompanywebsites] Q2112[A2].What wasthemost importantresource youusedwhen considering options?[Onlinecomparisonsites (thirdparty)]

YesYes

Q2112[A3].What wasthemost importantresource youusedwhen considering options?[Onlinereviews] Q2112[A4].What wasthemost importantresource youusedwhen considering options?[Onlinesocialmedia]

Q2112[A5].What wasthemost importantresource youusedwhen considering options?[Onlineindustry/consumer reports] Q2112[A6].What wasthemost importantresource youusedwhen considering options?[Offlinefamilyandfriends (wordofmouth)] Q2112[A7].What wasthemost importantresource youusedwhen considering options?[Offlineshops,showrooms, outlet,and/orsales reps]

SouthernHarbourDistrict 4225.3%42.4%127.2%2012.0%10.6%4627.7%4426.5%

NorthernHarbourDistrict 5022.5%52.3%135.9%3716.7%20.9%3917.6%7533.8%

SouthEasternDistrict 2417.9%64.5%75.2%1813.4%00.0%2518.7%5541.0%

WesternDistrict 3029.4%22.0%54.9%1110.8%11.0%2423.5%3332.4%

NorthernDistrict 2316.2%32.1%107.0%2618.3%10.7%3927.5%4028.2%

Gozo&CominoDistrict 1025.0%00.0%12.5%410.0%00.0%410.0%2050.0%

1 2022.7%11.1%11.1%89.1%00.0%2022.7%3539.8% 2 4017.4%62.6%125.2%2410.4%31.3%4720.4%10445.2% 3 4921.5%52.2%125.3%4118.0%10.4%6126.8%6227.2% 4 4326.2%42.4%1911.6%2716.5%10.6%3118.9%4225.6%

5+ 2728.1%44.2%44.2%1616.7%00.0%1818.8%2425.0%

Single 6526.0%93.6%208.0%4016.0%31.2%5522.0%6425.6%

Married/Partnered 9319.8%102.1%245.1%6614.0%20.4%10021.3%17637.4%

Seperated/Divorced 1833.3%00.0%35.6%1018.5%00.0%1324.1%1018.5%

Widow/Widower 39.4%13.1%13.1%00.0%00.0%928.1%1753.1%

MFQ2

12.9%38.8%00.0%25.9%00.0%720.6%2058.8%

MFQ7&8 4233.9%64.8%118.9%3024.2%32.4%2318.5%2016.1%

Legislators,Executives&SeniorManagers

AssociateProfessionalOccupations 2027.4%34.1%68.2%2027.4%11.4%1621.9%1115.1%

ClericalSupportWorkers 1022.2%48.9%511.1%613.3%00.0%715.6%1226.7% ServiceandSalesWorkers 1320.6%00.0%46.3%914.3%00.0%1422.2%2742.9%

Table 6.3b - Evaluation of Alternatives [Large Purchases] (Count & Row N %)

Multipleresponsesadjustedto100%Q2112[A1].What wasthemost importantresource youusedwhen considering options?[Onlinecompanywebsites] Q2112[A2].What wasthemost importantresource youusedwhen considering options?[Onlinecomparisonsites (thirdparty)]

Q2112[A4].What wasthemost importantresource youusedwhen considering options?[Onlinesocialmedia] Q2112[A3].What wasthemost importantresource youusedwhen considering options?[Onlinereviews]

Q2112[A5].What wasthemost importantresource youusedwhen considering options?[Onlineindustry/consumer reports] Q2112[A6].What wasthemost importantresource youusedwhen considering options?[Offlinefamilyandfriends (wordofmouth)]

Q2112[A7].What wasthemost importantresource youusedwhen considering options?[Offlineshops,showrooms, outlet,and/orsales reps]

YesYesYesYesYesYesYes

SouthernHarbourDistrict 4224.9%42.4%127.1%2011.8%10.6%4627.2%4426.0%

233100%

Table 6.3c - Evaluation of Alternatives [Large Purchases] (Test Statistic)

PearsonChi-SquareTests

Q2112[A1].Whatwas themostimportant resourceyouusedwhen consideringoptions?

Q2112[A2].Whatwas themostimportant resourceyouusedwhen consideringoptions?

[Online-company websites]

SexCode

AgeCode

Locality Code

Household SizeCode

Marital Status Code Levelof Education Code

Occupatio nCode

[Online-comparison sites(thirdparty)]

Q2112[A3].Whatwas themostimportant resourceyouusedwhen consideringoptions? [Online-reviews]

Q2112[A4].Whatwas themostimportant resourceyouusedwhen consideringoptions? [Online-socialmedia]

Q2112[A5].Whatwas themostimportant resourceyouusedwhen consideringoptions?

[Onlineindustry/consumer reports]

Q2112[A6].Whatwas themostimportant resourceyouusedwhen consideringoptions?

Q2112[A7].Whatwas themostimportant resourceyouusedwhen consideringoptions?

[Offline-familyand friends(wordofmouth)]

[Offline-shops, showrooms,outlet, and/orsalesreps]

Chi-square5.8153.3666.7350.2786.1090.0330.290 df1111111

Sig. .016 * 0.067 .009 * 0.598 .013*,b 0.8560.590

Chi-square26.7498.29616.74929.5327.19910.04365.193 df4444444

Sig. .000 * .081b .002 * .000 * .126b,c .040 * .000

Chi-square8.5793.4701.9675.2451.60112.55213.864 df5555555

Sig.0.127 .628b,c 0.8540.387 .901b,c .028 * .016

Chi-square6.6431.88013.8988.2903.0164.87227.601 df4444444

Sig.0.156 .758b .008 * 0.082 .555b,c 0.301 .000

Chi-square10.5942.9652.9446.6972.1890.97921.332 df3333333

Sig. .014 * .397b,c .400b 0.082 .534b,c 0.806 .000

Chi-square34.42519.71018.05920.2768.9414.04374.701 df5555555

Sig. .000 * .001*,b,c .003 * .001 * .111b,c 0.543 .000

Chi-square58.57416.18223.49238.5289.0843.93593.590 df12121212121212

Sig. .000*,b,c .183b,c .024*,b,c .000*,b,c .696b,c .985b,c .000*,c

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

MaritalStatus Code

Q2113[SQ001].Which socialmedia platformsdidyouuse togatherinformation? [Facebook]

Q2113[SQ002].Which socialmediaplatforms didyouusetogather information? [Instagram]

Q2113[SQ003].Which socialmediaplatforms didyouusetogather information?[Twitter]

Q2113[SQ005].Which socialmediaplatforms didyouusetogather information? [Pinterest]

Q2113[SQ006].Which socialmediaplatforms didyouusetogather information?[Reddit]

YesYesYesYesYes

Q2113[SQ007].Which socialmediaplatforms didyouusetogather information?[TikTok]

Q2113[SQ008].Which socialmediaplatforms didyouusetogather information?[YouTube]

YesYes

Occupation Code

NorthernHarbourDistrict 3817.1%135.9%00.0%20.9%00.0%00.0%125.4%

SouthEasternDistrict 1813.4%10.7%00.0%00.0%00.0%00.0%32.2%

WesternDistrict 109.8%32.9%00.0%00.0%11.0%00.0%43.9%

NorthernDistrict 2719.0%74.9%00.0%00.0%00.0%32.1%32.1%

Gozo&CominoDistrict 37.5%12.5%00.0%00.0%00.0%00.0%00.0%

1 78.0%00.0%00.0%00.0%00.0%00.0%33.4%

2 2611.3%20.9%00.0%00.0%00.0%20.9%41.7%

3 4118.0%93.9%00.0%00.0%00.0%00.0%167.0%

Table 6.4b - Social Media Platforms (Count & Row %)

Multipleresponsesadjustedto100%Q2113[SQ001].Which socialmediaplatforms didyouusetogather information? [Facebook]

Q2113[SQ002].Which socialmediaplatforms didyouusetogather information? [Instagram]

Q2113[SQ003].Which socialmediaplatforms didyouusetogather information?[Twitter]

Q2113[SQ005].Which socialmediaplatforms didyouusetogather information? [Pinterest]

Q2113[SQ006].Which socialmediaplatforms didyouusetogather information?[Reddit]

Q2113[SQ007].Which socialmediaplatforms didyouusetogather information?[TikTok]

Q2113[SQ008].Which socialmediaplatforms didyouusetogather information?[YouTube]

YesYesYesYesYesYesYes

HouseholdSizeCode

MaritalStatusCode

LevelofEducation Code

OccupationCode

Table 6.4c - Social Media Platforms (Test Statistic)

PearsonChi-SquareTests

Q2113[SQ001]. Whichsocialmedia platformsdidyou usetogather information? [Facebook]

Q2113[SQ002]. Whichsocialmedia platformsdidyou usetogather information? [Instagram]

Q2113[SQ003]. Whichsocialmedia platformsdidyou usetogather information? [Twitter]

SexCode

AgeCode

Locality Code

Household SizeCode

Marital Status Code

Levelof Education Code

Occupatio nCode

Q2113[SQ004].

Whichsocialmedia platformsdidyou usetogather information? [LinkedIn]

Q2113[SQ005].

Whichsocialmedia platformsdidyou usetogather information? [Pinterest]

Q2113[SQ006]. Whichsocialmedia platformsdidyou usetogather information?[Reddit]

Q2113[SQ007]. Whichsocialmedia platformsdidyou usetogather information? [TikTok]

Q2113[SQ008]. Whichsocialmedia platformsdidyou usetogather information? [YouTube]

Chi-square0.4883.5551.216-2.4351.2160.0544.437 df1111111

Sig.0.4850.059 .270b,c.119b,c .270b,c .816b .035 *

Chi-square39.95634.7405.507-9.5384.7635.01813.540 df4444444

Sig. .000 * .000 * .239b,c .049*,b,c .312b,c .285b,c .009*,b

Chi-square6.8266.9483.860-5.2746.9119.1586.206 df5555555

Sig.0.2340.225 .570b,c.383b,c .227b,c .103b,c .287b

Chi-square10.77229.1117.405-14.8283.9193.43615.720 df4444444

Sig. .029 * .000*,b .116b,c .005*,b,c .417b,c .488b,c .003*,b

Chi-square14.16017.0612.227-1.4332.2275.6951.155 df3333333

Sig. .003 * .001*,b .527b,c.698b,c .527b,c .127b,c .764b Chi-square26.51927.3161.944-10.0555.5079.94927.193 df5555555

Sig. .000 * .000 * .857b,c.074b,c .357b,c .077b,c .000*,b

Chi-square36.17331.39810.054-8.62710.05413.96819.123 df12121212121212

Sig. .000*,b,c .002*,b,c .611b,c.734b,c .611b,c .303b,c .086b,c

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

Q2121[A1].What factorsdidyou considerwhen lookingtomakeyour decision?[Personal desiresand requirements]

Q2121[A2].What factorsdidyou considerwhen lookingtomakeyour decision? [Advertisements]

Q2121[A3].What factorsdidyou considerwhen lookingtomakeyour decision?[Online researchandreviews] Levelof

Q2121[A4].What factorsdidyou considerwhen lookingtomakeyour decision?

[Recommendations fromfriendsor

YesYesYesYes

Q2121[A5].What factorsdidyou considerwhen lookingtomakeyour decision?[Product featuresandquality] SexCode

Q2121[A6].What factorsdidyou considerwhen lookingtomakeyour decision?[Brand reputationand image]

Q2121[A7].What factorsdidyou considerwhen lookingtomakeyour decision?[Priceand affordability]

Q2121[A8].What factorsdidyou considerwhen lookingtomakeyour decision?[Brand loyaltyortrust]

Yes YesYesYes

60+ 11146.3%10.4%62.5%2912.1%7732.1%156.3%6727.9%52.1%

SouthernHarbourDistrict 5432.5%127.2%1710.2%2213.3%5734.3%159.0%6036.1%148.4%

NorthernHarbourDistrict 8538.3%104.5%3214.4%3214.4%8437.8%229.9%9141.0%104.5%

SouthEasternDistrict 5440.3%32.2%1511.2%139.7%5641.8%32.2%5742.5%21.5%

WesternDistrict 4443.1%43.9%87.8%1615.7%3130.4%1615.7%3635.3%32.9%

NorthernDistrict 6545.8%64.2%1611.3%2014.1%5236.6%2517.6%6143.0%128.5%

Gozo&CominoDistrict 1640.0%12.5%12.5%615.0%1537.5%512.5%820.0%25.0%

1 4045.5%33.4%66.8%910.2%2629.5%89.1%3135.2%22.3%

2 8938.7%10.4%229.6%3213.9%7733.5%187.8%7733.5%125.2%

3 10947.8%156.6%2410.5%3615.8%8738.2%2410.5%8336.4%93.9%

4 5533.5%116.7%2716.5%2213.4%6137.2%2314.0%7646.3%127.3%

5+ 2526.0%66.3%1010.4%1010.4%4445.8%1313.5%4647.9%88.3%

Single 8634.4%2610.4%5220.8%4518.0%9638.4%2610.4%12048.0%249.6%

Married/Partnered 19140.6%91.9%316.6%5010.6%17737.7%5110.9%17136.4%163.4%

Seperated/Divorced 2851.9%11.9%35.6%916.7%1425.9%59.3%1527.8%11.9%

Widow/Widower 1340.6%00.0%39.4%515.6%825.0%412.5%721.9%26.3%

MFQ2 1852.9%00.0%00.0%25.9%926.5%38.8%411.8%12.9%

Legislators,Executives&SeniorManagers 3246.4%00.0%2130.4%1724.6%3043.5%913.0%3347.8%57.2% Science,Eng.&OtherSpecialisedProfessionals 6844.7%63.9%1711.2%2617.1%6442.1%2013.2%6442.1%63.9% AssociateProfessionalOccupations 3041.1%45.5%1013.7%79.6%2939.7%1216.4%3547.9%68.2%

ClericalSupportWorkers 1533.3%12.2%920.0%511.1%1328.9%613.3%2044.4%48.9%

Plantandmachineoperatorsandassemblers

425.0%212.5%00.0%16.3%531.3%212.5%425.0%00.0% Elementaryoccupations

Retired/Pensioners

880.0%00.0%00.0%110.0%110.0%00.0%330.0%00.0%

5548.2%00.0%10.9%97.9%3530.7%87.0%3228.1%10.9% HomeCarers/NonGainfullyOccupied

4536.3%10.8%10.8%1713.7%3830.6%64.8%3830.6%54.0%

Table 6.5b - Factors Influencing Product/Service Selection (Count & Row %)

factorsdidyou considerwhenlooking tomakeyour decision?[Personal desiresand requirements]

Q2121[A2].What factorsdidyou considerwhenlooking tomakeyour decision? [Advertisements] Household

Q2121[A3].What factorsdidyou considerwhenlooking tomakeyour decision?[Online researchandreviews]

Q2121[A4].What factorsdidyou considerwhenlooking tomakeyour decision? [Recommendations fromfriendsorfamily]

Q2121[A5].What factorsdidyou considerwhenlooking tomakeyour decision?[Product featuresandquality]

YesYesYesYesYes

Q2121[A6].What factorsdidyou considerwhenlooking tomakeyour decision?[Brand reputationandimage]

Q2121[A7].What factorsdidyou considerwhenlooking tomakeyour decision?[Priceand affordability]

Q2121[A8].What factorsdidyou considerwhenlooking tomakeyour decision?[Brand loyaltyortrust]

YesYes

Yes LocalityCode

Table 6.5c - Factors Influencing Product/Service Selection (Test Statistic)

Q2121[A1].What factorsdidyou considerwhenlooking tomakeyour decision?[Personal desiresand requirements] Q2121[A2].What factorsdidyou considerwhenlooking tomakeyour decision? [Advertisements] Q2121[A3].What factorsdidyou considerwhenlooking tomakeyour decision?[Online researchandreviews] Q2121[A4].What factorsdidyou considerwhenlooking tomakeyour decision? [Recommendations fromfriendsorfamily] Q2121[A5].What factorsdidyou considerwhenlooking tomakeyour decision?[Product featuresandquality] Q2121[A6].What factorsdidyou considerwhenlooking tomakeyour decision?[Brand reputationandimage] Q2121[A7].What factorsdidyou considerwhenlooking tomakeyour decision?[Priceand affordability] Q2121[A8].What factorsdidyou considerwhenlooking tomakeyour decision?[Brand loyaltyortrust]

SexCode

Chi-square0.0032.6401.1785.3980.4921.4000.0030.033 df11111111

Sig.0.9550.1040.278 .020* 0.4830.2370.9590.855

AgeCode

Chi-square18.57047.71148.4703.0623.34613.28123.89326.341 df44444444

Sig. .001 * .000 * .000 * 0.5480.502 .010 * .000 * .000 *

Locality Code Household SizeCode

Marital Status Code

Levelof Education Code Occupatio nCode

Chi-square6.4574.9816.7232.3563.77720.5939.24211.272 df55555555

Sig.0.2640.4180.2420.7980.582 .001 * 0.100 .046 *

Chi-square17.67514.0227.1162.6426.6444.95311.0525.494 df44444444

Sig. .001 * .007*,c 0.1300.6190.1560.292 .026 * 0.240

Chi-square6.44230.16035.4388.2065.0840.26016.68513.824 df33333333

Sig.0.092 .000*,c .000* .042* 0.1660.967 .001* .003*,c

Chi-square6.9108.94439.41621.06812.96128.40249.58040.806 df55555555

Sig.0.2270.111 .000 * .001 * .024 * .000 * .000 * .000 *

Chi-square32.37841.77081.36936.88115.59215.17519.68428.316

df1212121212121212

Sig.

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

c.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

Q2122[A1].What wasthemost importantfactor thatinformedyour decision?[Personal desiresand requirements]

Q2122[A2].What wasthemost importantfactor thatinformed yourdecision? [Advertisements]

Q2122[A3].What wasthemost importantfactor thatinformedyour decision?[Online researchand reviews]

Q2122[A4].Whatwas themostimportant factorthatinformed yourdecision? [Recommendations fromfriendsor family]

Q2122[A5].What wasthemost importantfactor thatinformedyour decision?[Product featuresand quality]

YesYesYesYes

Q2122[A6].What wasthemost importantfactor thatinformedyour decision?[Brand reputationand image]

YesYes

Q2122[A7].What wasthemost importantfactor thatinformedyour decision?[Price andaffordability]

Q2122[A8].Whatwas themostimportant factorthatinformed yourdecision?[Brand loyaltyortrust]

60+ 10142.1%00.0%52.1%229.2%6727.9%135.4%4920.4%52.1%

SouthernHarbourDistrict 5030.1%42.4%74.2%137.8%4225.3%53.0%5130.7%63.6%

NorthernHarbourDistrict 6730.2%73.2%209.0%135.9%6027.0%73.2%6931.1%41.8%

SouthEasternDistrict 4533.6%32.2%139.7%86.0%4432.8%21.5%3022.4%21.5%

WesternDistrict 3837.3%22.0%43.9%1211.8%2322.5%65.9%2120.6%11.0%

NorthernDistrict 5135.9%42.8%74.9%128.5%3826.8%117.7%4330.3%53.5%

Gozo&CominoDistrict 1640.0%00.0%12.5%615.0%1435.0%512.5%615.0%12.5%

1 3539.8%33.4%55.7%89.1%2225.0%78.0%2427.3%22.3%

2 7733.5%00.0%198.3%177.4%6829.6%125.2%5724.8%83.5%

3 9441.2%114.8%93.9%187.9%5323.2%83.5%5524.1%31.3%

4 4024.4%53.0%1710.4%148.5%4426.8%74.3%5936.0%42.4%

5+ 2121.9%11.0%22.1%77.3%3435.4%22.1%2526.0%22.1%

Single 6325.2%135.2%3012.0%156.0%6425.6%72.8%8433.6%93.6%

Married/Partnered 17036.2%61.3%173.6%408.5%14230.2%255.3%12125.7%81.7%

Seperated/Divorced 2342.6%11.9%35.6%59.3%916.7%35.6%1018.5%11.9%

Widow/Widower 1134.4%00.0%26.3%412.5%618.8%13.1%515.6%13.1%

MFQ2 1852.9%00.0%00.0%25.9%823.5%38.8%38.8%12.9%

MFQ3 8932.5%72.6%124.4%238.4%7427.0%114.0%6925.2%62.2%

MFQ4 1925.0%00.0%810.5%1013.2%1215.8%45.3%2532.9%00.0%

MFQ5 5734.8%63.7%95.5%148.5%4829.3%10.6%4326.2%21.2%

MFQ6 4936.6%21.5%107.5%118.2%4432.8%64.5%3626.9%21.5%

MFQ7&8 3528.2%54.0%1310.5%43.2%3528.2%118.9%4435.5%86.5%

Legislators,Executives&SeniorManagers 2130.4%00.0%1420.3%68.7%1826.1%45.8%1420.3%11.4%

Science,Eng.&OtherSpecialisedProfessionals

5536.2%42.6%74.6%1811.8%4428.9%106.6%4730.9%42.6% AssociateProfessionalOccupations

2534.2%11.4%56.8%22.7%2432.9%34.1%2128.8%11.4% ClericalSupportWorkers

920.0%12.2%511.1%12.2%613.3%12.2%1942.2%12.2% ServiceandSalesWorkers

2742.9%11.6%11.6%34.8%1828.6%11.6%1930.2%11.6% Skilledagricultural,forestryandfisheryworkers

Plantandmachineoperatorsandassemblers

425.0%212.5%00.0%00.0%425.0%16.3%318.8%00.0% Elementaryoccupations

880.0%00.0%00.0%110.0%110.0%00.0%220.0%00.0% Armedforcesoccupations

525.0%210.0%210.0%00.0%945.0%15.0%630.0%15.0% Retired/Pensioners

4233.9%10.8%10.8%1411.3%3427.4%54.0%2520.2%43.2%

5043.9%00.0%10.9%87.0%3228.1%54.4%2521.9%10.9% HomeCarers/NonGainfullyOccupied

Q2122[A1].What wasthemost importantfactor thatinformedyour decision?[Personal desiresand requirements] Q2122[A2].What wasthemost importantfactor thatinformed yourdecision? [Advertisements]

Q2122[A3].What wasthemost importantfactor thatinformedyour decision?[Online researchand reviews]

Q2122[A4].What wasthemost importantfactor thatinformedyour decision?

Multipleresponsesadjustedto100%Q2122[A5].What wasthemost importantfactor thatinformedyour decision?[Product featuresand quality] Q2122[A6].What wasthemost importantfactor thatinformedyour decision?[Brand reputationand image] Q2122[A7].What wasthemost importantfactor thatinformedyour decision?[Price andaffordability]

[Recommendations fromfriendsor family] HouseholdSize

YesYesYesYesYes

YesYes

Q2122[A8].What wasthemost importantfactor thatinformedyour decision?[Brand loyaltyortrust]

Table 6.6c - Most Imp. Factors Influencing Selection (Test Statistic)

PearsonChi-SquareTests

Q2122[A1].Whatwas themostimportant factorthatinformed yourdecision? [Personaldesiresand requirements]

Q2122[A2].Whatwas themostimportant factorthatinformed yourdecision? [Advertisements]

Q2122[A3].Whatwas themostimportant factorthatinformed yourdecision?[Online researchandreviews]

Q2122[A4].Whatwas themostimportant factorthatinformed yourdecision? [Recommendations fromfriendsorfamily]

Q2122[A5].Whatwas themostimportant factorthatinformed yourdecision? [Productfeaturesand quality]

Q2122[A6].Whatwas themostimportant factorthatinformed yourdecision?[Brand reputationandimage]

Q2122[A7].Whatwas themostimportant factorthatinformed yourdecision?[Price andaffordability]

Q2122[A8].Whatwas themostimportant factorthatinformed yourdecision?[Brand loyaltyortrust]

SexCode

AgeCode

LocalityCode

HouseholdSizeCode

MaritalStatusCode

LevelofEducationCode

OccupationCode

Chi-square0.0463.2591.0265.4320.6790.8830.0031.449

df11111111

Sig.0.8310.0710.311 .020 * 0.4100.3470.9550.229

Chi-square29.06024.79425.2853.4550.3421.27111.4637.335 df44444444

Sig. .000 .000*,c .000 * 0.4850.9870.866 .022 * .119c

Chi-square3.6961.6488.7866.8524.76914.60710.2093.552 df55555555

Sig.0.594 .895b,c 0.1180.2320.445 .012 * 0.070 .616b,c

Chi-square19.65912.37910.9010.3905.9014.5968.1912.369 df44444444

Sig. .001 .015*,c .028 * 0.9830.207 .331c 0.085 .668c

Chi-square11.26311.35819.0832.5356.6042.7139.8692.696 df33333333

Sig. .010 .010*,b,c .000*,c .469c 0.086 .438c .020 * .441b,c

Chi-square10.6005.51810.2056.9687.74513.11111.96112.307 df55555555

Sig.0.060 .356b,c 0.0700.2230.171 .022 * .035 * .031*,b,c

Chi-square38.12527.64052.00737.43411.8735.43116.6377.236

df1212121212121212

Sig. .000*,b .006*,b,c .000*,b,c .000*,b,c .456b .942b,c .164b .842b,c

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

c.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

StatusCode

Q2131[SQ001].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Seeingthe productsinperson]

Q2131[SQ002].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Reading productspecifications anddescriptions]

Q2131[SQ003].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Comparing productreviewsand ratingsonline]

Q2131[SQ004].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Seekingadvice fromfriends,family,or experts]

Q2131[SQ005].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Evaluatingthe company'sreputationor trackrecord]

Q2131[SQ006].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Researching thecompany'spolicies andcustomerservice]

Q2131[SQ007].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Reading testimonialsorcase studiesfromother Q2131[SQ008].Howdid youassessthedifferent product/serviceoptions tomakeyourfinal decision?[Consulting withindustry professionalsor YesYesYesYes

60+14861.7%166.7%197.9%6527.1%93.8%10.4%31.3%10.4%

SouthernHarbourDistrict7847.0%2313.9%2917.5%4627.7%84.8%21.2%74.2%10.6%

NorthernHarbourDistrict11853.2%3917.6%3716.7%5123.0%156.8%10.5%135.9%10.5%

SouthEasternDistrict7253.7%1611.9%2720.1%3929.1%10.7%00.0%10.7%21.5%

WesternDistrict5452.9%1716.7%1817.6%2423.5%43.9%22.0%11.0%43.9%

NorthernDistrict6847.9%2819.7%2517.6%3423.9%85.6%53.5%21.4%21.4%

Gozo&CominoDistrict1947.5%820.0%717.5%1230.0%00.0%00.0%00.0%00.0%

14247.7%1213.6%1719.3%1921.6%66.8%00.0%00.0%00.0%

212554.3%3816.5%3213.9%5122.2%52.2%10.4%73.0%00.0%

312253.5%4419.3%3716.2%7030.7%62.6%62.6%104.4%20.9%

47243.9%2615.9%3823.2%3923.8%116.7%31.8%31.8%63.7%

5+4850.0%1111.5%1919.8%2728.1%88.3%00.0%44.2%22.1%

Single11044.0%5823.2%6024.0%6526.0%156.0%62.4%135.2%52.0%

Married/Partnered25253.6%6113.0%7014.9%12526.6%173.6%30.6%102.1%51.1%

Seperated/Divorced2851.9%814.8%1018.5%1222.2%23.7%11.9%11.9%00.0%

Widow/Widower1959.4%412.5%39.4%412.5%26.3%00.0%00.0%00.0%

MFQ21955.9%25.9%25.9%1029.4%00.0%00.0%00.0%00.0%

MFQ316359.5%3211.7%2910.6%6323.0%114.0%31.1%72.6%31.1%

MFQ43140.8%79.2%1722.4%3039.5%33.9%45.3%00.0%00.0%

MFQ57847.6%2314.0%3219.5%3722.6%53.0%00.0%53.0%10.6%

MFQ66750.0%3123.1%2417.9%3526.1%43.0%21.5%00.0%21.5%

MFQ7&85141.1%3629.0%3931.5%3125.0%1310.5%10.8%129.7%43.2% Legislators,Executives&SeniorManagers

2942.0%1927.5%2130.4%1521.7%22.9%00.0%710.1%22.9%

Science,Eng.&OtherSpecialisedProfessionals 6140.1%3422.4%3120.4%5032.9%106.6%21.3%74.6%21.3% AssociateProfessionalOccupations

3750.7%1621.9%2027.4%1317.8%45.5%00.0%34.1%22.7% ClericalSupportWorkers1226.7%920.0%1022.2%920.0%48.9%511.1%36.7%00.0% ServiceandSalesWorkers4368.3%914.3%711.1%914.3%00.0%00.0%11.6%23.2% Skilledagricultural,forestryandfisheryworkers 2100.0%00.0%00.0%2100.0%00.0%00.0%00.0%00.0% Craftandrelatedtradesworkers 1155.0%00.0%315.0%630.0%15.0%00.0%00.0%00.0% Plantandmachineoperatorsandassemblers 743.8%00.0%318.8%425.0%00.0%00.0%00.0%16.3% Elementaryoccupations880.0%00.0%00.0%220.0%00.0%00.0%00.0%00.0% Armedforcesoccupations420.0%525.0%630.0%840.0%210.0%00.0%00.0%00.0% Retired/Pensioners7061.4%87.0%97.9%3429.8%43.5%00.0%10.9%00.0% HomeCarers/NonGainfullyOccupied

8064.5%75.6%97.3%3024.2%32.4%00.0%00.0%00.0% Students4545.9%2424.5%2424.5%2424.5%66.1%33.1%22.0%11.0%

Table 6.7b - Assessment & Final Purchase Decision (Count & Row %)

Multipleresponsesadjustedto100%

Q2131[SQ001].How didyouassessthe different product/service optionstomakeyour finaldecision?[Seeing theproductsinperson]

Q2131[SQ002].How didyouassessthe different product/service optionstomakeyour finaldecision?

[Readingproduct specificationsand descriptions]

Q2131[SQ003].How didyouassessthe different product/service optionstomakeyour finaldecision?

[Comparingproduct reviewsandratings online]

Q2131[SQ004].How didyouassessthe different product/service optionstomakeyour finaldecision?

[Seekingadvicefrom friends,family,or experts]

Q2131[SQ005].How didyouassessthe different product/service optionstomakeyour finaldecision?

[Evaluatingthe company'sreputation ortrackrecord]

YesYesYesYesYes

Q2131[SQ006].How didyouassessthe different product/service optionstomakeyour finaldecision?

[Researchingthe company'spolicies andcustomerservice]

Q2131[SQ007].How didyouassessthe different product/service optionstomakeyour finaldecision?

[Readingtestimonials orcasestudiesfrom othercustomers]

YesYes

Q2131[SQ008].How didyouassessthe different product/service optionstomakeyour finaldecision?

[Consultingwith industryprofessionals orauthorities]

Yes

60+14856.5%166.1%197.3%6524.8%93.4%10.4%31.1%10.4%262100%

SouthernHarbourDistrict7840.2%2311.9%2914.9%4623.7%84.1%21.0%73.6%10.5%194100%

NorthernHarbourDistrict11842.9%3914.2%3713.5%5118.5%155.5%10.4%134.7%10.4%275100%

SouthEasternDistrict7245.6%1610.1%2717.1%3924.7%10.6%00.0%10.6%21.3%158100%

WesternDistrict5443.5%1713.7%1814.5%2419.4%43.2%21.6%10.8%43.2%124100%

NorthernDistrict6839.5%2816.3%2514.5%3419.8%84.7%52.9%21.2%21.2%172100%

Gozo&CominoDistrict1941.3%817.4%715.2%1226.1%00.0%00.0%00.0%00.0%46100%

14243.8%1212.5%1717.7%1919.8%66.3%00.0%00.0%00.0%96100% 212548.3%3814.7%3212.4%5119.7%51.9%10.4%72.7%00.0%259100% 312241.1%4414.8%3712.5%7023.6%62.0%62.0%103.4%20.7%297100% 47236.4%2613.1%3819.2%3919.7%115.6%31.5%31.5%63.0%198100%

5+4840.3%119.2%1916.0%2722.7%86.7%00.0%43.4%21.7%119100%

Single11033.1%5817.5%6018.1%6519.6%154.5%61.8%133.9%51.5%332100% Married/Partnered25246.4%6111.2%7012.9%12523.0%173.1%30.6%101.8%50.9%543100% Seperated/Divorced2845.2%812.9%1016.1%1219.4%23.2%11.6%11.6%00.0%62100%

Widow/Widower1959.4%412.5%39.4%412.5%26.3%00.0%00.0%00.0%32100%

MFQ21957.6%26.1%26.1%1030.3%00.0%00.0%00.0%00.0%33100%

MFQ316352.4%3210.3%299.3%6320.3%113.5%31.0%72.3%31.0%311100%

MFQ43133.7%77.6%1718.5%3032.6%33.3%44.3%00.0%00.0%92100%

MFQ57843.1%2312.7%3217.7%3720.4%52.8%00.0%52.8%10.6%181100%

MFQ66740.6%3118.8%2414.5%3521.2%42.4%21.2%00.0%21.2%165100%

MFQ7&85127.3%3619.3%3920.9%3116.6%137.0%10.5%126.4%42.1%187100% Legislators,Executives&SeniorManagers2930.5%1920.0%2122.1%1515.8%22.1%00.0%77.4%22.1%95100% Science,Eng.&OtherSpecialisedProfessionals6131.0%3417.3%3115.7%5025.4%105.1%21.0%73.6%21.0%197100% AssociateProfessionalOccupations3738.9%1616.8%2021.1%1313.7%44.2%00.0%33.2%22.1%95100% ClericalSupportWorkers1223.1%917.3%1019.2%917.3%47.7%59.6%35.8%00.0%52100% ServiceandSalesWorkers4360.6%912.7%79.9%912.7%00.0%00.0%11.4%22.8%71100% Skilledagricultural,forestryandfisheryworkers250.0%00.0%00.0%250.0%00.0%00.0%00.0%00.0%4100% Craftandrelatedtradesworkers1152.4%00.0%314.3%628.6%14.8%00.0%00.0%00.0%21100% Plantandmachineoperatorsandassemblers746.7%00.0%320.0%426.7%00.0%00.0%00.0%16.7%15100% Elementaryoccupations880.0%00.0%00.0%220.0%00.0%00.0%00.0%00.0%10100% Armedforcesoccupations416.0%520.0%624.0%832.0%28.0%00.0%00.0%00.0%25100% Retired/Pensioners7055.6%86.3%97.1%3427.0%43.2%00.0%10.8%00.0%126100% HomeCarers/NonGainfullyOccupied8062.0%75.4%97.0%3023.3%32.3%00.0%00.0%00.0%129100% Students4534.9%2418.6%2418.6%2418.6%64.7%32.3%21.6%10.8%129100%

Table 6.7c - Assessment & Final Purchase Decision (Test Statistic)

Q2131[SQ001].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision?[Seeing theproductsinperson]

Q2131[SQ002].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision?[Reading productspecificationsand descriptions]

Q2131[SQ003].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision? [Comparingproductreviewsand ratingsonline]

Q2131[SQ004].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision?[Seeking advicefromfriends,family,orexperts]

Q2131[SQ005].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision? [Evaluatingthecompany'sreputation ortrackrecord]

Q2131[SQ006].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision? [Researchingthecompany'spolicies andcustomerservice]

Q2131[SQ007].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision?[Reading testimonialsorcasestudiesfromother customers]

Q2131[SQ008].Howdidyouassess thedifferentproduct/serviceoptions tomakeyourfinaldecision? [Consultingwithindustryprofessionals orauthorities]

SexCode

AgeCode

LocalityCode

HouseholdSizeCode

MaritalStatusCode

LevelofEducationCode

OccupationCode

Chisquare 1.19110.4364.4760.4280.1862.5220.0052.522

df11111111

Sig.0.275 .001 .034 0.5130.666 .112 0.946 .112c Chisquare 19.84037.34223.8580.6108.0698.02711.4384.533

df44444444

Sig. .001 .000 .000 0.9620.089 .091 .022*,c .339c

Chisquare 2.7604.4920.7202.9009.5189.77713.4048.271

df55555555

Sig.0.7370.4810.9820.7150.090 .082b,c .020*,c .142b,c

Chisquare 5.3053.6496.4075.88811.0677.5945.48812.622

df44444444

Sig.0.2570.4560.1710.208 .026*,c .108 .241 .013*,c

Chisquare 7.08212.97910.8793.4752.4854.7016.6682.377

df33333333

Sig.0.069 .005 .012 0.324 .478c .195b,c .083b,c .498b,c Chisquare 17.03729.80530.3359.76513.75312.83126.9276.020

df55555555

Sig. .004 .000 .000 0.082 .017 .025*,b,c .000*,c .304b,c Chisquare 56.00345.71340.26221.73312.02144.85724.45912.340

df1212121212121212

Sig. .000

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

c.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

Table 6.8a - Frequent Purchase Groups (Count & Row %)

SouthernHarbourDistrict 00.0%31.8%42.4%63.6%31.8%2816.9%3722.3%00.0%

NorthernHarbourDistrict 31.4%00.0%52.3%41.8%62.7%3013.5%5725.7%00.0%

SouthEasternDistrict32.2%00.0%32.2%10.7%139.7%107.5%3626.9%00.0%

WesternDistrict00.0%00.0%22.0%11.0%54.9%1312.7%1817.6%11.0% NorthernDistrict10.7%00.0%10.7%42.8%107.0%149.9%3222.5%00.0%

Gozo&CominoDistrict 00.0%00.0%00.0%00.0%410.0%717.5%1025.0%00.0%

100.0%00.0%00.0%11.1%33.4%1415.9%2326.1%00.0% 241.7%00.0%41.7%41.7%83.5%3113.5%5122.2%10.4% 310.4%00.0%83.5%62.6%167.0%229.6%5725.0%00.0% 421.2%31.8%21.2%42.4%84.9%2817.1%3320.1%00.0% 5+00.0%00.0%11.0%11.0%66.3%77.3%2627.1%00.0% Single31.2%31.2%114.4%145.6%166.4%2610.4%4317.2%00.0% Married/Partnered40.9%00.0%40.9%20.4%245.1%6113.0%12526.6%10.2% Seperated/Divorced00.0%00.0%00.0%00.0%11.9%1120.4%1324.1%00.0% Widow/Widower00.0%00.0%00.0%00.0%00.0%412.5%928.1%00.0%

MFQ200.0%00.0%00.0%00.0%25.9%514.7%617.6%00.0%

MFQ300.0%00.0%72.6%72.6%72.6%2910.6%7326.6%00.0%

MFQ445.3%00.0%33.9%45.3%810.5%56.6%1114.5%00.0%

MFQ510.6%00.0%00.0%21.2%21.2%1911.6%4628.0%00.0%

MFQ600.0%00.0%21.5%00.0%118.2%2216.4%3425.4%10.7%

MFQ7&821.6%32.4%32.4%32.4%118.9%2217.7%2016.1%00.0% Legislators,Executives&Senior 22.9%00.0%00.0%11.4%22.9%1217.4%1623.2%11.4% Science,Eng.&OtherSpecialised 10.7%00.0%32.0%10.7%106.6%2013.2%4630.3%00.0% AssociateProfessionalOccupations 00.0%11.4%34.1%22.7%79.6%1317.8%1115.1%00.0% ClericalSupportWorkers 00.0%00.0%36.7%12.2%00.0%715.6%920.0%00.0% ServiceandSalesWorkers 11.6%00.0%00.0%00.0%11.6%914.3%1727.0%00.0% Skilledagricultural,forestryandfishery

00.0%00.0%00.0%00.0%150.0%00.0%00.0%00.0% Craftandrelatedtradesworkers 00.0%00.0%15.0%15.0%00.0%210.0%630.0%00.0% Plantandmachineoperatorsand 00.0%00.0%00.0%00.0%00.0%212.5%531.3%00.0% Elementaryoccupations 00.0%00.0%00.0%00.0%00.0%220.0%330.0%00.0% Armedforcesoccupations

00.0%00.0%00.0%00.0%15.0%315.0%735.0%00.0% Retired/Pensioners10.9%00.0%00.0%10.9%21.8%119.6%3530.7%00.0% HomeCarers/NonGainfullyOccupied

00.0%00.0%00.0%00.0%43.2%1512.1%2419.4%00.0% Students22.0%22.0%55.1%99.2%1313.3%66.1%1111.2%00.0%

Table 6.8b - Frequent Purchase Groups (Test Statistic)

Resultsarebasedonnonemptyrowsandcolumnsineachinnermost subtable. *.TheChi-squarestatisticissignificantatthe.05level.

b.Morethan20%ofcellsinthissubtablehaveexpectedcellcountsless than5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableislessthanone.Chisquareresultsmaybeinvalid.

Female 101.1%151.7%546.1%70.8%546.1%566.3%14316.2%00.0%10.1%10.1%728.1%182.0%657.4%15317.3%222.5%101.1%10211.5%131.5%8810.0% 18to29 216.6%103.2%4213.3%196.0%3711.7%175.4%247.6%00.0%00.0%00.0%247.6%61.9%144.4%123.8%61.9%20.6%3410.8%288.9%206.3%

30to39 103.6%62.1%227.9%20.7%145.0%227.9%5017.9%00.0%00.0%00.0%279.6%41.4%155.4%3813.6%103.6%145.0%93.2%00.0%3713.2%

40to49 83.2%93.6%176.9%10.4%104.0%208.1%3815.3%00.0%10.4%00.0%2811.3%41.6%176.9%3915.7%10.4%52.0%197.7%20.8%2911.7% 50to59 62.1%31.0%165.6%31.0%62.1%227.6%5218.1%10.3%00.0%10.3%3211.1%31.0%248.3%5719.8%10.3%20.7%289.7%20.7%2910.1% 60+71.5%30.6%224.6%20.4%142.9%336.9%9119.0%00.0%00.0%00.0%387.9%30.6%408.3%11524.0%81.7%20.4%6513.5%30.6%347.1% SouthernHarbourDistrict 144.2%61.8%288.4%123.6%103.0%309.0%4714.2%00.0%00.0%00.0%319.3%51.5%247.2%5115.4%20.6%41.2%3711.1%30.9%288.4% NorthernHarbourDistrict 163.6%112.5%368.1%51.1%143.2%337.4%7216.2%00.0%00.0%00.0%306.8%61.4%276.1%7917.8%81.8%92.0%419.2%143.2%439.7% SouthEasternDistrict 93.4%10.4%186.7%10.4%238.6%166.0%5420.1%00.0%00.0%00.0%3111.6%31.1%186.7%4416.4%41.5%41.5%228.2%20.7%186.7% WesternDistrict 73.4%31.5%188.8%52.5%125.9%136.4%2311.3%10.5%10.5%00.0%199.3%21.0%136.4%2713.2%31.5%31.5%2512.3%94.4%209.8% NorthernDistrict 62.1%103.5%155.3%41.4%176.0%155.3%4415.5%00.0%00.0%10.4%3010.6%10.4%186.3%4716.5%82.8%31.1%279.5%72.5%3110.9% Gozo&CominoDistrict 00.0%00.0%45.0%00.0%56.3%78.8%1518.8%00.0%00.0%00.0%810.0%33.8%1012.5%1316.3%11.3%22.5%33.8%00.0%911.3% 131.7%10.6%1910.8%10.6%84.5%158.5%3117.6%00.0%00.0%00.0%126.8%21.1%169.1%3419.3%21.1%31.7%179.7%52.8%74.0% 2173.7%81.7%265.7%61.3%132.8%347.4%7416.1%10.2%10.2%10.2%5010.9%40.9%327.0%7616.5%61.3%51.1%5912.8%92.0%388.3% 3153.3%71.5%357.7%132.9%306.6%255.5%6614.5%00.0%00.0%00.0%429.2%51.1%306.6%7115.6%132.9%81.8%367.9%102.2%5011.0% 492.7%103.0%319.5%61.8%144.3%288.5%4914.9%00.0%00.0%00.0%298.8%51.5%226.7%4914.9%41.2%72.1%309.1%00.0%3510.7% 5+84.2%52.6%84.2%10.5%168.3%126.3%3518.2%00.0%00.0%00.0%168.3%42.1%105.2%3116.1%10.5%21.0%136.8%115.7%199.9% Single 244.8%132.6%5410.8%193.8%387.6%306.0%5911.8%00.0%00.0%00.0%438.6%81.6%265.2%469.2%132.6%81.6%5110.2%244.8%448.8% Married/Partnered 232.4%141.5%535.6%70.7%363.8%667.0%16817.9%10.1%10.1%10.1%899.5%91.0%768.1%18319.5%91.0%141.5%869.1%111.2%939.9% Seperated/Divorced 54.6%43.7%98.3%00.0%54.6%1110.2%1513.9%00.0%00.0%00.0%1211.1%21.9%54.6%1513.9%21.9%32.8%98.3%00.0%1110.2% Widow/Widower 00.0%00.0%34.7%11.6%23.1%710.9%1320.3%00.0%00.0%00.0%57.8%11.6%34.7%1726.6%23.1%00.0%914.1%00.0%11.6% MFQ2 00.0%00.0%34.4%00.0%68.8%68.8%1014.7%00.0%00.0%00.0%45.9%11.5%22.9%1826.5%22.9%00.0%1319.1%00.0%34.4%

MFQ3 122.2%81.5%386.9%101.8%132.4%336.0%9717.7%00.0%00.0%10.2%498.9%50.9%478.6%11220.4%112.0%40.7%6010.9%40.7%448.0%

MFQ4 127.9%42.6%138.6%53.3%1610.5%85.3%138.6%00.0%00.0%00.0%1711.2%63.9%74.6%138.6%32.0%21.3%159.9%53.3%138.6%

MFQ5 41.2%61.8%175.2%61.8%103.0%226.7%6419.5%00.0%10.3%00.0%3510.7%72.1%185.5%5516.8%20.6%51.5%3310.1%92.7%3410.4%

MFQ6 93.4%62.2%269.7%31.1%197.1%238.6%4617.2%10.4%00.0%00.0%3011.2%10.4%176.3%4115.3%41.5%41.5%72.6%83.0%238.6%

MFQ7&8 156.0%72.8%228.9%31.2%176.9%228.9%2510.1%00.0%00.0%00.0%145.6%00.0%197.7%228.9%41.6%104.0%2710.9%93.6%3212.9% Legislators,Executives&SeniorManagers75.1%32.2%96.5%10.7%42.9%139.4%2215.9%10.7%00.0%00.0%128.7%00.0%118.0%1611.6%53.6%21.4%107.2%10.7%2115.2% Science,Eng.&OtherSpecialised Professionals 103.3%62.0%309.9%20.7%196.3%227.2%5618.4%00.0%00.0%00.0%278.9%41.3%227.2%4514.8%20.7%62.0%134.3%72.3%3310.9% AssociateProfessionalOccupations

53.4%32.1%1611.0%21.4%117.5%138.9%138.9%00.0%00.0%00.0%138.9%32.1%85.5%1611.0%21.4%85.5%106.8%53.4%1812.3% ClericalSupportWorkers 11.1%22.2%77.8%22.2%44.4%77.8%1112.2%00.0%11.1%00.0%44.4%44.4%33.3%1213.3%22.2%11.1%1011.1%66.7%1314.4% ServiceandSalesWorkers 64.8%00.0%43.2%10.8%21.6%97.1%2419.0%00.0%00.0%00.0%1612.7%00.0%97.1%2822.2%21.6%43.2%129.5%00.0%97.1% Skilledagricultural,forestryandfishery workers 00.0%00.0%00.0%00.0%125.0%00.0%00.0%00.0%00.0%00.0%125.0%125.0%00.0%00.0%00.0%00.0%00.0%00.0%125.0%

Craftandrelatedtradesworkers 12.5%25.0%410.0%25.0%00.0%25.0%615.0%00.0%00.0%00.0%615.0%00.0%25.0%820.0%00.0%12.5%37.5%00.0%37.5% Plantandmachineoperatorsand assemblers 00.0%00.0%13.1%00.0%13.1%39.4%618.8%00.0%00.0%00.0%39.4%00.0%412.5%618.8%13.1%13.1%39.4%00.0%39.4% Elementaryoccupations 00.0%00.0%15.0%00.0%15.0%210.0%420.0%00.0%00.0%00.0%210.0%00.0%15.0%420.0%00.0%00.0%210.0%15.0%210.0% Armedforcesoccupations 12.5%410.0%25.0%00.0%25.0%37.5%1025.0%00.0%00.0%00.0%25.0%00.0%25.0%820.0%00.0%00.0%00.0%00.0%615.0% Retired/Pensioners 52.2%10.4%125.3%20.9%41.8%156.6%4921.5%00.0%00.0%00.0%219.2%31.3%198.3%5323.2%31.3%10.4%2611.4%10.4%135.7% HomeCarers/NonGainfullyOccupied 00.0%41.6%83.2%00.0%93.6%166.5%3815.3%00.0%00.0%10.4%2610.5%20.8%228.9%5522.2%62.4%00.0%4417.7%00.0%176.9% Students 168.2%63.1%2512.8%157.7%2311.7%94.6%168.2%00.0%00.0%00.0%168.2%31.5%73.6%105.1%31.5%10.5%2211.2%147.1%105.1% [Vacation,

Table 6.9b - Aggregated Market Category Data (Test Statistic)

SexCode

AgeCode

LargePurchaseFrequentPurchase Chisquare 51.28353.395 df1716

Sig. .000*,b,c .000*,b,c Chisquare 200.469284.597 df6864

LocalityCode

HouseholdSizeCode

MaritalStatusCode

Sig. .000*,b,c .000*,b,c Chisquare 103.473106.662 df8580

Sig. .084b,c .025*,b,c Chisquare 91.42288.472 df6864

Sig. .031*,b,c .023*,b,c Chisquare 107.891121.939 df5148

LevelofEducationCode

Sig. .000*,b,c .000*,b,c Chi-149.415175.242 df8580

OccupationCode

Sig. .000*,b,c .000*,b,c Chisquare 345.065359.548

df204192

Resultsarebasedonnonemptyrowsandcolumnsineach innermostsubtable. *.TheChi-squarestatisticissignificantatthe.05level. b.Morethan20%ofcellsinthissubtablehaveexpectedcell countslessthan5.Chi-squareresultsmaybe c.invalid. Theminimumexpectedcellcountinthissubtableislessthan one.Chi-squareresultsmaybeinvalid.

Table 6.10a - Advertisements or Promotions (Count & Row %)

Table 6.10b - Advertisements or Promotions (Test Statistic)

Q2142[SQ001].

Wheredoyourecall seeingadsbefore yourpurchase? [Television commercials]

Q2142[SQ002].

Wheredoyourecall seeingadsbefore yourpurchase? [Radio advertisements]

Q2142[SQ003].

Wheredoyourecall seeingadsbefore yourpurchase? [Onlinebannerads]

Q2142[SQ004].

Wheredoyourecall seeingadsbefore yourpurchase?

Q2142[SQ005].

Wheredoyourecall seeingadsbefore yourpurchase?

[Socialmedia advertisements(e.g., Facebook, Instagram)]

[Sponsoredcontent onwebsitesorblogs]

Q2142[SQ006].

Wheredoyourecall seeingadsbefore yourpurchase? [Emailmarketing campaigns]

Q2142[SQ007].

Wheredoyourecall seeingadsbefore yourpurchase? [Searchengine advertisements(e.g., GoogleAds)]

Q2142[SQ008].

Wheredoyourecall seeingadsbefore yourpurchase?[Print advertisements(e.g., newspapers, magazines)]

Q2142[SQ009].

Wheredoyourecall seeingadsbefore yourpurchase? [Outdooradvertising (e.g.,billboards, posters)]

Q2142[SQ010].

Wheredoyourecall seeingadsbefore yourpurchase? [Mobileapp advertisements]

Q2142[SQ011].

Wheredoyourecall seeingadsbefore yourpurchase? [Influencermarketing onsocialmedia platforms]

YesYesYesYes

Q2142[SQ012].

Wheredoyourecall seeingadsbefore yourpurchase?

Q2142[SQ013].

Wheredoyourecall seeingadsbefore yourpurchase?

Q2142[SQ014].

[Productplacements inmoviesorTV shows]

[Directmail advertisements]

Wheredoyourecall seeingadsbefore yourpurchase? [Eventsor sponsorships]

Q2142[SQ015].

Wheredoyourecall seeingadsbefore yourpurchase?[Instoredisplaysor promotions]

YesYesYesYesYes

YesYesYesYes

YesYes

30to39 42.9%00.0%96.4%2517.9%107.1%10.7%10.7%42.9%21.4%32.1%10.7%00.0%21.4%21.4%10.7% 40to49 54.0%43.2%32.4%2116.9%32.4%21.6%10.8%00.0%10.8%10.8%00.0%00.0%10.8%00.0%10.8%

50to59 106.9%10.7%21.4%3121.5%21.4%10.7%00.0%64.2%21.4%32.1%10.7%00.0%53.5%00.0%00.0%

60+ 2711.3%31.3%00.0%239.6%20.8%10.4%52.1%52.1%41.7%10.4%00.0%00.0%156.3%00.0%10.4% SouthernHarbourDistrict 84.8%31.8%31.8%3420.5%84.8%10.6%10.6%42.4%10.6%42.4%21.2%00.0%84.8%63.6%10.6% NorthernHarbourDistrict 146.3%20.9%125.4%3716.7%52.3%10.5%31.4%94.1%62.7%104.5%62.7%00.0%41.8%20.9%00.0% SouthEasternDistrict 118.2%00.0%00.0%2317.2%75.2%21.5%21.5%00.0%10.7%10.7%00.0%00.0%10.7%00.0%00.0% WesternDistrict 65.9%11.0%22.0%2019.6%11.0%00.0%00.0%11.0%11.0%22.0%00.0%00.0%22.0%00.0%11.0% NorthernDistrict 1712.0%21.4%32.1%2215.5%53.5%00.0%10.7%10.7%64.2%00.0%00.0%00.0%53.5%00.0%10.7% Gozo&CominoDistrict 00.0%00.0%00.0%820.0%00.0%12.5%00.0%00.0%00.0%00.0%00.0%00.0%37.5%00.0%00.0% 189.1%00.0%00.0%1011.4%11.1%00.0%00.0%11.1%00.0%00.0%00.0%00.0%11.1%00.0%00.0% 2177.4%20.9%31.3%3414.8%41.7%20.9%62.6%73.0%73.0%83.5%20.9%00.0%135.7%20.9%20.9% 3104.4%41.8%104.4%3515.4%62.6%00.0%00.0%52.2%62.6%31.3%10.4%00.0%41.8%00.0%10.4% 4137.9%21.2%31.8%3722.6%63.7%21.2%00.0%21.2%21.2%53.0%10.6%00.0%21.2%00.0%00.0% 5+88.3%00.0%44.2%2829.2%99.4%11.0%11.0%00.0%00.0%11.0%44.2%00.0%33.1%66.3%00.0%

Single 145.6%00.0%135.2%5120.4%187.2%00.0%20.8%52.0%62.4%135.2%20.8%00.0%10.4%83.2%10.4%

Married/Partnered 388.1%71.5%30.6%8017.0%81.7%40.9%40.9%71.5%81.7%40.9%51.1%00.0%194.0%00.0%10.2%

Seperated/Divorced 23.7%11.9%23.7%916.7%00.0%11.9%00.0%11.9%11.9%00.0%11.9%00.0%23.7%00.0%11.9%

Widow/Widower 26.3%00.0%26.3%412.5%00.0%00.0%13.1%26.3%00.0%00.0%00.0%00.0%13.1%00.0%00.0%

MFQ2 514.7%00.0%00.0%38.8%00.0%00.0%12.9%00.0%00.0%00.0%00.0%00.0%411.8%00.0%00.0%

MFQ3 207.3%51.8%51.8%3813.9%93.3%10.4%10.4%51.8%51.8%31.1%00.0%00.0%134.7%00.0%00.0%

MFQ4 45.3%11.3%67.9%1925.0%11.3%11.3%00.0%22.6%22.6%00.0%00.0%00.0%11.3%00.0%11.3%

MFQ5 116.7%21.2%21.2%2515.2%31.8%21.2%10.6%10.6%31.8%00.0%53.0%00.0%42.4%00.0%21.2%

MFQ6 139.7%00.0%21.5%2014.9%53.7%10.7%10.7%43.0%10.7%21.5%00.0%00.0%10.7%00.0%00.0%

Occupation Code

MFQ7&8 32.4%00.0%54.0%3931.5%86.5%00.0%32.4%32.4%43.2%129.7%32.4%00.0%00.0%86.5%00.0% Legislators,Executives&SeniorManagers00.0%11.4%68.7%1826.1%45.8%00.0%11.4%45.8%11.4%34.3%22.9%00.0%22.9%22.9%00.0% Science,Eng.&OtherSpecialised 74.6%00.0%42.6%3523.0%85.3%10.7%32.0%10.7%32.0%21.3%10.7%00.0%21.3%21.3%10.7% AssociateProfessionalOccupations 45.5%00.0%34.1%1419.2%22.7%00.0%00.0%22.7%34.1%68.2%11.4%00.0%11.4%00.0%11.4% ClericalSupportWorkers 12.2%00.0%48.9%1635.6%36.7%00.0%00.0%24.4%00.0%00.0%36.7%00.0%00.0%00.0%00.0% ServiceandSalesWorkers 711.1%11.6%00.0%69.5%11.6%00.0%00.0%11.6%23.2%11.6%00.0%00.0%11.6%00.0%00.0% Skilledagricultural,forestryandfishery 00.0%00.0%150.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Craftandrelatedtradesworkers 00.0%210.0%00.0%15.0%15.0%15.0%00.0%00.0%00.0%15.0%00.0%00.0%15.0%00.0%00.0%

Elementaryoccupations 110.0%00.0%00.0%110.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%

Table 6.11b - Recall of Ads & Advertising Channel Effectiveness (Count & Row %)

Multipleresponsesadjustedto100%

Q2142[SQ001].

Wheredoyourecall seeingadsbefore yourpurchase? [Television commercials]

Q2142[SQ002].

Wheredoyourecall seeingadsbefore yourpurchase? [Radio advertisements]

Q2142[SQ003].

Wheredoyourecall seeingadsbefore yourpurchase? [Onlinebannerads] Locality

Q2142[SQ004].

Wheredoyourecall seeingadsbefore yourpurchase?

[Socialmedia advertisements(e.g., Facebook, Instagram)]

Q2142[SQ005].

Wheredoyourecall seeingadsbefore yourpurchase?

Q2142[SQ006].

Wheredoyourecall seeingadsbefore yourpurchase?

[Sponsoredcontent onwebsitesorblogs]

[Emailmarketing campaigns]

Q2142[SQ007].

Wheredoyourecall seeingadsbefore yourpurchase?

[Searchengine advertisements(e.g., GoogleAds)]

Q2142[SQ008].

Wheredoyourecall seeingadsbefore yourpurchase?[Print advertisements(e.g., newspapers, magazines)]

Q2142[SQ009].

Wheredoyourecall seeingadsbefore yourpurchase?

Q2142[SQ010].

Wheredoyourecall seeingadsbefore yourpurchase?

Q2142[SQ011].

[Outdooradvertising (e.g.,billboards, posters)]

[Mobileapp advertisements]

Wheredoyourecall seeingadsbefore yourpurchase? [Influencermarketing onsocialmedia platforms]

YesYesYesYesYesYesYesYesYes

YesYes

Q2142[SQ012].

Wheredoyourecall seeingadsbefore yourpurchase?

Q2142[SQ013].

Wheredoyourecall seeingadsbefore yourpurchase?

[Productplacements inmoviesorTV shows]

[Directmail advertisements]

Q2142[SQ014].

Wheredoyourecall seeingadsbefore yourpurchase? [Eventsor sponsorships]

Q2142[SQ015].

Wheredoyourecall seeingadsbefore yourpurchase?[Instoredisplaysor promotions]

YesYesYesYes

% Male2316.2%53.5%42.8%4632.4%107.0%21.4%32.1%85.6%117.7%149.9%00.0%00.0%64.2%85.6%21.4%142100% Female3315.5%31.4%167.5%9846.0%167.5%31.4%41.9%73.3%41.9%31.4%83.8%00.0%178.0%00.0%10.5%213100% 18to291010.4%00.0%66.3%4445.8%99.4%00.0%00.0%00.0%66.3%99.4%66.3%00.0%00.0%66.3%00.0%96100% 30to3946.2%00.0%913.8%2538.5%1015.4%11.5%11.5%46.2%23.1%34.6%11.5%00.0%23.1%23.1%11.5%65100% 40to49511.6%49.3%37.0%2148.8%37.0%24.7%12.3%00.0%12.3%12.3%00.0%00.0%12.3%00.0%12.3%43100% 50to591015.6%11.6%23.1%3148.4%23.1%11.6%00.0%69.4%23.1%34.7%11.6%00.0%57.8%00.0%00.0%64100% 60+2731.0%33.4%00.0%2326.4%22.3%11.1%55.7%55.7%44.6%11.1%00.0%00.0%1517.2%00.0%11.1%87100% SouthernHarbourDistrict89.5%33.6%33.6%3440.5%89.5%11.2%11.2%44.8%11.2%44.8%22.4%00.0%89.5%67.1%11.2%84100% NorthernHarbourDistrict1412.6%21.8%1210.8%3733.3%54.5%10.9%32.7%98.1%65.4%109.0%65.4%00.0%43.6%21.8%00.0%111100% SouthEasternDistrict1122.9%00.0%00.0%2347.9%714.6%24.2%24.2%00.0%12.1%12.1%00.0%00.0%12.1%00.0%00.0%48100% WesternDistrict616.2%12.7%25.4%2054.1%12.7%00.0%00.0%12.7%12.7%25.4%00.0%00.0%25.4%00.0%12.7%37100% NorthernDistrict1727.0%23.2%34.8%2234.9%57.9%00.0%11.6%11.6%69.5%00.0%00.0%00.0%57.9%00.0%11.6%63100% Gozo&CominoDistrict00.0%00.0%00.0%866.7%00.0%18.3%00.0%00.0%00.0%00.0%00.0%00.0%325.0%00.0%00.0%12100% 1838.1%00.0%00.0%1047.6%14.8%00.0%00.0%14.8%00.0%00.0%00.0%00.0%14.8%00.0%00.0%21100% 21715.6%21.8%32.8%3431.2%43.7%21.8%65.5%76.4%76.4%87.3%21.8%00.0%1311.9%21.8%21.8%109100% 31011.8%44.7%1011.8%3541.2%67.1%00.0%00.0%55.9%67.1%33.5%11.2%00.0%44.7%00.0%11.2%85100% 41317.3%22.7%34.0%3749.3%68.0%22.7%00.0%22.7%22.7%56.7%11.3%00.0%22.7%00.0%00.0%75100% 5+812.3%00.0%46.2%2843.1%913.8%11.5%11.5%00.0%00.0%11.5%46.2%00.0%34.6%69.2%00.0%65100% Single1410.4%00.0%139.7%5138.1%1813.4%00.0%21.5%53.7%64.5%139.7%21.5%00.0%10.7%86.0%10.7%134100% Married/Partnered3820.2%73.7%31.6%8042.6%84.3%42.1%42.1%73.7%84.3%42.1%52.7%00.0%1910.1%00.0%10.5%188100% Seperated/Divorced29.5%14.8%29.5%942.9%00.0%14.8%00.0%14.8%14.8%00.0%14.8%00.0%29.5%00.0%14.8%21100% Widow/Widower216.7%00.0%216.7%433.3%00.0%00.0%18.3%216.7%00.0%00.0%00.0%00.0%18.3%00.0%00.0%12100% MFQ2538.5%00.0%00.0%323.1%00.0%00.0%17.7%00.0%00.0%00.0%00.0%00.0%430.8%00.0%00.0%13100%

MFQ32019.0%54.8%54.8%3836.2%98.6%11.0%11.0%54.8%54.8%32.9%00.0%00.0%1312.4%00.0%00.0%105100% MFQ4410.5%12.6%615.8%1950.0%12.6%12.6%00.0%25.3%25.3%00.0%00.0%00.0%12.6%00.0%12.6%38100% MFQ51118.0%23.3%23.3%2541.0%34.9%23.3%11.6%11.6%34.9%00.0%58.2%00.0%46.6%00.0%23.3%61100% MFQ61326.0%00.0%24.0%2040.0%510.0%12.0%12.0%48.0%12.0%24.0%00.0%00.0%12.0%00.0%00.0%50100% MFQ7&833.4%00.0%55.7%3944.3%89.1%00.0%33.4%33.4%44.5%1213.6%33.4%00.0%00.0%89.1%00.0%88100% Legislators,Executives&Senior 00.0%12.3%613.6%1840.9%49.1%00.0%12.3%49.1%12.3%36.8%24.5%00.0%24.5%24.5%00.0%44100% Science,Eng.&OtherSpecialised 710.0%00.0%45.7%3550.0%811.4%11.4%34.3%11.4%34.3%22.9%11.4%00.0%22.9%22.9%11.4%70100% AssociateProfessionalOccupations410.8%00.0%38.1%1437.8%25.4%00.0%00.0%25.4%38.1%616.2%12.7%00.0%12.7%00.0%12.7%37100% ClericalSupportWorkers13.4%00.0%413.8%1655.2%310.3%00.0%00.0%26.9%00.0%00.0%310.3%00.0%00.0%00.0%00.0%29100% ServiceandSalesWorkers735.0%15.0%00.0%630.0%15.0%00.0%00.0%15.0%210.0%15.0%00.0%00.0%15.0%00.0%00.0%20100% Skilledagricultural,forestryandfishery00.0%00.0%1100.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%1100% Craftandrelatedtradesworkers00.0%228.6%00.0%114.3%114.3%114.3%00.0%00.0%00.0%114.3%00.0%00.0%114.3%00.0%00.0%7100% Plantandmachineoperatorsand 330.0%220.0%00.0%220.0%110.0%00.0%00.0%00.0%220.0%00.0%00.0%00.0%00.0%00.0%00.0%10100% Elementaryoccupations150.0%00.0%00.0%150.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%2100% Armedforcesoccupations114.3%00.0%00.0%457.1%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%114.3%00.0%114.3%7100% Retired/Pensioners1233.3%12.8%00.0%1027.8%12.8%12.8%25.6%513.9%00.0%00.0%00.0%00.0%411.1%00.0%00.0%36100% HomeCarers/NonGainfullyOccupied1328.9%12.2%00.0%1533.3%12.2%24.4%12.2%00.0%12.2%00.0%00.0%00.0%1124.4%00.0%00.0%45100% Students714.9%00.0%24.3%2246.8%48.5%00.0%00.0%00.0%36.4%48.5%12.1%00.0%00.0%48.5%00.0%47100%

Table 6.11c - Recall of Ads & Advertising Channel Effectiveness (Test Statistic)

Q2142[SQ00 1].Wheredo yourecall seeingads beforeyour purchase?

[Television commercials]

Q2142[SQ002]. Wheredoyou recallseeingads beforeyour purchase?

[Radio advertisements]

Q2142[SQ00 3].Wheredo yourecall seeingads beforeyour purchase?

[Online bannerads]

Q2142[SQ00 4].Wheredo yourecall seeingads beforeyour purchase?

[Socialmedia advertisemen ts(e.g., Facebook, Instagram)]

Q2142[SQ00 5].Wheredo yourecall seeingads beforeyour purchase?

[Sponsored contenton websitesor blogs]

Q2142[SQ00 6].Wheredo yourecall seeingads beforeyour purchase?

[Email marketing campaigns]

Q2142[SQ00 7].Wheredo yourecall seeingads beforeyour purchase?

[Search engine advertisemen ts(e.g., GoogleAds)]

Q2142[SQ00 8].Wheredo yourecall seeingads beforeyour purchase?

[Print advertisemen ts(e.g., newspapers, magazines)]

Q2142[SQ00 9].Wheredo yourecall seeingads beforeyour purchase?

[Outdoor advertising (e.g., billboards, posters)]

Q2142[SQ010]. Wheredoyou recallseeingads beforeyour purchase?

[Mobileapp advertisements]

Q2142[SQ01 1].Wheredo yourecall seeingads beforeyour purchase? [Influencer marketingon socialmedia platforms]

Q2142[SQ012]. Wheredoyou recallseeing adsbeforeyour purchase?

[Product placementsin moviesorTV shows]

Q2142[SQ013]. Wheredoyou recallseeing adsbeforeyour purchase?

[Directmail advertisements]

Q2142[SQ01 4].Wheredo yourecall seeingads beforeyour purchase?

[Eventsor sponsorships]

Q2142[SQ01 5].Wheredo yourecall seeingads beforeyour purchase?[Instoredisplays or promotions]

SexCode

AgeCode

LocalityCode

Chisquare 0.4060.9815.24312.3660.4870.0540.0150.4124.8989.6996.654-3.4789.8120.562

df11111111111111

Sig.0.524 .322b .022 * .000 * 0.485 .816b .902b 0.521 .027 * .002 * .010*,b 0.062 .002*,b .453b

Chisquare 12.2189.57316.96423.33816.1853.1626.80410.3644.36814.19616.539-17.72718.0132.213

df44444444444444

Sig. .016 * .048*,b .002*,b .000 * .003*,b .531b,c .147b .035*,b .359b .007*,b .002*,b .001*,b .001*,b .697b,c Chisquare 10.3443.13512.7771.9176.7585.5742.63210.8928.75011.38010.873-8.98315.8223.156

df55555555555555

Sig.0.066 .679b,c .026*,b,c 0.861 .239b .350b,c .756b,c .054b,c .119b,c .044*,b,c .054b,c .110b .007*,b,c .676b,c

HouseholdSizeCode

Chisquare 3.5383.3138.38915.82714.8433.43612.3294.3416.3615.91011.716-10.03331.8502.861

df44444444444444

Sig.0.472 .507b,c .078b .003 * .005*,b .488b,c .015*,b,c .362b .174b .206b .020*,b,c .040*,b .000*,b,c .581b,c

MaritalStatusCode

Chisquare 2.5464.41316.4452.00319.0113.4952.3813.7571.06917.0230.845-7.97517.9703.635

df33333333333333

Sig. .467b .220

LevelofEducation Code

OccupationCode

square 9.0715.02513.41024.6697.2922.8626.7843.4383.07141.91514.818-19.81244.4417.114

df55555555555555

.000

.212b,c Chisquare 19.94242.51547.54032.73512.09210.8026.51218.51518.13525.20921.273-24.30217.11115.941

df1212121212121212121212121212

Sig. .068b,c .000*,b,c .000*,b,c .001*,b,c .438

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

Table 6.12a - Post Purchase Behaviour & Customer Support Need (Count & Row %)

Table 6.12b - Post Purchase Behaviour & Customer Support Need (Test Statistic)

Table 6.12a - Satisfaction Levels Customer Support (Count, Mean, Standard Deviation)

Table 6.12b - Satisfaction Levels Customer Support (Test Statistic)

ANOVA Tablea Q2152.Howsatisfiedwereyouwiththe overallsupportexperience?*SexCode

a.Withfewerthanthreegroups,linearitymeasuresforQ2152.Howsatisfiedwereyouwiththeoverallsupportexperience?*SexCodecannot becomputed.

Measures of Association

ANOVA Table

Q2152. How satisfied were you with the overall support experience? * Marital Status Code

Between Groups Within Groups Total

SquareFSig.

EtaEtaSquared Q2152.Howsatisfiedwereyouwiththe overallsupportexperience?*SexCode

Q2152. How satisfied were you with the overall support experience? * Age Code

0.0160.000

Between Groups Within Groups Total

ANOVA Table

Sum of SquaresdfMean SquareFSig. (Combined)3.28240.8201.4020.242

Linearity0.97010.9701.6570.202

Deviation from Linearity 2.31230.7711.3160.275

43.906750.585

47.18879

Measures of Association

RR SquaredEtaEta Squared

Q2152. How satisfied were you with the overall support experience? * Age Code

-0.1430.0210.2640.070

ANOVA Table

Sum of SquaresdfMean SquareFSig. (Combined)5.35951.0721.8960.105

Q2152. How satisfied were you with the overall support experience? * Locality Code Between Groups Within Groups Total

Linearity0.47110.4710.8330.364

Deviation from Linearity 4.88841.2222.1620.082

41.828740.565 47.18879

Measures of Association

RR SquaredEtaEta Squared

Q2152. How satisfied were you with the overall support experience? * Locality Code

-0.1000.0100.3370.114

Measures of Association

RR SquaredEtaEta Squared Q2152. How satisfied were you with the overall support experience?

ANOVA Table

Q2152. How satisfied were you with the overall support experience? * Level of Education Code

Between Groups Within Groups Total

Sum of SquaresdfMean SquareFSig. (Combined)8.25342.0633.9740.006

Linearity0.08210.0820.1590.692

Deviation from Linearity 8.17032.7235.2460.002

38.935750.519 47.18879

Measures of Association

RR SquaredEtaEta Squared Q2152. How satisfied were you with the overall support experience? * Level of Education Code 0.0420.0020.4180.175

ANOVA Table

Q2152. How satisfied were you with the overall support experience? * Occupation Code

Between Groups Within Groups Total

Sum of SquaresdfMean SquareFSig. (Combined)9.229110.8391.5030.151

Linearity0.32510.3250.5810.448

Deviation from Linearity 8.905100.8901.5950.127

37.958680.558 47.18879

Measures of Association

RR SquaredEtaEta Squared

Q2152. How satisfied were you with the overall support experience? * Occupation Code

0.0830.0070.4420.196

Table 6.13a - Changing Purchasing Behaviours (Count & Row %)

Table 6.13b - Changing Purchasing Behaviours (Test Statistic)

Q311.Have your purchasing habits changed in the last year when it comes to these products/services?

Chisquare

Sig..037* Chisquare

Sig..012*

Sig.0.246

Sig.0.458

Chisquare

Sig.0.623 Chisquare

Sig..026* Chisquare

Sig..016*,b

Results are based on nonempty rows and columns in each innermost *.subtable. The Chi-square statistic is significant at the .05 level.

b. The minimum expected cell count in this subtable is less than one. Chi-square results may be invalid.

SexCode

AgeCode

18

Locality Code

Becamemore price-sensitiveor budget-conscious.

Beganseeking out environmentallyfriendlyor sustainable

Begansharing experiencesor recommendations withfriendsor family.

Changed preferredbrands orproducts.

Decreased frequencyof purchases.

Increased frequencyof purchases.

Started participatingin loyaltyprograms orrewards programs.

Started purchasingfrom differentstores orplatforms.

Started purchasingin bulkorlarger quantities.

Started purchasing morepremium orluxury products. Household SizeCode

Started researching productsmore thoroughly before

Startedusing discountsor couponsmore frequently.

StartedOther experimenting withnew productsor brands.

Switchedto online purchasing insteadofinstore.

29106.3%31.9%21.3%53.2%1912.0%95.7%21.3%00.0%00.0%00.0%21.3%00.0%00.0%00.0%00.0% 30to391611.4%21.4%00.0%10.7%53.6%53.6%85.7%00.0%32.1%00.0%00.0%21.4%00.0%21.4%10.7% 40to492217.7%00.0%10.8%00.0%32.4%54.0%32.4%00.0%21.6%00.0%00.0%10.8%10.8%00.0%00.0%

50to592416.7%00.0%00.0%00.0%117.6%21.4%32.1%10.7%10.7%10.7%00.0%21.4%00.0%00.0%32.1% 60+218.8%00.0%00.0%10.4%125.0%41.7%62.5%00.0%20.8%10.4%00.0%10.4%00.0%00.0%00.0%

SouthernHarbourDistrict 2313.9%31.8%00.0%31.8%74.2%42.4%31.8%10.6%21.2%00.0%00.0%10.6%00.0%00.0%00.0%

NorthernHarbourDistrict 2511.3%20.9%10.5%00.0%177.7%62.7%83.6%00.0%00.0%00.0%00.0%20.9%10.5%20.9%20.9% SouthEasternDistrict 96.7%00.0%00.0%00.0%118.2%32.2%10.7%00.0%43.0%10.7%00.0%21.5%00.0%00.0%00.0% WesternDistrict 1110.8%00.0%00.0%43.9%65.9%32.9%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%11.0%

NorthernDistrict 2014.1%00.0%00.0%00.0%74.9%96.3%96.3%00.0%10.7%10.7%21.4%10.7%00.0%00.0%10.7% Gozo&CominoDistrict 512.5%00.0%25.0%00.0%25.0%00.0%12.5%00.0%12.5%00.0%00.0%00.0%00.0%00.0%00.0% 11011.4%00.0%22.3%00.0%66.8%11.1%55.7%00.0%22.3%00.0%00.0%00.0%00.0%00.0%00.0% 2208.7%00.0%00.0%10.4%167.0%73.0%41.7%00.0%10.4%10.4%00.0%31.3%00.0%00.0%20.9% 32912.7%20.9%10.4%31.3%167.0%41.8%52.2%10.4%20.9%00.0%00.0%31.3%10.4%20.9%20.9% 42314.0%00.0%00.0%31.8%63.7%106.1%31.8%00.0%21.2%10.6%21.2%00.0%00.0%00.0%00.0% 5+1111.5%33.1%00.0%00.0%66.3%33.1%55.2%00.0%11.0%00.0%00.0%00.0%00.0%00.0%00.0% Single218.4%52.0%20.8%31.2%249.6%135.2%52.0%00.0%10.4%00.0%20.8%20.8%00.0%00.0%00.0% Married/Partnered 6213.2%00.0%10.2%40.9%214.5%112.3%153.2%10.2%61.3%10.2%00.0%20.4%00.0%20.4%40.9% Seperated/Divorced 713.0%00.0%00.0%00.0%23.7%11.9%23.7%00.0%00.0%11.9%00.0%23.7%11.9%00.0%00.0% Widow/Widower 39.4%00.0%00.0%00.0%39.4%00.0%00.0%00.0%13.1%00.0%00.0%00.0%00.0%00.0%00.0%

MFQ2411.8%00.0%00.0%00.0%12.9%12.9%12.9%00.0%12.9%00.0%00.0%00.0%00.0%00.0%00.0%

MFQ32910.6%00.0%00.0%10.4%196.9%31.1%72.6%00.0%10.4%00.0%00.0%31.1%00.0%00.0%31.1%

MFQ41215.8%00.0%00.0%22.6%45.3%33.9%22.6%00.0%11.3%00.0%00.0%00.0%00.0%00.0%00.0%

MFQ52615.9%00.0%31.8%10.6%116.7%42.4%10.6%00.0%31.8%10.6%00.0%21.2%00.0%00.0%00.0%

MFQ6139.7%53.7%00.0%32.2%107.5%107.5%75.2%00.0%21.5%10.7%00.0%10.7%00.0%00.0%00.0%

MFQ7&897.3%00.0%00.0%00.0%54.0%43.2%43.2%10.8%00.0%00.0%21.6%00.0%10.8%21.6%10.8% Legislators,Executives&SeniorManagers

913.0%00.0%00.0%00.0%57.2%00.0%00.0%11.4%00.0%11.4%00.0%34.3%00.0%00.0%11.4% Science,Eng.&OtherSpecialised 2315.1%00.0%10.7%10.7%106.6%74.6%74.6%00.0%53.3%00.0%00.0%10.7%10.7%00.0%00.0% AssociateProfessionalOccupations 79.6%00.0%00.0%11.4%34.1%45.5%11.4%00.0%00.0%00.0%11.4%11.4%00.0%22.7%00.0% ClericalSupportWorkers 48.9%00.0%00.0%00.0%36.7%511.1%36.7%00.0%00.0%00.0%00.0%00.0%00.0%00.0%12.2% ServiceandSalesWorkers 812.7%23.2%11.6%11.6%46.3%00.0%23.2%00.0%11.6%11.6%00.0%00.0%00.0%00.0%00.0%

Skilledagricultural,forestryandfishery 00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Craftandrelatedtradesworkers 525.0%00.0%00.0%00.0%15.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Plantandmachineoperatorsand 16.3%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Elementaryoccupations 220.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Armedforcesoccupations

420.0%00.0%00.0%00.0%00.0%00.0%15.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Retired/Pensioners 54.4%00.0%00.0%00.0%65.3%10.9%43.5%00.0%10.9%00.0%00.0%10.9%00.0%00.0%00.0% HomeCarers/NonGainfullyOccupied 1512.1%00.0%00.0%00.0%64.8%43.2%32.4%00.0%10.8%00.0%00.0%00.0%00.0%00.0%21.6% Students1010.2%33.1%11.0%44.1%1212.2%44.1%11.0%00.0%00.0%00.0%11.0%00.0%00.0%00.0%00.0%

Table 6.14b - Changes in Consumer Purchasing Habits (Count & Row %)

Multipleresponsesadjustedto100%

Becamemore price-sensitive orbudgetconscious.

Beganseeking out environmentallyfriendlyor sustainable

Begansharing experiencesor recommendatio nswithfriends orfamily.

Sex

Changed preferred brandsor products. Age

Decreased frequencyof purchases.

Increased frequencyof purchases.

Started experimenting withnew productsor brands.

Started participatingin loyalty programsor rewards

Started purchasingfrom differentstores orplatforms.

Started purchasingin bulkorlarger quantities.

Started purchasing morepremium orluxury products.

Started researching productsmore thoroughly before

Startedusing discountsor couponsmore frequently.

Switchedto online purchasing insteadofinstore.

Other

18to291019.2%35.8%23.8%59.6%1936.5%917.3%23.8%00.0%00.0%00.0%23.8%00.0%00.0%00.0%00.0%52100%

30to391635.6%24.4%00.0%12.2%511.1%511.1%817.8%00.0%36.7%00.0%00.0%24.4%00.0%24.4%12.2%45100% 40to492257.9%00.0%12.6%00.0%37.9%513.2%37.9%00.0%25.3%00.0%00.0%12.6%12.6%00.0%00.0%38100% 50to592450.0%00.0%00.0%00.0%1122.9%24.2%36.3%12.1%12.1%12.1%00.0%24.2%00.0%00.0%36.3%48100% 60+2143.8%00.0%00.0%12.1%1225.0%48.3%612.5%00.0%24.2%12.1%00.0%12.1%00.0%00.0%00.0%48100% SouthernHarbourDistrict2348.9%36.4%00.0%36.4%714.9%48.5%36.4%12.1%24.3%00.0%00.0%12.1%00.0%00.0%00.0%47100% NorthernHarbourDistrict2537.9%23.0%11.5%00.0%1725.8%69.1%812.1%00.0%00.0%00.0%00.0%23.0%11.5%23.0%23.0%66100% SouthEasternDistrict929.0%00.0%00.0%00.0%1135.5%39.7%13.2%00.0%412.9%13.2%00.0%26.5%00.0%00.0%00.0%31100% WesternDistrict1144.0%00.0%00.0%416.0%624.0%312.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%14.0%25100% NorthernDistrict2039.2%00.0%00.0%00.0%713.7%917.6%917.6%00.0%12.0%12.0%23.9%12.0%00.0%00.0%12.0%51100% Gozo&CominoDistrict545.5%00.0%218.2%00.0%218.2%00.0%19.1%00.0%19.1%00.0%00.0%00.0%00.0%00.0%00.0%11100% 11038.5%00.0%27.7%00.0%623.1%13.8%519.2%00.0%27.7%00.0%00.0%00.0%00.0%00.0%00.0%26100% 22036.4%00.0%00.0%11.8%1629.1%712.7%47.3%00.0%11.8%11.8%00.0%35.5%00.0%00.0%23.6%55100% 32940.8%22.8%11.4%34.2%1622.5%45.6%57.0%11.4%22.8%00.0%00.0%34.2%11.4%22.8%22.8%71100% 42346.0%00.0%00.0%36.0%612.0%1020.0%36.0%00.0%24.0%12.0%24.0%00.0%00.0%00.0%00.0%50100% 5+1137.9%310.3%00.0%00.0%620.7%310.3%517.2%00.0%13.4%00.0%00.0%00.0%00.0%00.0%00.0%29100% Single2126.9%56.4%22.6%33.8%2430.8%1316.7%56.4%00.0%11.3%00.0%22.6%22.6%00.0%00.0%00.0%78100% Married/Partnered6247.7%00.0%10.8%43.1%2116.2%118.5%1511.5%10.8%64.6%10.8%00.0%21.5%00.0%21.5%43.1%##100% Seperated/Divorced743.8%00.0%00.0%00.0%212.5%16.3%212.5%00.0%00.0%16.3%00.0%212.5%16.3%00.0%00.0%16100% Widow/Widower342.9%00.0%00.0%00.0%342.9%00.0%00.0%00.0%114.3%00.0%00.0%00.0%00.0%00.0%00.0%7100% MFQ2450.0%00.0%00.0%00.0%112.5%112.5%112.5%00.0%112.5%00.0%00.0%00.0%00.0%00.0%00.0%8100% MFQ32943.9%00.0%00.0%11.5%1928.8%34.5%710.6%00.0%11.5%00.0%00.0%34.5%00.0%00.0%34.5%66100% MFQ41250.0%00.0%00.0%28.3%416.7%312.5%28.3%00.0%14.2%00.0%00.0%00.0%00.0%00.0%00.0%24100% MFQ52650.0%00.0%35.8%11.9%1121.2%47.7%11.9%00.0%35.8%11.9%00.0%23.8%00.0%00.0%00.0%52100% MFQ61325.0%59.6%00.0%35.8%1019.2%1019.2%713.5%00.0%23.8%11.9%00.0%11.9%00.0%00.0%00.0%52100% MFQ7&8931.0%00.0%00.0%00.0%517.2%413.8%413.8%13.4%00.0%00.0%26.9%00.0%13.4%26.9%13.4%29100% Legislators,Executives&Senior 945.0%00.0%00.0%00.0%525.0%00.0%00.0%15.0%00.0%15.0%00.0%315.0%00.0%00.0%15.0%20100% Science,Eng.&OtherSpecialised 2341.1%00.0%11.8%11.8%1017.9%712.5%712.5%00.0%58.9%00.0%00.0%11.8%11.8%00.0%00.0%56100% AssociateProfessionalOccupations735.0%00.0%00.0%15.0%315.0%420.0%15.0%00.0%00.0%00.0%15.0%15.0%00.0%210.0%00.0%20100% ClericalSupportWorkers425.0%00.0%00.0%00.0%318.8%531.3%318.8%00.0%00.0%00.0%00.0%00.0%00.0%00.0%16.3%16100% ServiceandSalesWorkers840.0%210.0%15.0%15.0%420.0%00.0%210.0%00.0%15.0%15.0%00.0%00.0%00.0%00.0%00.0%20100% Skilledagricultural,forestryandfishery00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00% Craftandrelatedtradesworkers583.3%00.0%00.0%00.0%116.7%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%6100% Plantandmachineoperatorsand 1100.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%1100% Elementaryoccupations2100.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%2100% Armedforcesoccupations480.0%00.0%00.0%00.0%00.0%00.0%120.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%5100% Retired/Pensioners527.8%00.0%00.0%00.0%633.3%15.6%422.2%00.0%15.6%00.0%00.0%15.6%00.0%00.0%00.0%18100% HomeCarers/NonGainfullyOccupied1548.4%00.0%00.0%00.0%619.4%412.9%39.7%00.0%13.2%00.0%00.0%00.0%00.0%00.0%26.5%31100% Students1027.8%38.3%12.8%411.1%1233.3%411.1%12.8%00.0%00.0%00.0%12.8%00.0%00.0%00.0%00.0%36100%

Table 6.14c - Changes in Consumer Purchasing Habits (Test Statistic)

Q312.Whatisthemain wayinwhichtheychanged?

SexCode

AgeCode

LocalityCode

Chisquare 16.159

df15

Sig..372a,b

Chisquare 118.391

df60

Sig. .000a,b,*

Chisquare 117.683

df75

Sig. .001a,b,*

HouseholdSize Code

MaritalStatus Code

Levelof EducationCode

Chisquare 77.498

df60

Sig..064a,b

Chisquare 73.844

df45

Sig. .004a,b,* Chisquare 123.767

df75

Sig. .000a,b,*

OccupationCode

Chisquare 192.354

df180

Sig..251a,b

Resultsarebasedonnonemptyrowsandcolumnsineach innermostsubtable. *.TheChi-squarestatisticissignificantatthe.05level.

a.Morethan20%ofcellsinthissubtablehaveexpected cellcountslessthan5.Chi-squareresultsmaybeinvalid.

b.Theminimumexpectedcellcountinthissubtableisless thanone.Chi-squareresultsmaybeinvalid.

SexCode

AgeCode

Locality Code Household SizeCode

Pricechangesor discounts. Productqualityor performance. Recommendation sfromfriendsor family. Marital StatusCode Levelof Education Code Occupation Code

AvailabilityOther of newproductsor brands. Changesin financial situationor Changesin personal preferencesor Convenienceof online shopping. Environmentalor ethical considerations. Influenceof trendsor culturalshifts. Personal experiences withtheproduct

50to5900.0%128.3%1812.5%00.0%21.4%00.0%00.0%1611.1%00.0%00.0%00.0%

60+00.0%93.8%229.2%00.0%00.0%00.0%20.8%145.8%00.0%10.4%00.0%

SouthernHarbourDistrict 00.0%95.4%1710.2%00.0%00.0%00.0%00.0%169.6%53.0%00.0%00.0%

NorthernHarbourDistrict 00.0%2611.7%167.2%00.0%10.5%31.4%10.5%167.2%00.0%10.5%20.9%

SouthEasternDistrict 00.0%32.2%2014.9%10.7%10.7%00.0%00.0%64.5%00.0%00.0%00.0%

WesternDistrict00.0%54.9%1514.7%00.0%11.0%00.0%00.0%43.9%00.0%00.0%00.0%

NorthernDistrict32.1%139.2%1812.7%00.0%10.7%00.0%42.8%96.3%32.1%00.0%00.0%

Gozo&CominoDistrict 00.0%512.5%512.5%00.0%00.0%00.0%00.0%12.5%00.0%00.0%00.0%

100.0%78.0%1314.8%00.0%00.0%00.0%00.0%55.7%00.0%11.1%00.0%

200.0%104.3%2510.9%00.0%10.4%31.3%10.4%156.5%00.0%00.0%00.0%

300.0%2511.0%2511.0%00.0%00.0%00.0%10.4%125.3%62.6%00.0%20.9%

421.2%116.7%2112.8%00.0%31.8%00.0%21.2%95.5%21.2%00.0%00.0% 5+11.0%88.3%77.3%11.0%00.0%00.0%11.0%1111.5%00.0%00.0%00.0%

Single20.8%208.0%2610.4%00.0%10.4%31.2%31.2%135.2%83.2%00.0%20.8%

Married/Partnered 10.2%347.2%5511.7%10.2%20.4%00.0%20.4%357.4%00.0%00.0%00.0%

Seperated/Divorced 00.0%611.1%713.0%00.0%11.9%00.0%00.0%23.7%00.0%00.0%00.0% Widow/Widower00.0%13.1%39.4%00.0%00.0%00.0%00.0%26.3%00.0%13.1%00.0%

MFQ200.0%12.9%38.8%00.0%00.0%00.0%12.9%38.8%00.0%00.0%00.0%

MFQ310.4%259.1%186.6%00.0%00.0%31.1%00.0%165.8%31.1%00.0%00.0%

MFQ400.0%810.5%1215.8%00.0%00.0%00.0%00.0%22.6%22.6%00.0%00.0%

MFQ500.0%127.3%1911.6%00.0%21.2%00.0%10.6%159.1%31.8%00.0%00.0%

MFQ621.5%118.2%2619.4%10.7%00.0%00.0%32.2%64.5%00.0%10.7%21.5%

MFQ7&800.0%43.2%1310.5%00.0%21.6%00.0%00.0%108.1%00.0%00.0%00.0% Legislators,Executives&SeniorManagers 00.0%913.0%68.7%00.0%11.4%00.0%00.0%45.8%00.0%00.0%00.0% Science,Eng.&OtherSpecialised 10.7%159.9%2516.4%10.7%21.3%00.0%10.7%106.6%10.7%00.0%00.0% AssociateProfessionalOccupations 00.0%68.2%912.3%00.0%00.0%00.0%00.0%56.8%00.0%00.0%00.0%

ClericalSupportWorkers 24.4%36.7%511.1%00.0%12.2%12.2%24.4%24.4%00.0%00.0%00.0%

ServiceandSalesWorkers 00.0%23.2%1219.0%00.0%00.0%00.0%00.0%46.3%00.0%00.0%23.2% Skilledagricultural,forestryandfishery 00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Craftandrelatedtradesworkers 00.0%420.0%15.0%00.0%00.0%00.0%00.0%00.0%15.0%00.0%00.0%

Plantandmachineoperatorsand 00.0%16.3%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Elementaryoccupations 00.0%220.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Armedforcesoccupations 00.0%210.0%210.0%00.0%00.0%00.0%00.0%15.0%00.0%00.0%00.0% Retired/Pensioners 00.0%10.9%97.9%00.0%00.0%00.0%10.9%65.3%00.0%10.9%00.0% HomeCarers/NonGainfullyOccupied 00.0%75.6%97.3%00.0%00.0%00.0%10.8%1411.3%00.0%00.0%00.0% Students00.0%99.2%1313.3%00.0%00.0%22.0%00.0%66.1%66.1%00.0%00.0%

Table 6.15b - Cause of Change in Consumer Purchasing Habits (Count & Row %)

Multipleresponsesadjustedto100%

Availabilityofnew productsor brands.

Changesin financialsituation orbudget.

Changesin personal preferencesor Convenienceof onlineshopping.

Environmentalor ethical considerations.

Influenceoftrends orculturalshifts. Personal experienceswith theproductor

Pricechangesor discounts. Productqualityor performance. Recommendations fromfriendsor family.

50to5900.0%1225.0%1837.5%00.0%24.2%00.0%00.0%1633.3%00.0%00.0%00.0%48100% 60+00.0%918.8%2245.8%00.0%00.0%00.0%24.2%1429.2%00.0%12.1%00.0%48100%

SouthernHarbourDistrict00.0%919.1%1736.2%00.0%00.0%00.0%00.0%1634.0%510.6%00.0%00.0%47100% NorthernHarbourDistrict00.0%2639.4%1624.2%00.0%11.5%34.5%11.5%1624.2%00.0%11.5%23.0%66100% SouthEasternDistrict00.0%39.7%2064.5%13.2%13.2%00.0%00.0%619.4%00.0%00.0%00.0%31100% WesternDistrict00.0%520.0%1560.0%00.0%14.0%00.0%00.0%416.0%00.0%00.0%00.0%25100% NorthernDistrict35.9%1325.5%1835.3%00.0%12.0%00.0%47.8%917.6%35.9%00.0%00.0%51100% Gozo&CominoDistrict00.0%545.5%545.5%00.0%00.0%00.0%00.0%19.1%00.0%00.0%00.0%11100% 100.0%726.9%1350.0%00.0%00.0%00.0%00.0%519.2%00.0%13.8%00.0%26100% 200.0%1018.2%2545.5%00.0%11.8%35.5%11.8%1527.3%00.0%00.0%00.0%55100% 300.0%2535.2%2535.2%00.0%00.0%00.0%11.4%1216.9%68.5%00.0%22.8%71100% 424.0%1122.0%2142.0%00.0%36.0%00.0%24.0%918.0%24.0%00.0%00.0%50100% 5+13.4%827.6%724.1%13.4%00.0%00.0%13.4%1137.9%00.0%00.0%00.0%29100% Single22.6%2025.6%2633.3%00.0%11.3%33.8%33.8%1316.7%810.3%00.0%22.6%78100% Married/Partnered10.8%3426.2%5542.3%10.8%21.5%00.0%21.5%3526.9%00.0%00.0%00.0%130100% Seperated/Divorced00.0%637.5%743.8%00.0%16.3%00.0%00.0%212.5%00.0%00.0%00.0%16100% Widow/Widower00.0%114.3%342.9%00.0%00.0%00.0%00.0%228.6%00.0%114.3%00.0%7100%

MFQ200.0%112.5%337.5%00.0%00.0%00.0%112.5%337.5%00.0%00.0%00.0%8100% MFQ311.5%2537.9%1827.3%00.0%00.0%34.5%00.0%1624.2%34.5%00.0%00.0%66100%

MFQ400.0%833.3%1250.0%00.0%00.0%00.0%00.0%28.3%28.3%00.0%00.0%24100%

MFQ500.0%1223.1%1936.5%00.0%23.8%00.0%11.9%1528.8%35.8%00.0%00.0%52100% MFQ623.8%1121.2%2650.0%11.9%00.0%00.0%35.8%611.5%00.0%11.9%23.8%52100% MFQ7&800.0%413.8%1344.8%00.0%26.9%00.0%00.0%1034.5%00.0%00.0%00.0%29100% Legislators,Executives&SeniorManagers00.0%945.0%630.0%00.0%15.0%00.0%00.0%420.0%00.0%00.0%00.0%20100% Science,Eng.&OtherSpecialisedProfessionals11.8%1526.8%2544.6%11.8%23.6%00.0%11.8%1017.9%11.8%00.0%00.0%56100% AssociateProfessionalOccupations00.0%630.0%945.0%00.0%00.0%00.0%00.0%525.0%00.0%00.0%00.0%20100% ClericalSupportWorkers212.5%318.8%531.3%00.0%16.3%16.3%212.5%212.5%00.0%00.0%00.0%16100% ServiceandSalesWorkers00.0%210.0%1260.0%00.0%00.0%00.0%00.0%420.0%00.0%00.0%210.0%20100% Skilledagricultural,forestryandfisheryworkers00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00% Craftandrelatedtradesworkers00.0%466.7%116.7%00.0%00.0%00.0%00.0%00.0%116.7%00.0%00.0%6100% Plantandmachineoperatorsandassemblers00.0%1100.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%1100% Elementaryoccupations00.0%2100.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%2100% Armedforcesoccupations00.0%240.0%240.0%00.0%00.0%00.0%00.0%120.0%00.0%00.0%00.0%5100% Retired/Pensioners00.0%15.6%950.0%00.0%00.0%00.0%15.6%633.3%00.0%15.6%00.0%18100% HomeCarers/NonGainfullyOccupied00.0%722.6%929.0%00.0%00.0%00.0%13.2%1445.2%00.0%00.0%00.0%31100% Students00.0%925.0%1336.1%00.0%00.0%25.6%00.0%616.7%616.7%00.0%00.0%36100%

Table 6.15b - Cause of Change in Consumer Purchasing Habits (Test Statistic)

Q313.What causedyouto makethis change?

SexCode

AgeCode

LocalityCode

HouseholdSizeCode

MaritalStatusCode

LevelofEducation Code

OccupationCode

Chi-square31.884 df11

Sig. .001*,b,c Chi-square100.988 df44

Sig. .000*,b,c Chi-square91.744 df55

Sig. .001*,b,c Chi-square69.972 df44

Sig. .008*,b,c Chi-square64.926 df33

Sig. .001*,b,c Chi-square86.714 df55

Sig. .004*,b,c Chi-square176.696 df132

Sig. .006*,b,c

Resultsarebasedonnonemptyrowsandcolumnsin eachinnermostsubtable. *.TheChi-squarestatisticissignificantatthe.05level. b.Morethan20%ofcellsinthissubtablehaveexpected cellcountslessthan5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableis lessthanone.Chi-squareresultsmaybeinvalid.

Table 6.16a - Purchase Habit Formation (Origin) (Count, Row Yes/ No % - Multiple Choice)

Q314[A1]. From what you can remember, why did you start making this purchase from this particular company?

[Competitive pricing.]

Q314[A2]. From what you can remember, why did you start making this purchase from this particular company?

[Superior product quality.]

Q314[A3]. From what you can remember, why did you start making this purchase from this particular company? [Convenient location or accessibility.]

Q314[A4]. From what you can remember, why did you start making this purchase from this particular company?

[Positive past experiences with the company.]

Q314[A5]. From what you can remember, why did you start making this purchase from this particular company? [Recommendation from friends or family.] Sex

Q314[A6]. From what you can remember, why did you start making this purchase from this particular company? [Loyalty program benefits or rewards.]

Q314[A7]. From what you can remember, why did you start making this purchase from this particular company? [Special promotions or discounts.]

Q314[A8]. From what you can remember, why did you start making this purchase from this particular company? [Positive online reviews or ratings.]

Q314[A9]. From what you can remember, why did you start making this purchase from this particular company? [Unique product offerings.]

Q314[A10]. From what you can remember, why did you start making this purchase from this particular company? [Ethical or sustainable business practices.]

Q314[A11]. From what you can remember, why did you start making this purchase from this particular company?

[Superior customer service.]

Q314[A12]. From what you can remember, why did you start making this purchase from this particular company? [Brand reputation or image.]

Q314[A14]. From what you can remember, why did you start making this purchase from this particular company? [Innovative technology or features.]

Male12534.3%11331.0%15943.7%298.0%195.2%102.7%236.3%123.3%92.5%236.3%236.3%92.5%61.6% Female16136.4%11726.5%18942.8%398.8%317.0%112.5%225.0%92.0%245.4%368.1%327.2%61.4%00.0% 18 to 295534.8%5333.5%6038.0%2213.9%117.0%63.8%95.7%1710.8%21.3%42.5%74.4%31.9%31.9% 30 to 396345.0%3625.7%5740.7%96.4%96.4%53.6%85.7%10.7%107.1%1611.4%75.0%64.3%10.7% 40 to 494334.7%3225.8%6552.4%118.9%54.0%21.6%86.5%00.0%75.6%129.7%108.1%32.4%10.8% 50 to 595437.5%5638.9%6645.8%96.3%64.2%21.4%85.6%21.4%42.8%128.3%149.7%10.7%10.7% 60+7129.6%5322.1%10041.7%177.1%197.9%62.5%125.0%10.4%104.2%156.3%177.1%20.8%00.0% Southern Harbour District5834.9%4225.3%6438.6%116.6%116.6%53.0%95.4%74.2%53.0%106.0%169.6%31.8%42.4% Northern Harbour District9542.8%6629.7%10145.5%2712.2%146.3%104.5%167.2%104.5%104.5%167.2%125.4%41.8%00.0% South Eastern District3828.4%4432.8%5742.5%118.2%118.2%43.0%96.7%32.2%86.0%107.5%43.0%32.2%00.0% Western District3534.3%2322.5%5049.0%98.8%76.9%11.0%54.9%11.0%54.9%76.9%109.8%54.9%22.0% Northern District4733.1%3927.5%5740.1%96.3%64.2%10.7%64.2%00.0%42.8%128.5%128.5%00.0%00.0% Gozo & Comino District1332.5%1640.0%1947.5%12.5%12.5%00.0%00.0%00.0%12.5%410.0%12.5%00.0%00.0% 11820.5%1921.6%5562.5%44.5%55.7%00.0%22.3%00.0%44.5%910.2%22.3%00.0%00.0% 27833.9%5825.2%10043.5%229.6%125.2%83.5%198.3%31.3%104.3%114.8%187.8%20.9%00.0% 38738.2%6829.8%9541.7%2410.5%177.5%52.2%146.1%73.1%125.3%229.6%146.1%52.2%10.4% 46640.2%5231.7%7042.7%127.3%127.3%31.8%74.3%42.4%63.7%137.9%159.1%53.0%21.2% 5+3738.5%3334.4%2829.2%66.3%44.2%55.2%33.1%77.3%11.0%44.2%66.3%33.1%33.1% Single8534.0%7329.2%10542.0%3012.0%2510.0%104.0%176.8%187.2%114.4%135.2%124.8%62.4%41.6% Married/ Partnered17938.1%13929.6%19341.1%316.6%214.5%112.3%234.9%20.4%214.5%367.7%388.1%81.7%20.4% Seperated/ Divorced1833.3%1425.9%2953.7%23.7%00.0%00.0%59.3%11.9%11.9%1018.5%23.7%11.9%00.0% Widow/ Widower412.5%412.5%2165.6%515.6%412.5%00.0%00.0%00.0%00.0%00.0%39.4%00.0%00.0%

MFQ 21029.4%720.6%1132.4%25.9%38.8%00.0%25.9%00.0%25.9%00.0%25.9%12.9%00.0%

MFQ 39635.0%7326.6%11642.3%217.7%165.8%82.9%176.2%62.2%145.1%145.1%228.0%20.7%00.0%

MFQ 43140.8%3140.8%2938.2%1215.8%45.3%00.0%33.9%22.6%11.3%67.9%45.3%00.0%11.3%

MFQ 56237.8%4326.2%6841.5%127.3%116.7%31.8%74.3%21.2%53.0%106.1%84.9%00.0%00.0%

MFQ 63324.6%3425.4%6850.7%75.2%53.7%10.7%43.0%32.2%53.7%1611.9%107.5%21.5%10.7% MFQ 7&85443.5%4233.9%5645.2%1411.3%118.9%97.3%129.7%86.5%64.8%1310.5%97.3%108.1%43.2% Legislators, Executives & Senior Managers2637.7%1724.6%3550.7%57.2%45.8%34.3%68.7%00.0%68.7%68.7%22.9%00.0%00.0% Science, Eng.& Other Specialised Professionals5334.9%4932.2%8052.6%117.2%106.6%63.9%53.3%21.3%42.6%1711.2%117.2%32.0%32.0% Associate Professional Occupations3750.7%2737.0%2534.2%1115.1%34.1%22.7%56.8%34.1%11.4%1013.7%68.2%68.2%11.4% Clerical Support Workers2351.1%1533.3%1737.8%511.1%48.9%00.0%36.7%48.9%511.1%36.7%715.6%00.0%00.0% Service and Sales Workers2031.7%1523.8%2641.3%46.3%57.9%00.0%11.6%00.0%57.9%914.3%69.5%11.6%00.0% Skilled agricultural, forestry and fishery workers00.0%150.0%00.0%00.0%00.0%150.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0% Craft and related trades workers630.0%420.0%945.0%15.0%00.0%00.0%15.0%15.0%00.0%15.0%315.0%00.0%00.0% Plant and machine operators and assemblers743.8%956.3%531.3%00.0%00.0%00.0%212.5%16.3%00.0%00.0%16.3%00.0%00.0% Elementary occupations550.0%440.0%550.0%00.0%00.0%00.0%110.0%00.0%110.0%00.0%00.0%00.0%00.0% Armed forces occupations525.0%630.0%1260.0%00.0%210.0%00.0%00.0%00.0%00.0%210.0%00.0%00.0%00.0% Retired/ Pensioners3530.7%2622.8%5144.7%119.6%76.1%43.5%65.3%00.0%43.5%54.4%108.8%00.0%00.0% Home Carers/ Non Gainfully Occupied3931.5%2520.2%4637.1%97.3%97.3%21.6%86.5%10.8%75.6%43.2%64.8%32.4%00.0% Students3030.6%3232.7%3737.8%1111.2%66.1%33.1%77.1%99.2%00.0%22.0%33.1%22.0%22.0%

Table 6.16b - Purchase Habit Formation (Origin) (Count & Row %)

Multipleresponsesadjustedto100%

Q314[A1].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?

[Competitive pricing.]

Q314[A2].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Superior productquality.]

Q314[A3].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?

[Convenient locationor accessibility.]

Q314[A4].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Positive pastexperiences withthecompany.]

Q314[A5].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company? [Recommendation fromfriendsor family.]

Q314[A6].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Loyalty programbenefits orrewards.]

Q314[A7].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Special promotionsor discounts.]

Q314[A8].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Positive onlinereviewsor ratings.]

Q314[A9].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Unique productofferings.]

Q314[A10].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Ethical orsustainable businesspractices.]

Q314[A11].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Superior customerservice.]

Q314[A12].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company?[Brand reputationor image.]

Q314[A14].From whatyoucan remember,whydid youstartmaking thispurchasefrom thisparticular company? [Innovative technologyor features.]

18to295521.8%5321.0%6023.8%228.7%114.4%62.4%93.6%176.7%20.8%41.6%72.8%31.2%31.2%252100% 30to396327.6%3615.8%5725.0%93.9%93.9%52.2%83.5%10.4%104.4%167.0%73.1%62.6%10.4%228100% 40to494321.6%3216.1%6532.7%115.5%52.5%21.0%84.0%00.0%73.5%126.0%105.0%31.5%10.5%199100% 50to595423.0%5623.8%6628.1%93.8%62.6%20.9%83.4%20.9%41.7%125.1%146.0%10.4%10.4%235100% 60+7122.0%5316.4%10031.0%175.3%195.9%61.9%123.7%10.3%103.1%154.6%175.3%20.6%00.0%323100%

SouthernHarbourDistrict5823.7%4217.1%6426.1%114.5%114.5%52.0%93.7%72.9%52.0%104.1%166.5%31.2%41.6%245100%

NorthernHarbourDistrict9524.9%6617.3%10126.5%277.1%143.7%102.6%164.2%102.6%102.6%164.2%123.1%41.0%00.0%381100% SouthEasternDistrict3818.8%4421.8%5728.2%115.4%115.4%42.0%94.5%31.5%84.0%105.0%42.0%31.5%00.0%202100% WesternDistrict3521.9%2314.4%5031.3%95.6%74.4%10.6%53.1%10.6%53.1%74.4%106.3%53.1%21.3%160100% NorthernDistrict4724.4%3920.2%5729.5%94.7%63.1%10.5%63.1%00.0%42.1%126.2%126.2%00.0%00.0%193100% Gozo&CominoDistrict1323.2%1628.6%1933.9%11.8%11.8%00.0%00.0%00.0%11.8%47.1%11.8%00.0%00.0%56100% 11815.3%1916.1%5546.6%43.4%54.2%00.0%21.7%00.0%43.4%97.6%21.7%00.0%00.0%118100% 27822.9%5817.0%10029.3%226.5%123.5%82.3%195.6%30.9%102.9%113.2%185.3%20.6%00.0%341100% 38723.5%6818.3%9525.6%246.5%174.6%51.3%143.8%71.9%123.2%225.9%143.8%51.3%10.3%371100% 46624.7%5219.5%7026.2%124.5%124.5%31.1%72.6%41.5%62.2%134.9%155.6%51.9%20.7%267100% 5+3726.4%3323.6%2820.0%64.3%42.9%53.6%32.1%75.0%10.7%42.9%64.3%32.1%32.1%140100% Single8520.8%7317.8%10525.7%307.3%256.1%102.4%174.2%184.4%112.7%133.2%122.9%61.5%41.0%409100% Married/Partnered17925.4%13919.7%19327.4%314.4%213.0%111.6%233.3%20.3%213.0%365.1%385.4%81.1%20.3%704100% Seperated/Divorced1821.7%1416.9%2934.9%22.4%00.0%00.0%56.0%11.2%11.2%1012.0%22.4%11.2%00.0%83100% Widow/Widower49.8%49.8%2151.2%512.2%49.8%00.0%00.0%00.0%00.0%00.0%37.3%00.0%00.0%41100%

MFQ21025.0%717.5%1127.5%25.0%37.5%00.0%25.0%00.0%25.0%00.0%25.0%12.5%00.0%40100%

MFQ39623.7%7318.0%11628.6%215.2%164.0%82.0%174.2%61.5%143.5%143.5%225.4%20.5%00.0%405100% MFQ43125.0%3125.0%2923.4%129.7%43.2%00.0%32.4%21.6%10.8%64.8%43.2%00.0%10.8%124100% MFQ56226.8%4318.6%6829.4%125.2%114.8%31.3%73.0%20.9%52.2%104.3%83.5%00.0%00.0%231100% MFQ63317.5%3418.0%6836.0%73.7%52.6%10.5%42.1%31.6%52.6%168.5%105.3%21.1%10.5%189100%

MFQ7&85421.8%4216.9%5622.6%145.6%114.4%93.6%124.8%83.2%62.4%135.2%93.6%104.0%41.6%248100% Legislators,Executives&SeniorManagers2623.6%1715.5%3531.8%54.5%43.6%32.7%65.5%00.0%65.5%65.5%21.8%00.0%00.0%110100% Science,Eng.&OtherSpecialised 5320.9%4919.3%8031.5%114.3%103.9%62.4%52.0%20.8%41.6%176.7%114.3%31.2%31.2%254100% AssociateProfessionalOccupations3727.0%2719.7%2518.2%118.0%32.2%21.5%53.6%32.2%10.7%107.3%64.4%64.4%10.7%137100% ClericalSupportWorkers2326.7%1517.4%1719.8%55.8%44.7%00.0%33.5%44.7%55.8%33.5%78.1%00.0%00.0%86100% ServiceandSalesWorkers2021.7%1516.3%2628.3%44.3%55.4%00.0%11.1%00.0%55.4%99.8%66.5%11.1%00.0%92100% Skilledagricultural,forestryandfishery 00.0%150.0%00.0%00.0%00.0%150.0%00.0%00.0%00.0%00.0%00.0%00.0%00.0%2100% Craftandrelatedtradesworkers623.1%415.4%934.6%13.8%00.0%00.0%13.8%13.8%00.0%13.8%311.5%00.0%00.0%26100% Plantandmachineoperatorsand 728.0%936.0%520.0%00.0%00.0%00.0%28.0%14.0%00.0%00.0%14.0%00.0%00.0%25100% Elementaryoccupations531.3%425.0%531.3%00.0%00.0%00.0%16.3%00.0%16.3%00.0%00.0%00.0%00.0%16100% Armedforcesoccupations518.5%622.2%1244.4%00.0%27.4%00.0%00.0%00.0%00.0%27.4%00.0%00.0%00.0%27100% Retired/Pensioners3522.0%2616.4%5132.1%116.9%74.4%42.5%63.8%00.0%42.5%53.1%106.3%00.0%00.0%159100% HomeCarers/NonGainfullyOccupied3924.5%2515.7%4628.9%95.7%95.7%21.3%85.0%10.6%74.4%42.5%63.8%31.9%00.0%159100% Students3020.8%3222.2%3725.7%117.6%64.2%32.1%74.9%96.3%00.0%21.4%32.1%21.4%21.4%144100%

Table 6.16c - Purchase Habit Formation (Origin) (Test Statistic)

Q314[A1].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company?

[Competitive pricing.]

Q314[A2].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company?

[Superiorproduct quality.]

Q314[A3].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company? [Convenient locationor accessibility.]

Q314[A4].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company? [Positivepast experienceswith thecompany.]

Q314[A5].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company? [Recommendation fromfriendsor family.]

Q314[A6].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company?[Loyalty programbenefits orrewards.]

Q314[A7].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company?[Special promotionsor discounts.]

Q314[A8].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company? [Positiveonline reviewsor ratings.]

Q314[A9].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company?[Unique productofferings.]

Q314[A10].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company?[Ethical orsustainable business practices.]

Q314[A11].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company? [Superiorcustomer service.]

Q314[A12].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company?[Brand reputationor image.]

Q314[A13].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company? [Influencer endorsements.]

Q314[A14].From whatyoucan remember,why didyoustart makingthis purchasefromthis particular company? [Innovative technologyor features.]

SexCode

Chisquare 0.3792.0470.0690.1901.1040.0530.6811.2504.4460.9810.2661.3597.340

df1111111111111

Sig.0.5380.1520.7930.6630.2930.8190.4090.264 .035 * 0.3220.6060.244 .007*,c

AgeCode

Chisquare 9.51015.4127.0448.3803.4102.7310.34152.0607.93110.4624.3847.180-4.662

df4444444444444

Sig. .050 * .004 0.1340.0790.492 .604c 0.987 .000*,c 0.094 .033 * 0.357 .127c .324b,c

Locality Code Househol dSize Code Marital Status Code Levelof Education Code

Occupati onCode

Chisquare 8.7436.6724.2127.3562.9557.4944.39710.8552.8101.1429.0698.727-12.307

df5555555555555

Sig.0.1200.2460.5190.1950.707 .186c 0.494 .054c 0.7290.9500.106 .120b,c .031*,b,c

Chisquare 11.6585.92321.3104.2532.0746.1506.73012.4083.2346.5984.8395.151-10.538

df4444444444444

Sig. .020 * 0.205 .000 * 0.3730.722 .188c 0.151 .015*,c .519c 0.1590.304 .272c .032*,b,c

Chisquare 9.1234.51810.0089.87814.3774.3474.40330.5762.28414.2453.9411.069-3.769

df3333333333333

Sig. .028 * 0.211 .018 * .020*,c .002*,c .226b,c .221c .000*,b,c .516c .003

Chisquare 12.3149.9506.0089.1823.57415.8426.7899.6373.16711.1032.06432.915-14.209

df5555555555555

Chisquare 19.48020.06118.26811.4925.39825.1968.80335.66822.34723.56816.14122.036-9.347

df12121212121212121212121212

Resultsarebasedonnonemptyrowsandcolumnsineachinnermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Theminimumexpectedcellcountinthissubtableislessthanone.Chi-squareresultsmaybeinvalid.

c.Morethan20%ofcellsinthissubtablehaveexpectedcellcountslessthan5.Chi-squareresultsmaybeinvalid.

Widow/Widower412.5%2887.5%

MFQ

Doyouever makethesepurchases online?

Chisquare 0.026 df1

Sig.0.872

Chisquare 82.254 df4

Sig. .000 *

Chisquare 1.782 df5

Sig.0.878

Chisquare 13.782 df4

Sig. .008 *

Chisquare 23.968 df3

Sig. .000 *

Chisquare 50.213 df5

Sig. .000 *

Chisquare 89.917 df12

Sig. .000*,b,c

Resultsarebasedonnonemptyrowsandcolumnsineach innermostsubtable. *.TheChi-squarestatisticissignificantatthe.05level.

b.Morethan20%ofcellsinthissubtablehaveexpected cellcountslessthan5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableisless thanone.Chi-squareresultsmaybeinvalid.

Table 6.17a - Online Purchases (Count & Row %)

Table 6.17b - Online Purchases (Test Statistic)

Table 6.18b - Online Purchase Frequency/ 10 Purchases (Test Statistic)

ANOVATablea

Sumof SquaresdfMeanSquareFSig.

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*SexCode

Between Groups (Combined)6.15016.1500.5070.477

WithinGroups Total

1878.84315512.122

1884.994156

a.Withfewerthanthreegroups,linearitymeasuresforQ33[SQ001].Whenconsideringallyourpurchasesofthistype,forevery10purchasesyoumade, howmanyofthesepurchasesweremadeonline?[OnlinePurchaseFrequency]*SexCodecannotbecomputed.

MeasuresofAssociation

EtaEtaSquared

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*SexCode

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*AgeCode

0.0570.003

Between Groups WithinGroups Total

ANOVATable

Sumof SquaresdfMeanSquareFSig. (Combined)261.389465.3476.1180.000

Linearity163.1901163.19015.2780.000

Deviation fromLinearity

MeasuresofAssociation

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*AgeCode

98.199332.7333.0640.030

1623.60515210.682

1884.994156

RRSquaredEtaEtaSquared

-0.2940.0870.3720.139

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

Between Groups

[OnlinePurchaseFrequency]*HouseholdSizeCode

ANOVATable

Sumof SquaresdfMeanSquareFSig. (Combined)99.861424.9652.1260.080

Linearity9.91219.9120.8440.360

Deviation fromLinearity

WithinGroups Total

MeasuresofAssociation

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*HouseholdSizeCode

89.949329.9832.5530.058

1785.13315211.744

1884.994156

RRSquaredEtaEtaSquared

0.0730.0050.2300.053

ANOVATable

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*MaritalStatusCode

Between Groups WithinGroups Total

Sumof SquaresdfMeanSquareFSig. (Combined)338.0903112.69711.1470.000

Linearity102.0281102.02810.0910.002

Deviation fromLinearity

MeasuresofAssociation

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*MaritalStatusCode

236.0632118.03111.6740.000

1546.90315310.110

1884.994156

RRSquaredEtaEtaSquared

-0.2330.0540.4240.179

ANOVATable

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*LocalityCode

Between Groups WithinGroups Total

Sumof SquaresdfMeanSquareFSig. (Combined)126.415525.2832.1710.060

Linearity70.764170.7646.0760.015

Deviation fromLinearity

MeasuresofAssociation

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*LocalityCode

55.650413.9131.1950.316

1758.57915111.646

1884.994156

RRSquaredEtaEtaSquared

0.1940.0380.2590.067

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*LevelofEducation Code

Between Groups

ANOVATable

Sumof SquaresdfMeanSquareFSig. (Combined)108.467427.1172.3200.059

Linearity44.281144.2813.7890.053

Deviation fromLinearity

WithinGroups Total

MeasuresofAssociation

Q33[SQ001].Whenconsideringallyourpurchases ofthistype,forevery10purchasesyoumade,how manyofthesepurchasesweremadeonline?

[OnlinePurchaseFrequency]*LevelofEducation Code

64.186321.3951.8310.144

1776.52615211.688

1884.994156

RRSquaredEtaEtaSquared

0.1530.0230.2400.058

Table 6.19a - Artificial Intelligence (AI) & inferences on Advanced Technology (Mean)

Table 6.19b - Artificial Intelligence (AI) & inferences on Advanced Technology (Test Statistic)

[Researchinformationaboutthe product/service]*SexCode

[Bookameetingwithahumansales representative]*SexCode

[Ordertheproduct/service]*SexCode

[Purchasetheproduct/service]*SexCode

[Getsupportonanissuewiththe product/service]*SexCode

WithinGroups

Total

Sumof SquaresdfMeanSquareFSig.

Betwee n Groups (Combined)214.0591214.05918.8370.000

9136.20480411.363

9350.263805

Betwee n Groups (Combined)290.5791290.57923.0010.000

WithinGroups

Total

10157.01480412.633

10447.593805

Betwee n Groups (Combined)304.6001304.60026.2430.000

WithinGroups

Total

9331.83780411.607

9636.437805

Betwee n Groups (Combined)237.9401237.94020.1960.000

WithinGroups Total

9472.38380411.782

9710.323805

Betwee n Groups (Combined)82.079182.0797.3730.007

WithinGroups

Total

8950.22980411.132

9032.308805

a.Withfewerthanthreegroups,linearitymeasuresfor[Researchinformationabouttheproduct/service]*SexCodecannotbecomputed.

b.Withfewerthanthreegroups,linearitymeasuresfor[Bookameetingwithahumansalesrepresentative]*SexCodecannotbecomputed.

c.Withfewerthanthreegroups,linearitymeasuresfor[Ordertheproduct/service]*SexCodecannotbecomputed. ANOVATable

d.Withfewerthanthreegroups,linearitymeasuresfor[Purchasetheproduct/service]*SexCodecannotbecomputed.

e.Withfewerthanthreegroups,linearitymeasuresfor[Getsupportonanissuewiththeproduct/service]*SexCodecannotbecomputed.

MeasuresofAssociation

EtaEtaSquared

[Researchinformationaboutthe product/service]*SexCode

[Bookameetingwithahumansales representative]*SexCode

0.1510.023

0.1670.028

[Ordertheproduct/service]*SexCode0.1780.032

[Purchasetheproduct/service]*SexCode0.1570.025

[Getsupportonanissuewiththe product/service]*SexCode

0.0950.009

[Researchinformationaboutthe product/service]*OccupationCode Betwee n Groups

ANOVATable

Sumof SquaresdfMeanSquareFSig. (Combined)1824.10912152.00916.0170.000

Linearity307.7381307.73832.4250.000

Deviation fromLinearity 1516.37111137.85214.5250.000

7526.1547939.491

9350.263805 (Combined)2597.46612216.45521.8660.000

[Bookameetingwithahumansales representative]*OccupationCode Betwee n Groups WithinGroups Total

[Ordertheproduct/service]*Occupation Code Betwee n Groups

[Purchasetheproduct/service]* OccupationCode Betwee n Groups WithinGroups Total WithinGroups Total

Linearity512.0661512.06651.7280.000

Deviation fromLinearity 2085.40011189.58219.1510.000

7850.1277939.899

10447.593805 (Combined)2053.27912171.10717.8930.000

Linearity394.5191394.51941.2560.000

Deviation fromLinearity 1658.75911150.79615.7690.000

MeasuresofAssociation WithinGroups Total

7583.1587939.563

9636.437805 (Combined)1934.28412161.19016.4380.000

Linearity365.2581365.25837.2490.000

Deviation fromLinearity 1569.02611142.63914.5460.000

7776.0387939.806

9710.323805 (Combined)1684.24812140.35415.1470.000

[Getsupportonanissuewiththe product/service]*OccupationCode Betwee n Groups WithinGroups Total

Linearity238.2911238.29125.7160.000

Deviation fromLinearity 1445.95611131.45114.1860.000

7348.0607939.266

9032.308805

RRSquaredEtaEtaSquared

[Researchinformationaboutthe product/service]*OccupationCode -0.1810.0330.4420.195

[Bookameetingwithahumansales representative]*OccupationCode -0.2210.0490.4990.249

[Ordertheproduct/service]*Occupation Code -0.2020.0410.4620.213

[Purchasetheproduct/service]* OccupationCode -0.1940.0380.4460.199

[Getsupportonanissuewiththe product/service]*OccupationCode -0.1620.0260.4320.186

Male226.0%4011.0%349.3%246.6%5013.7%19453.3%

Female347.7%61.4%5011.3%245.4%347.7%29466.5%

18to292415.2%2415.2%3824.1%42.5%2012.7%4830.4%

30to39107.1%42.9%1812.9%2417.1%2820.0%5640.0%

40to4964.8%86.5%1411.3%1411.3%108.1%7258.1%

50to59128.3%64.2%85.6%64.2%2215.3%9062.5%

60+41.7%41.7%62.5%00.0%41.7%22292.5%

SouthernHarbourDistrict84.8%1810.8%148.4%63.6%2213.3%9859.0%

NorthernHarbourDistrict188.1%104.5%229.9%167.2%2410.8%13259.5%

SouthEasternDistrict86.0%86.0%129.0%43.0%1410.4%8865.7%

WesternDistrict1413.7%43.9%87.8%87.8%87.8%6058.8%

NorthernDistrict64.2%64.2%2819.7%128.5%85.6%8257.7%

Gozo&CominoDistrict25.0%00.0%00.0%25.0%820.0%2870.0%

11011.4%22.3%1213.6%44.5%66.8%5461.4%

2125.2%146.1%41.7%146.1%104.3%17676.5% 3125.3%208.8%208.8%20.9%3214.0%14262.3%

4148.5%42.4%3823.2%2213.4%148.5%7243.9%

5+88.3%66.3%1010.4%66.3%2222.9%4445.8%

Single2811.2%3012.0%5220.8%145.6%3012.0%9638.4%

Married/Partnered224.7%143.0%265.5%306.4%428.9%33671.5%

Seperated/Divorced47.4%00.0%611.1%47.4%1222.2%2851.9%

Widow/Widower26.3%26.3%00.0%00.0%00.0%2887.5%

MFQ200.0%00.0%00.0%25.9%00.0%3294.1%

MFQ3103.6%124.4%103.6%82.9%124.4%22281.0%

MFQ467.9%810.5%1215.8%45.3%1823.7%2836.8%

MFQ5127.3%63.7%84.9%84.9%127.3%11872.0%

MFQ686.0%86.0%3626.9%107.5%1410.4%5843.3%

MFQ7&82016.1%129.7%1814.5%1612.9%2822.6%3024.2%

Legislators,Executives&SeniorManagers68.7%1014.5%811.6%913.0%45.8%3246.4%

Science,Eng.&OtherSpecialisedProfessionals2013.2%74.6%2214.5%127.9%2013.2%7146.7%

AssociateProfessionalOccupations811.0%34.1%1013.7%1317.8%1723.3%2230.1%

ClericalSupportWorkers48.9%24.4%817.8%48.9%48.9%2351.1%

ServiceandSalesWorkers23.2%00.0%23.2%23.2%914.3%4876.2%

Skilledagricultural,forestryandfisheryworkers00.0%00.0%00.0%00.0%2100.0%00.0%

Craftandrelatedtradesworkers00.0%210.0%00.0%420.0%00.0%1470.0%

Plantandmachineoperatorsandassemblers00.0%00.0%425.0%00.0%637.5%637.5%

Elementaryoccupations220.0%00.0%00.0%00.0%220.0%660.0% Armedforcesoccupations00.0%210.0%00.0%210.0%420.0%1260.0% Retired/Pensioners00.0%21.8%21.8%00.0%21.8%10894.7% HomeCarers/NonGainfullyOccupied43.2%00.0%43.2%00.0%00.0%11693.5%

b.

Table 6.20a - AI for Personal Use (Count & Row %)

Table 6.20b - AI for Personal Use (Test Statistic)

Male308.2%328.8%369.9%205.5%82.2%23865.4%

Female306.8%327.2%306.8%204.5%61.4%32473.3%

18to292616.5%3421.5%3019.0%106.3%42.5%5434.2%

30to391410.0%107.1%2014.3%1410.0%21.4%8057.1%

40to4986.5%108.1%129.7%108.1%64.8%7862.9%

50to5985.6%106.9%00.0%21.4%00.0%12486.1% 60+41.7%00.0%41.7%41.7%20.8%22694.2%

SouthernHarbourDistrict148.4%148.4%127.2%169.6%63.6%10462.7%

NorthernHarbourDistrict125.4%2410.8%188.1%83.6%41.8%15670.3%

SouthEasternDistrict86.0%129.0%86.0%00.0%00.0%10679.1%

WesternDistrict1615.7%00.0%1211.8%22.0%00.0%7270.6%

NorthernDistrict85.6%149.9%1611.3%107.0%42.8%9063.4%

Gozo&CominoDistrict25.0%00.0%00.0%410.0%00.0%3485.0%

166.8%22.3%1415.9%44.5%00.0%6270.5% 2125.2%167.0%83.5%104.3%62.6%17877.4% 3187.9%2812.3%83.5%83.5%20.9%16471.9% 4169.8%127.3%2213.4%169.8%00.0%9859.8% 5+88.3%66.3%1414.6%22.1%66.3%6062.5%

Single3212.8%4016.0%4216.8%187.2%62.4%11244.8%

Married/Partnered245.1%204.3%183.8%204.3%81.7%38080.9%

Seperated/Divorced47.4%23.7%611.1%23.7%00.0%4074.1%

Widow/Widower00.0%26.3%00.0%00.0%00.0%3093.8%

MFQ225.9%00.0%00.0%00.0%00.0%3294.1%

MFQ3124.4%82.9%103.6%41.5%00.0%24087.6%

MFQ467.9%1418.4%1621.1%22.6%810.5%3039.5%

MFQ5106.1%63.7%127.3%21.2%00.0%13481.7%

MFQ664.5%1611.9%1611.9%86.0%43.0%8462.7%

MFQ7&82419.4%2016.1%129.7%2419.4%21.6%4233.9%

Legislators,Executives&SeniorManagers68.7%1014.5%1318.8%45.8%00.0%3652.2%

Science,Eng.&OtherSpecialised Professionals 1811.8%159.9%2214.5%106.6%42.6%8354.6%

AssociateProfessionalOccupations1013.7%56.8%34.1%1216.4%22.7%4156.2%

ClericalSupportWorkers48.9%1226.7%00.0%00.0%00.0%2964.4%

ServiceandSalesWorkers23.2%23.2%23.2%00.0%00.0%5790.5%

Skilledagricultural,forestryandfishery workers

00.0%00.0%00.0%2100.0%00.0%00.0%

Craftandrelatedtradesworkers210.0%00.0%00.0%420.0%00.0%1470.0%

Plantandmachineoperatorsandassemblers00.0%212.5%00.0%00.0%212.5%1275.0%

Elementaryoccupations220.0%00.0%00.0%00.0%00.0%880.0%

Armedforcesoccupations00.0%00.0%210.0%210.0%210.0%1470.0%

Retired/

Home

Resultsarebasedonnonemptyrowsandcolumnsineach innermostsubtable.

*.TheChi-squarestatisticissignificantatthe.05level.

b.Morethan20%ofcellsinthissubtablehaveexpectedcell countslessthan5.Chi-squareresultsmaybeinvalid.

c.Theminimumexpectedcellcountinthissubtableis

than one.Chi-squareresultsmaybeinvalid.

Table 6.21a - AI for Work or Professional Life (Count & Row %)

Table 6.21b - AI for Work or Professional Life (Test Statistic)