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LESS ARTIFICIAL, MORE INTELLIGENT

How can brands use intelligent technologies to bring their customer relationships to life?


PROJECT DECLARATION This submission is the result of my own work. All help and advice other than that recieved from tutors has been acknowledged and primary and secondary sources of information have been properly attributed. Should this statement prove to be untrue I recognise the right and duty of the board of examiners to recommend what action should be taken in line with the University’s regulations on assessment contained in its handbook. SIGNED PRINTED NAME DATE

ETHICS CLAUSE I confirm that this work has gained ethical approval and that I have faithfully observed the terms of approval in the conduct of this project. SIGNED DATE WORD COUNT: 7948

ALICE WALKER N0673122


CONTENTS Introduction

1.1 Report Introduction..........................................................................1 1.2 Rationale..........................................................................................1 1.3 Aim & Objectives..............................................................................2

Literature Review

2.1 Introduction......................................................................................3 2.2 Improved Quality of Life.................................................................3 2.3 Illusion of Intimacy..........................................................................4 2.4 Privacy and Security Concerns......................................................5 2.5 Human Hacking...............................................................................5 2.6 Increasing Brand Equity..................................................................6 2.7 Who Will Benefit?.............................................................................7 2.8 Research Gap Analysis...................................................................7

Methodology

3.1 Research Approach.........................................................................9 3.2 Sample.............................................................................................9 3.3 Secondary Research.....................................................................10 3.4 Primary Research....................................................................11-13

Friend Not a Therapist

4.1 Introduction....................................................................................15 4.2 Where is the Line?........................................................................15 4.3 The Consumer Trust Crisis...........................................................16

Fear of the Unknown

5.1 Introduction....................................................................................18 5.2 Black Box Effect.......................................................................19-20 5.3 Pre-Conceived Paranoia...............................................................21 5.4 Subconscious Data Sharing.........................................................22

The Future

6.1 Introduction....................................................................................23 6.2 Pessimistic vs Optimistic Outlook...............................................23 6.3 Innovative Consumer Relationships...........................................25 6.4 Reaping the Rewards....................................................................27

Conclusion

7.1 Key Insights....................................................................................29 7.2 Conclusion......................................................................................29 7.3 Recommendations.........................................................................30

References

8.1 References................................................................................31-32 8.2 Bibliography..............................................................................33-37 8.3 List of Illustration.....................................................................38-39 8.4 Appendix..................................................................................40-71


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INTRODUCTION


1.1 Introduction

1.2 Rationale

In the era of unlimited choice, artificial intelligence (AI) has the potential to provide highly personal experiences in an impersonal environment. However, being personal isn’t enough, personalisation must be experienced as relevant and inventive by offering surprising and complementary items, done in a way that isn’t intrusive. Therefore, this report aims to investigate the consumer consequences/ opportunities of using AI and emotional intelligence (EI) as a tool to enhance brand’s customer relationships. A literature review will firstly be presented with a thorough exploration into relevant theories and debates surrounding this topic through academic sources to then structure the methodology for primary research. key findings from research will then be highlighted to discovered meaningful insights and spark inspiration going forward into stage two

AI can turn large data sets into enriched information that can be used to improve the retail industry from sales to customer service (Business of Fashion, 2018). Intelligent personal assistants (IPAs) have provided a route for AI to be accepted into the home and this market is growing in popularity “the worldwide IPA market will grow 32.8 percent a year from 2016-2024” (Transparency Market Research, 2016). The future of this technology shows EI being combined with AI by analysing emotive signals from facial expressions, voice intonation and behavioural patterns to significantly enhance user experience (Gartner, 2018). This will go beyond the traditional areas of machine learning into creative customer interaction, blurring the line between technology and creativity. However, to maximise the adoption of this technology, further investigation surrounding the research and debates of this topic is required. The world is at a pivotal moment of collectively deciding how the benefits of AI can be shared throughout society. Before intelligent technologies are fully adopted into everyday life, irreversible impacts need to be considered in order to achieve efficient and ethical adoption. The use of AI is transforming retail and holds the possibility of disrupting the fashion industry entirely. Fashion is expected to be the digital frontier in demonstrating the potential of breakthrough AI innovations. According to Accenture (2018), AI systems will boost profitability in the retail sector by 60% over the next two decades. To remain relevant, it will become a necessity for brand to integrate AI into every aspect of their business strategy or face marginalisation. Ultimately, this report is crucial in determining how to reap the benefits of technology without jeopardising consumer’s rights and privacy. .

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1.3 Aims & Objectives Aim: To investigate the consumer consequences/ opportunities of using AI and EI as a tool to enhance brand’s customer relationships. The following objectives have guided the research to accordingly achieve the overall aim of this project. 1) To understand how AI and EI can encourage/ discourage customer engagement and the societal impacts this will create. 2) To explore consumer acceptance/rejection towards intelligent technologies acting as an assistance in building customer relationships.

How can brands use intelligent technologies to bring their customer relationships to life?

3) To investigate consumer’s attitudes in relation to how much their personal devices know about them and their privacy and security concerns due to this. 4) To determine how brands can use AI and EI to understand their consumer and offer valuable individualised experiences to their strategies. . .

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LITERATURE REVIEW 2.1 Introduction AI can turn large data sets into enriched information that can be used to improve the retail industry from sales to customer service (Business of Fashion, 2018). The future of this technology shows emotional context being combined with AI to go beyond the traditional areas of machine learning into creative customer interaction. However, to maximise the adoption of this technology, further investigation surrounding the research and debates of this topic would need to be required. Therefore, this literature review aims to critically analyse the consequences as well as the opportunities that this technology will provide companies and consumers. The most relevant theories around this subject have been identified through academic sources to evaluate what research is already existing to direct further specific research that needs to be conducted. The scope of this review includes the global market and societal impacts of the use of AI and EI whilst primarily focusing on the retail industry .

2.2 Improved Quality of Life

“Everyone is born with the potential to live happy, fulfilled lives, but most people find it difficult to attain the potential” (Pieper, 2005, p.3). Weaver (2014) argues that AI can be used to attain this potential and improve the quality of human life, giving us more time for friends, family, and personal development. He explains that AI is already established and its reach will be extended, meaning that society should make sure that we properly guide its adoption through public policy decisions, regulations and laws. “We are about to see an explosion in weak AI products

that are commercially available. In the next 10 to 20 years, AI will permeate our lives thoroughly, from the way we travel to the media we consume to the tools in place to police our streets.” (Weaver, 2014, p.4)

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Historically, societies with greater constraints did not leave much scope for personal development but now due to technological advancement, modern society has been liberated and the need to achieve selfactualisation is becoming heightened (Carr, 2013). This deep consumer need can be explained through Maslow’s hierarchy of needs (1987) (see Appendix 15), a motivational theory in psychology that puts self-actualisation at the top of the pyramid. Today, intelligent technologies serve to accelerate consumers already fast-paced lives even further (Weaver, 2014). One factor of improving a human’s life, would be optimal decision making. In today’s society, the problem surrounding decision making is that it is usually too complex to be applied successfully through a single context or point of view (Doumpos, 2013). Phillips-Wren (2013) expands on this point, explaining that decision making is a fundamental human activity and people make both good decisions and poor decisions but with the help of technology, this will be the most effective way to assist people in arriving at a ‘good’ decision. Hess (2011) also supports this claim, arguing that better decisions can be achieved by shifting decision-maker’s intuition with a more extensive data collection and analytical processes, enabling the decisionmaker to construct relevant plans of action. While the emergence of the modern technology has had positive impacts on the one hand, it has also raised the issue of whether it has hindered personal independence, resulting in humans (mainly children) becoming too reliant on technology and outsourcing decision making. Research to support this argument was led by Anna Vollmer (2018) at the University of Plymouth which showed that young children are significantly more likely than adults to have their opinions and decisions influenced by robots. When asked a question, adults were mostly able to resist being persuaded by robots, however, children were more likely to give the same responses as the robots, even if they were obviously incorrect. This was a worrying finding as in the near future when autonomous social robots are used as help for education or child therapists, the robot is in a position in which the information provided can significantly affect the child. Therefore, a discussion is required about whether protective measures, such as regulatory frameworks, should be in place that minimise the risk to children during social child-robot interaction.


2.3 Illusion of Intimacy As personal devices come to have human-like interfaces, researchers have explored the existence of the emotional connection between people and their devices (Louie et al, 2014). A key researcher, Han (2018), explains the parasocial relationships (PSR) theory as an appropriate way to understand how this emotional closeness to such technology exists, suggesting that people may perceive humanlike computers (particularly IPAs) as a source of personal communication, implying the potential for friendship. His findings proved that interpersonal attraction (task attraction and social attraction) and security/privacy risks are important factors affecting the adoptions of IPAs, as shown in the diagram below. Although, there were some limitations to his methodology as the data was only based from users in the USA and the differences among the survey respondents were not examined. Nonetheless, the fundamental conclusion of the research is that IPA manufacturers should focus on the improvement of natural language processing and AI technologies to communicate with humans in a realistic way.

The importance of “humanness” within IPAs is extremely necessary to create human-like conversational flow and certain IPAs are able to joke with users to create a more relaxed relationship (Han, 2018). Weaver (2014) agrees with this as he explains that;

“the human brain is built for speech, so anything that sounds like a voice, our brains lights up and we get an enormous range of social and other responses” (p. 6). This will allow IPAs to work more effectively with speech and add human value to their interactions. Han (2018) suggests in the future that sensors and cameras will be added to IPAs to collect contextual information such as temperature, or to distinguish between visitors and residents when providing more situation-relevant information to users. Thus, allowing these technologies to become even more intelligent and blurring the boundaries between man and machine. However, Adolphs (2012) argues that manufacturers need to engineer an internal processing architecture that goes beyond fooling humans into thinking that the robots have emotions. He suggests whether the program is truly intelligent”or just a bag of tricks exploiting a large database and fast computing. Although, the date of this reference needs to be taken into consideration as it is slightly out of date and the technology back then may have been less understood. Little academic research has been done to examine the issue of a social relationship between the IPA and its user, therefore this will be explored deeper when conducting primary research.

PSR Theory

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2.4 Privacy and Security Concerns

2.5 Human Hacking

Botsman (2017), explains the “trust leap” theory, a societal movement from a known situation to an unknown one. She gave the example of “when trains began, people believed men’s bodies would melt at 80mph…people then weren’t ready to take the trust leap” (p. 21). Watcher (2018) explains that this can then be applied to today’s technology, specifically IPAs as their algorithms automatically build complex models based on big data, so the people using them cannot explain why or how a conclusion is reached, therefore, supporting Botsman’s view of it being an unknown situation and having to rely on the “trust leap”. Han (2018) argues because of central cloud systems, consumers are increasingly concerned about their personal information being leaked through their online applications. This loss in trust can cause a reluctance of interacting with a device as explained by Moorthy and Vu

Huge increase in the sophistication of neuroscience has been seen in recent years as well as the revolutionary development of computer technology (Adolphs, 2012). This has led to controversy concerns surrounding the ethical and moral implications of utilising these technological advancements (Carr, 2013). In 2018, Gartner, a global research incorporation, released a shocking statement: “By 2022, personal devices will know more about an individual’s emotional state than his or her own family”. Gartner goes onto explain that everyday objects are utilising affective computing and emotional and artificial intelligence to detect, analyse, process and respond to people’s emotional states and moods. It is not only our voices that are being analysed but also our facial expressions to recognise emotions (Knight, 2016). This raises the question of where technology oversteps the line of hacking the human brain?

“IPA users were more cautious in disclosing private info than non-private info, and emphasized privacy concerns as one of the major reasons for not using IPAs” (2015, p. 307).

Yuval Noah Harari is a historian who strongly agrees with how technology is resulting in human hacking. He says the algorithms are watching everyone, where they go, what they buy, who they meet, and soon they will monitor all their steps, breaths and heartbeats. If the algorithms understand what’s happening within their user better than they do, the authority will shift to them (Harari, 2018). This opinion may be biased as it is coming from one person’s perspective who is also a best-selling author and is therefore going to sell his opinion in the most convincing way. However, it still highlights main consequences of continuously allowing technology to learn from their users, consequently, there needs to be regulations set in order to control computer understanding in the future.

Possible solutions to gain back trust are explained by Han (2018) who suggests that IPA manufacturers should invest in strengthening security technologies and providing strong internal policies to prevent information leakage. However, Watcher (2018) argues that the focus needs to be on integrity as consumers are wanting reassurance that a company’s intentions are aligned with the wellbeing of people in society and that is how to achieve integrity at scale. Therefore, primary research will be conducted to determine the urgency of what solution should be executed first in order to gain trust in the most effective way.

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2.6 Increasing Brand Equity Aaker (1991) states that brand equity plays a key role in the success of a firm. Leveraging intelligent technologies within brands can improve performance in communication, responsiveness and customer service and in turn, leading to positive brand associations (Rodriguez, 2018). This correlation between improved performance and value to the customer is explained through Aaker’s brand equity model (1991) (see Appendix 14) and as Rodiguez (2018) argues, intelligent technologies can improve this responsiveness to benefit both the customer and brand value. Customers’ expectations are always rising, and sometimes companies struggle to keep up, but by taking the time to invest in new technology, companies can rapidly create valuable new customer experiences, manage them cost-effectively and continue evolving them to keep pace with a rapidly changing world (Business of Fashion, 2017.) Therefore, the adoption of technology in brands is crucial in order to stay relevant to customers whilst also increasing brand loyalty and competitive advantage.

One of the major factors effecting brand equity is the new customer expectation of hyper personalisation and this can be attained by AI and big data so e-commerce platforms can make an impersonal environment seem highly personal with tailored products, personalised recommendations, and smarter supply chains. This then raises the question of how much data are consumers willing to hand over in order to gain more tailored experiences from brands. According to a Salesforce UK survey (2017) consumers are happy to hand over data to receive tailored experiences with 63% of UK customers say being sent personalised recommendations has a direct influence on their loyalty. To connect with these empowered consumers, companies need their experiences to be unique and effective however many seem to struggle with turning customer data into intelligent and action-able insights (Business of Fashion, 2017). This can be a source of differentiation and brands can leveraging data with intelligent technologies to provide cuttingedge individualised curation that takes into account purchase journeys and customer feedback; to increase relevance of their branding and contextual channels. This is supported by Mckinsey & Company (2017) that found that targeted communications, which are relevant and useful, could create lasting customer loyalty and drive revenue growth of 10 to 30 percent. They also state that in nearly two-thirds of the cases of customers switching from one brand to another, it’s because they’re looking for a more relevant product, service or experience. This debate of how much data consumers are willing to hand over will be further questioned in primary research.

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2.7 Who Will Benefit? As previously mentioned, the need for consumer data raises the ethical argument of who actually benefits from this acceptance in technology and sharing of personal information? Is it to meet the new expectations of consumers and fulfil their needs or are brands exploiting their customers? Weaver (2014) argues that there is no economic law that says everyone has to benefit equally from increased productivity. He explains that jobs are lost to AI, new jobs aren’t created to replace those jobs and the wealth of AI is only in the hands of the few people who own the programs, resulting in economic inequality. Leonardi (2004) also supports this claim with his theory of technological determinism;

“Leaders in high-tech organizations use the story of technological determinism as a discursive practice through which they invoke the “inevitability” of technology to justify managerial decisions to the public” (Leonardi, 2004, p.615.) Therefore, rather than taking ownership of certain actions, managers use this story to claim that certain business changes are inevitable to produce an appealing picture of the brand for various people (customers, shareholders, governments), and to then benefit the company not the consumer. This could relate to algorithms that understand consumers better than they understand themselves, AI could predict their choices and desires to manipulate them into purchasing (Harari, 2018). However, personalisation doesn’t only benefit the brands battling for market share; customers also benefit from sophisticated algorithms. AI, for example, can operate chatbots that mimic consumers’ interaction with a customer-care assistant, making online assistance available outside of business hours (Business of Fashion, 2017). Customers don’t care about retailer’s problems, they care about finding the right product at the right time and AI can help provide that (Lui, 2018). The Business of Fashion (2017) even argues that consumers don’t generally think about the technologies they use and often, they don’t even notice them, therefore, intelligent technology and data will make consumers lives smarter and friction free. The trade for an increasingly personalised service on platforms, however, is customer privacy:

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“Privacy is like currency. Consumers are ultimately going to send that currency to brands and retailers they feel they can trust. It’s going to become a basic business attribute that if you want to be successful and you want to have close, loyal relationships with customers, you’re going to have to prove to them that you respect their information and that you will treat it with care,” (Stephens, 2018) As explained previously in the “Privacy and Security Concerns” segment, Watcher (2018) supports this claim by saying consumers are asking for reassurance that a company’s intentions are aligned with the wellbeing of people in society. Thus, brands need to make their intentions clear and have strong values in what they stand for. If consumers want tailored recommendations they will have to give up some data in order to get to that point and the companies that are more transparent and trustworthy will gain this valuable data.

2.8 Gap Analysis This in-depth use of academic research has been crucial in understanding how AI and EI effects customer relationships and the societal impacts it will create, therefore achieving the first research objective in this theoretical framework. It has also highlighted further need for investigation in any gaps of knowledge whilst assessing the importance of primary research. A key gap in research is investigating how to reap the benefits of technology without it jeopardising consumer’s rights and privacy. This will be explored in primary research by analysing what data is stored on people’s phones and their attitudes towards this. It is also clear that there is possibility of a technology backlash unless people understand that there are challenges but also opportunities. There are gaps in knowledge surrounding how to explain why we should be optimistic about the future of technology and primary research will be conducted in order to determine how to turn pessimistic views into an optimistic outlook.


METHODOLOGY

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3.1 Research Approach

3.2 Sample

After critically analysing existing academic research and identifying the gaps in knowledge, these gaps will be explored through a multi method design approach of both qualitative and quantitative research, through the process of triangulation. “Triangulation is the use of two or more independent sources of data methods within one study” (Saunders et al, 2009, p.602). Each research method will meet a specific objective in order for this report to have a direct focus and coherent outcome whilst also following a sequential exploration strategy to discover insights and recommendations for Stage 2.

Selecting a sample is crucial as it would be impractical to collect data from the entire population (Saunders et al, 2009). As mentioned in the research approach it was difficult to attain a large sample size due to time and budget constraints, although, it is also beneficial in making the analysis precise. The sample for this research includes male and females aged 20-30 that are 70% early adopters in technology and 30% late majority, in order to focus on dedicated users of personal devices but also explore the perception of those who may be more cautious to then gain insights from both sides of the research question.

“An exploratory study is a valuable means of finding out what is happening; to seek new insights; to ask questions and to assess phenomena in a new light” (Robson 2002, p.59).

This sample overlaps between millennials and GenZ which highlights a limitation of not having a specific demographic group when using secondary research to understand their societal attitudes. However, the individualisation trend has led to consumers not wanting to be categorised or prejudged based on what society labels them, therefore, this sample size represents a combination of these demographics and reflects the true bricolage way of living. This age range shares the term of digital natives which has resulted in them being fast movers, liking information at their fingertips and interactivity. They also put a big focus on self-development and changing the world whilst also being concerned about the future (Ypulse, 2018). Consequently, this relates well with the subject of intelligent technologies as they are thought to enjoy this innovation in technology but also don’t trust the long-term effect.

The overall limitations of this research approach included limited time constraints and no financial support which proved difficult when conducting both primary and secondary research. Without these limitations, data could have been collected at a greater scale and insightful exploration could have gone deeper into the issue being researched to strengthen recommendations. However, this allowed for the analysis to be highly targeted and precise to the specific sample. The ethical principles of honesty, duty of care and respect have all been considered whilst undertaking this research and each method has gained ethical approval.

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3.3 Secondary Research Literature Review: To begin the research process a literature review was crucial to gain an extensive understanding of AI and EI and meet the objective of how it can encourage/discourage customer relationships and the societal impacts it will create. This included critical analysis of academic journals, books, case studies, news articles and industry reports to highlight the key themes surrounding the topic and any gaps in knowledge that would lead onto primary research. The advantages of this method include saving resources like time and money (Ghauri and Gronhaug, 2005) and complex issues and theories surrounding the topic can be clearly analysed. It also presents far larger data sets that are higher-quality than personal primary research (Stewart and Kamins, 1993) meaning that a wide scope of professional ideologies can be identified efficiently. Limitations: The research question could only be partially answered from the use of secondary research as primary research was needed in order to fill the gaps in knowledge. However, these gaps were clearly identified, therefore it was an extremely beneficial approach to be able to focus the primary research specifically to the unidentified knowledge. This links to the other limitation of it being very time consuming and therefore not leaving a lot of time to conduct primary research due to the time constraints of the project. Thus, the use of precise criteria needed was vital in gathering the data in a small time frame. Saunders et al (2009) also argues that due to these documents being revisited over time, definitions may differ and represent the interpretations of those who wrote them, rather than offer a true reflection of reality. Deliberate distortion could also occur to play down negative comments to make the service appear better. Therefore, this was taken into consideration when using data from organisations who may have unreliable intentions.

Case study: Robson (2002) defines a case study as “a strategy for doing research which involves an empirical investigation of a particular contemporary phenomenon within its real life context� (p.178). Therefore, case studies were utilised in this report to add context and showcase innovative implementation of brand strategy. One example of a case study was combined with an expert interview from the owner of the case study brand to triangulate multiple sources of data. Case studies are useful in exploring existing theories and a valuable tool for explaining how these theories are being successfully implemented into everyday life. Two case studies were analysed to examine their success but also highlight possible improvements that could be made. Limitations: Case studies have an unscientific feel (Saunders et al, 2009) meaning that when trying to prove a hypothesis the evidence it offers will not be convincing enough on its own. This can be improved by triangulation, by combining the case study with a different research method and as mentioned previously, this was carried out with an industry expert interview. A specific limitation to this report includes the premature nature that it reflects, therefore it proved difficult finding case studies that had already been tried and tested as lots of the businesses strategies relating to this topic are not commercially available yet.

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3.4 Primary Research Survey: A deductive approach was then carried out when undertaking primary research. The first method was a quantitative online survey which allowed for a large collection of data from a sizeable population in a highly economical way (Saunders et al, 2009). It also was easy to compare results and visualise insights from a graph or percentage. The survey used a rating scale design to avoid yes/no answers and gain deeper understanding. The sample for the survey was a total of 53 respondents both male and female aged 16-50. Limitations: “There is a limit to the number of questions that any questionnaire can contain” (Saunders et al, 2009, p.144). Because of this, it limited the length of questions or open ended responses as people tend to get impatient. These findings will consequently be supported with indepth interviews to gain a deeper understanding with more explanation on consumer attitudes. It was also challenging to receive a high number of respondents due to the specific period the survey was release (1st December- 10th January). This resulted in the sample being untargeted and unspecific in order to get as many respondents as possible. The total respondents were still low meaning the findings were not completely representative, although they still offer first hand evidence when supporting a claim. . Focus Group One: Carson et al (2001) refers to the term “group interviews” where the topic is clearly defined and there is a focus to enable interactive discussion between participants. They are more time efficient than 1 to 1s as the interviewee can address a larger number of individuals at once and it offers more complex behaviour and attitudes as participants can interact with each other. “Members interactions are both encouraged and more closely controlled to maintain focus” (Saunders et al, 2009, p.347). Two focus groups were carried out to meet the objective to explore consumer attitudes towards AI and EI acting as an assistance in selfdiscovery. Focus group one included six females aged 20-23 who are all early adopters in technology. Limitations: A common limitation in a focus groups is that people can often dominate the conversation, leading to insightful responses sometimes being missed from quieter members in the group. This was controlled when undergoing the focus group research by using audio recording to then give more opportunity to manage and control the process rather than writing down the responses. “It is difficult to manage the process and note key points as well. This can be overcome by audio recording (Saunders et al, 2009, p.346).

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Focus Group Two: A second focus group was conducted in order to compare results and record more consumer attitudes. This focus group however included a visual stimulus of the Amazon Echo Look advert to gain initial responses from the participants and create a more interactive environment. It also corroborated the Amazon case study to discover improvements from the consumer point of view. This focus group sample included four females and one male participant aged 20-21 half of which were early adopters and the other half were late majorities. Limitations: The split of early adopters and late majorities resulted in some friction of opinions. The late majorities conclude the overall reactions to be mainly negative when relating to technology and therefore the others in the group might have held back in what they truly think because they didn’t want to be judged. Consequently, the first focus group is beneficial to compare results and also to not rely on one groups findings. In-depth Interviews: “Interviews gather valid reliable data that are relevant to your research question” (Saunders et al, 2009, p.318) Therefore, one to one interviews were recorded to investigate consumers’ acceptance/rejection in relation to their personal devices knowing more about them than themselves. Visual stimulus of personal phone security was used to spark raw reactions in how they felt towards their devices knowing so much about them. The research was semi-structured and emotional questions like “how does that make you feel” were asked to gain a qualitative, deeper understanding. Two males were interviewed aged 21 and 23 and one female aged 20. Limitations: Participants sometimes are only willing to give monosyllabic answers like yes or no, although, this was controlled by asking openended, emotive questions as stated before. Another limitation is that the process is very time consuming and a lot of explanation of technical meaning had to be stated for the participant to understand. however, the depth of data received from the interview makes it worthwhile. Because this sample size was small it is not necessarily representative of what society truly believes, therefore it will be supported with secondary research in order for the findings to be credible.


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Alexa Conversation: Over the space of a month, the Amazon Echo Alexa conversations from a 20 year old male was recorded to investigate how these technologies and theories were being carried out in the commercial world of everyday life. The app documents each interaction the user has with their Alexa, therefore, it was useful to be able to go back and analyse the most popular commands. Limitations: The results gained from this method were fairly unambiguous as it was factual evidence of how the user was utilising their device with no follow up questions to understand why. The deeper meanings behind the command were therefore left to the unknown with no supporting evidence of justification. However, it still created effective results and statistics that could be measured. Answer The Public: The online tool of “Answer the Public” was used to gain quantitative evidence of what questions and queries consumers are searching for in Google. The key phrases: “is technology” and “is AI” were put into the system and a visual report of statistics were presented. It resulted in a large sample size to make the results generalisable and offer an up to date, macro view of consumer perceptions. Limitations: Because the results were only quantitative, it failed to shed a light on the full complexity of the consumer perceptions. Therefore, it revealed what / to what extent, but it was unable to explore why or how. These answers will then be supported with qualitative in-depth interviews to understand the why and how. Expert Interviews: Two experts in the field of AI were reached out to and interviewed to determine how brands can use AI to understand their consumer and offer human value to their strategies. Professional knowledge was gained on the subject area and context was added on how to apply it. One interview in particular was supported with a case study as they were the owner of the case study brand which offered triangulation of data.

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Limitations: A limitation to this method includes the progress of research being delayed due to dependence on others for information. The Interviews may last a few weeks as there is a time delay between a question being asked and it being answered however, this can be advantageous as it “allows both the interviewer and the interviewee to reflect on the questions and responses prior to providing a considered response” (Saunders et al, 2009, p.351). The possibility of answers being biased had to be considered as one of the experts is an owner of a brand utilising AI. Thus, their responses could have unreliable intentions and be biased to make their service appear better. Instagram: An Instagram poll is an appropriate method of research to be reached globally and have quick and easy responses. Therefore, the last quantitative research method conducted was an Instagram poll to be used to support any other claims found in other qualitative research. It was available for only 24 hours and received 68 responses from both male and female participants. Limitations: Due to the fast-paced environment of social media the poll was only available for 24 hours which limited the number of respondents. Although, this meant the research could be completed quickly and efficiently with more time to analyse the results. It also limited the demographic able to take part as not everyone has access to Instagram and the people who did take part couldn’t be controlled to a specific sample size as it was available to everyone. This resulted in the responses not being very specific or relating to a controlled demographic.


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RESEARCH FINDINGS: FRIEND NOT A THERAPIST

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4.1 Introduction A key gap found in the academic research was how to exhaust the benefits of technology without risking consumer’s rights and privacy. Therefore, this was a fundamental topic of discussion when conducting primary research. The findings relating to rights and privacy seemed to spark high consumer frustration with how there is a constant battle between wanting individualised experiences without the risk of personal information being misused or consumers being exploited. How personal is too personal will be analysed from primary research and why consumers are losing faith in brands due to confusing intentions will be reflected upon.

4.2 Where is the Line? There have been multiple discussions surrounding where technology crosses the intrusive barrier, yet to pin point where exactly that is proved difficult to determine. When shown examples of how EI could be implemented into personal devices, the first focus group conducted (see Appendix 2) held strong opinions of this being particularly unsettling and invasive to their personal emotions. Participant 2 stated “imagine if your phone texted you telling you you’re pregnant (laughs) I’d be terrified.” The term “terrified” insinuates a strong negative perception of EI capabilities. Participant 1 then suggests that technological interaction “should be like a friend that knows you but doesn’t know everything about you” supporting the consumer need to this chapter title of personal devise being a friend not a therapist. An interview from an AI and big data expert provided a solution of “using less and less consumer (personal) data in AI solutions to still be effective without overstepping the line.” They also explained not to underestimate regulations like GDPR for setting boundaries from a legal perspective. This was a critical factor in the STEEPLE analysis (see Appendix 13) of modernising laws to protect the personal information of individuals (Burgess, 2018) which is a step in the right direction of controlling intrusive technology at scale.

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Both brands and consumers need to find a common ground in privacy, especially with new consumer expectations resulting in the need for highly tailored recommendations, raising the debate of “how personal is too personal?” These new consumer expectations are supported in the literature review: “63% of UK customers say being sent personalised recommendations has a direct influence on their loyalty” (Salesforce, 2017). Whilst focus group 1 (see Appendix 2) also resoundingly agreed that they would rather see a useful advert than one that doesn’t apply to them. When focus groups one and two were questioned about the Spotify 2018 “my year in review” campaign (see Appendix 2&3) they both found it extremely interesting finding individualised information about their listening habits. This was due to the detachment of emotional information to statistical findings which therefore wasn’t overstepping the line into emotive understanding. “I loved the Spotify 2018 round up because it wasn’t too personal”, “because it’s a matter of statistics, it wasn’t personal”, “its music, not data about me as such”. This an effective example of how to be relevant without being intrusive

“It should be like a friend that knows you but doesn’t know everything about you.”


4.3 Consumer Trust Crisis

Instagram poll percentage of 68 respondents who trust/ don’t trust their personal devices

“Consumers aren’t becoming less trusting in technology but are becoming more aware of the value of their private information and how It can be misused.”

Results from the Instagram poll presented that 75% of 68 people don’t trust their personal devices with how it stores their information (see Appendix 11). This is supported with findings from focus group two (see Appendix 3) as when asked about how their personal devices knowing information about them mades them feel, the most common words were “uncomfortable/ unsafe/creeped out/intruded”. Participant 1 explained: “I trust the device, I just don’t trust the things behind it, the stuff I can’t see”. This lack of transparency relates to Botsman’s Trust Leap Theory (2017) which is explored in the literature review, supporting the reluctance of sharing personal data due to the fear of where it might be stored. This claim is supported in the one to one interview (see Appendix 5) as the data shown to the participant of how much personal information is stored on their phone shocked them. The participant argued that Apple “should definitely make people more aware of their privacy”. However, in focus group two, participant 1 explained that in terms of handing over data “it depends on the brand, whether I trust them or not”. Therefore, the credibility and relationship the consumer has with a brand are huge factors in whether they share their information with them or not. An interview with the owner of the case study brand “Facenote” argues that “consumers aren’t becoming less trusting in technology but are becoming more aware of the value of their private information and how It can be misused.” Thus, brands need to always prioritise integrity being at the centre of their core values if they are to maintain access to data. The leaders of the pack will then leverage data and technology to provide individualised experiences and tailoring for consumers (Business of Fashion, 2018).

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FEAR OF THE UNKNOWN

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5.1 Introduction Technology used to be a source of wonder and excitement for the future but due to the rate at which it is advancing, the complexity of these algorithms are quickly becoming dangerous and powerful in the eyes of the public. This fear of the unknown plays a crucial part in investigating the acceptance/ rejection of intelligent personal devices and data sharing. Therefore, this section of the report will aim to evaluate primary research findings on why a lack of understanding has resulted in consumer fear and what this means for brands bringing intelligent technologies into the home.

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5.2 Black Box Effect To arrive at AI decisions, machine learning algorithms build highly complex models based on data sets, resulting in the end user not being able to explain why or how a conclusion is reached making the device a black box (Wired, 2018). An expert in the field of AI backed this claim during the primary research interview. He stated: “AI is still a black box. Why is the algorithm doing what it is doing? As an example, we have a guiding principle of ’no to black box, yes to glass box’”. He further explains that consumers want to know and understand why AI is doing what it is doing to then have control to quality assure the process. In the online survey (see Appendix 1) 32% of respondents owned a home assistant but 68% did not and when asked why participants thought they were “pointless” and “unsure it would be worth the money”. This demonstrates a lack of understanding of how these devices work which then shows a reluctance to purchase or even try the product. Although, this could be personal preference of simply not being interested in the product. In focus group one (see Appendix 2) when asked about the quote “By 2022, personal devices will know more about an individual’s emotional state than his or her own family” (Gartner, 2018), participant 6 found the concept very difficult to understand “I don’t actually believe that’s very true” proving how unaware some users are of technological systems resulting in finding it hard to believe.

“No to black box, yes to glass box.”

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The black box effect can be applied to the case study of the new Amazon Echo Look, “a hands-free camera and style assistant that helps you look your best” (Amazonfashion, 2018). It is one of the newest additions to Amazon’s line of Echo-branded devices that uses voice activation to see yourself from all angles, then build a personal lookbook of your outfits, and share those photos with others. The Style Check service also combines machine learning algorithms with advice from “fashion specialists” to get style advice. When examining the four P’s, the stand out P (see Appendix 12) was the product, due to Amazon’s growing emphasis on their own services. It is an extension of the Echo Dot to break into the fashion industry ahead of competitors such as Apple and Google. With the brand being a major retailer of clothes, users can use the device to shop current styles, adding to the product offering. It is also improving the place sector in the four P’s (see Appendix 12) by bringing the amazon service into the home and expanding the seamless user experience Amazon has to offer. The success of the case study is challenging to determine, with the product only being available to the public for six months and mix reviews on the Amazon website. For example, some reviews describe the product as “a mediocre Alexa” and a “waste of money”, although, others describe it as a “game changer” and “the next generation of Alexa”. The overall rating on the Amazon website is 3.5 out of 5 stars which could be a result of releasing it into the market too quickly and a hesitant process of acceptance as it is still in the early adoption stages. However, it is an example of how to unlock unstructured types of data, such as images and natural language to analyse data that were previously inaccessible for commercial use. It is developing the use of AI to recommend complementary products based on previous style preferences to generate outfit matches from hundreds of items, like an online personal stylist. .


Focus group 2 (see Appendix 3) were shown a two-minute clip of the Echo Look advert and the responses were divided. The positive responses included “great, cool, different and helpful” while the negative responses included “scary, weird, not only listens but sees and unsure of where the information is going.” Participants then responded with “no” when being asked if they would purchase the product as the technology was unfamiliar to them and therefore unsettling. This is an example of the black box effect of appreciating the “different and helpful” features of the device but because of the lack of understanding the focus group instantly had negative connotations before even testing the product. Findings from the industry expert interview (see Appendix 10) provided a solution to put the customer back in charge through Vendor Relationship Management. This is an example of business activity made possible by software tools that aim to provide customers with both independence from vendors and better means for engaging with vendors.

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5.3 Pre-Conceived Paranoia The black box effect has resulted in paranoia towards AI and therefore a reluctance to embrace the technology. In the online survey (see Appendix 1) a respondent claimed they “would never buy one (a home assistant) as they’re too intrusive, I would much rather use an iPad”. This proves a lack of understanding as iPads hold just as much personal information if not more than a home assistant. Likewise, focus group one (see Appendix 2) raised an opinion that “they only talk about exciting new advancements, they never talk about the dangers (of technology)”. However, the opposite of this could be argued with recent media coverage focusing on the negative implications of technology such as Facebook leaking personal data of 87 million people (Salinas, 2018). A report from the Information Technology and Innovation Foundation (2018) found that media coverage of technology in the 1980s and early 1990s was largely favourable and the tone has gradually shifted over the years, becoming more negative (Allen, 2018). In one of the in-depth interviews (see Appendix 5) when shown their phone has access to their microphone in relation to the use of Siri, he replied “I knew it was listening to me” suggesting that rumours have led to paranoia surrounding voice activation. The other interviewee said “it feels like the phone is always watching” because of their location services always being turned on. This however is due to the user allowing this feature which could easily be switched off. Participant 1 in focus group 1 (see Appendix 2) explained that “we have this big reluctance to technology but it is eventually going to happen…people are going to have views about it damaging our health but we don’t know until we try”. This mind-set of embracing technology was a rare find when conducting primary research, therefore more focus should be put on stamping out the pre-conceived paranoia and the possibilities of what these advancements could achieve.

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5.4 Subconscious Data Sharing When conducting the one to one interviews (see Appendix 4,5&6) there was a clear correlation to the interviewees being shocked, however not enough to change any of their sharing settings. Towards the end of the interview after showing the participant all the personal information stored on their phone, they were asked “does this make you want to change any of the settings” and all three respondents said no. Participant 1 stated that “it does it behind the scenes without you even realising” and “I would’ve never looked on these settings if it wasn’t for this interview”. This is supported in the “who will benefit” section of the literature review as Lui (2018) argues customers don’t care about retailer’s problems, they care about finding the right product at the right time. It also states that consumers don’t generally think about the technologies they use and often, don’t even notice them (Business of Fashion, 2017). This again is supported by primary findings as in focus group 1 (see Appendix 2) participant 2 stated “I’d do it automatically without thinking” in relation to sharing data. All of these findings signify a need to make the storage of personal data more explicit to the user. However, even though the participants were shocked, ultimately there is absence of genuine concern to act upon their worries of data sharing.

“They only talk about exciting new advancements, they never talk about the dangers.” .


THE FUTURE

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6.1 Introduction There is uncertainty relating to the future of intelligent technologies and the rate at which they are advancing is causing society to feel apprehensive of what lies ahead. To take better control, guided adoption with the help of political discussion to determine laws and regulations must be the main focus going forward. Otherwise, there is a risk of a technological backlash resulting in digital detoxes with the increasing desire to “switch off”. The subject of the future was a crucial topic when conducting primary research which proved to split the opinions of those taking part. Findings from these reponses will be evaluated and analysed to move forward in developing possible ideas for the future.

6.2 Pessimistic vs Optimistic Outlook There was an obvious divide in pessimistic and optimistic outlooks when questioned about the future of technology. In the Instagram poll (see Appendix 11) the responses were split with 51% saying scared and 49% saying excited when asked “does the future of technology scare or excite you?” The poll also presented the opinions on the effect technology has on society with 44% saying it has a positive effect and 56% saying negative, showing a slight inclination towards negativity. This was also the case in focus group one (see Appendix 2) due to the reflection at the end of the interview that everyone agreed that the “negatives outweigh the positives” in terms of AI and EI. However, this could reflect how technology is negatively portrayed in the media as stated previously.

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The rate at which technology is advancing insinuated a pessimistic response to most participants in the primary research. In focus group one (see Appendix 2) participant 3 stated “they’re trying to take it further and further, there has to be a time when you just stop, otherwise it’s going to ruin our population”. This supports the theory of technological determinism (Leonardi, 2004) as mentioned in the literature review, that the inevitability of technological advancement is purely a deceiving concept to benefit the company not the consumer. The topic of EI also presented an unsettling response from participants that implies that society isn’t ready to adopt this technology into their everyday devices. Focus group two (see Appendix 3) said they would feel “weird” if technology could sense and adapt to emotions and it would be “too smart, intrusive, personal and unsettling.” An expert in the field of AI and EI stated that “EI is intrusive, it can be beneficial in many industries in the future but regarding fashion, we should find ways that are useful for the end user.” Therefore, the question when implementing these technologies should always be what’s in it for the customer and will the end user gets the major benefit? Although there is a clear lean towards pessimistic outlooks than optimistic ones found in the primary research, there was still consideration towards the importance of intelligent technologies and their benefits. One respondent from the online survey (see Appendix 1) explained that they would be lost without their phone and are “open to expanding its use further” showing a willingness to benefit from technological advancements. However, this was a rare find in the acceptance of technology. A key worry in the future for consumers was a concern of losing jobs due to AI. This was clear in the Ask the Public findings (see Appendix 8) as common queries being searched in Google were “can technology replace my job” “will AI take my job” “will AI replace humans”. Therefore, the challenge to the next generation will be managing the transition and this needs to be taught in education to minimise societies fear of job loss.

“Too smart, intrusive, personal and unsettling” .

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Instagram poll percentage of 68 respondents who feel scared/excited for the future of technology

Instagram poll percentage of 68 respondents who feel negatively/positively for the future of technology

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6.3 Innovative Consumer Relationships The findings from the Alexa conversation (see Appendix 7) suggested that once the novelty of conversations wore off, the main use went to convenience in playing music from playlists or the radio. This shows that the human value function these devices are supposed to add is yet to reach its potential. Instead, practical adoption of home assistants seems to be driven by convenience rather than building consumer relationships. In focus group two (see Appendix 3) participant 5 said the main use for their personal assistants is to play music, she then goes onto explain that “I don’t find it that useful, I would rather use my phone to search for things,” again proving that the potential for communication is still at the early stages of adoption. However, the industry expert interview (see Appendix 9) highlighted that “human and machine interaction will become more and more important in the future.” This relates to the literature review when Han (2018) suggested that in the future, sensors and cameras will be added to IPAs to collect contextual information to provide more situationrelevant information to users and blur the boundaries between man and machine. A case study on the “Facenote” brand is an example of how this contextual information will be provided in the retail industry.

Facenote is a facial identification technology that helps companies recognise their most valuable customers.

“Consumers opt-into the service by providing a selfie, and Facenote takes it from there, increasing customer engagement and loyalty program as well as equipping store associates with information on their purchasing behaviour, style preferences and more.” (Facenote.me, 2019) The brand essence model as shown below, showcases how Facenote has created a coherent and meaningful service for both businesses and customers, with core values including privacy and integrating the retail journey experience from online to offline. In the interview with the owner of the Facenote brand (see Appendix 9) he explained that “in store experiences feel detached and standalone. This can be overcome by offering a personalised experience at the door tied with online experience to provide a competitive advantage…like entering a store and being reminded of something in your online basket.” The brand has had huge success in America in the early stages of their business with the service being available across the country however their next challenge is to break into the global market and expand their business in the UK. It is guiding the trend of individualisation by developing an ultrapersonalised shopping experience. It is also an example of how to implement AI powered customer recognition without being intrusive whilst achieving customer loyalty. This use of facial identification will become more popular in the future for companies to recognise their most valuable customers and create innovative customer relationships.

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BRAND ESSENCE

Brand essence model for the Facenote brand

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6.4 Reaping the Rewards The challenge going forward is figuring out how to reap the benefits of technology without jeopardising consumers’ rights and privacy. The way that this can be achieved successfully is to start a political conversation in how to guide technological adoption in a way that is controlled and regulated by laws. In the expert interview (see Appendix 10) the interviewee explained that “our AI industry needs more self-regulation as government and laws are behind and will always be behind giving the pace of speed in innovation. Code of conduct within our industry is a must and needs to be organised from within.” Tony Blair (2018) supports this need for political discussion as he told Wired magazine;

“the first political leaders who can understand and explain why we should be optimistic about the future of technology will own the politics of the next couple of decades” (Blair, 2018, p.56). Guided adoption can lead to the potential for companies to combine creativity and AI and therefore provide constant interactivity with their customers.

Scenario planning was conducted by taking into consideration a ranking of immediacy drawn from the STEEPLE analysis (see Appendix 13). It resulted in four possible futures from diverging worlds, as shown below, to identify possible ideas that might be useful in the future. The two main factors in the STEEPLE model were political leaders failing to address concerns and personalisation without intrusion. These issues have been explored into a futuristic narrative and the world of creative retail and sustainable AI were found to be the most relevant when relating to this topic. According to Accenture, AI systems will boost probability in the retail sector by 60% over the next two decades (2018). Therefore, opportunity platforms of individualised subscription services could have the ability to disrupt in the fashion industry in the future in terms of AI curating and buying for consumers. The future narrative of sustainable AI shown in the scenario planning diagram below, also shows the possibilities of AI predicting fashion trends to reducing waste and benefit the environment. This is an example of how to reap the rewards of intelligent technologies for the greater good of society.

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AI and EI technology has moved away from brand usage and instead is being utilised in healthcare to spot signs of illness at a very early stage and technological psychological therapy uses EI to aid mental health understanding. It is also being used for consumers to reach their full potential and improve the quality of their lives, giving them more time for friends, family and personal development.

Consumers expect radical transparency from brands and the use of personal data has been greatly controlled by laws and regulations. This has led to a lack of personalised experiences from brands as they don’t want to seem intrusive, making brand loyalty extremely difficult to achieve. However, political discussion surrounding efficient adoption of technology is constantly being discussed with a slow approach to implementation.

Radical Transparency

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Fast

Creative Retail

The speed of innovation has resulted in AI curating and buying for consumers with individualised subscription services. The main use for shopping is only for social interaction and to find the few products that help customers express who they are. Human and robotic interaction is widely accepted into everyday life. Although, because at the rate that technology has advanced, workers face high unemployment with machines taking over their skills.

AI can now predict fashion trends by learning from consumers what is popular, reducing waste in resources and benefitting the environment. There is also a skills revolution in education, implemented by the government to teach skill transformation and avoid unemployment on a mass scale.

Slow

Hyper Individualisation

Consumer Privacy

AI Saves Lives

Sustainable AI


7

CONCLUSION

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7.1 Key Insights

7.2 Conclusion

Friend not a Therapist: • Consumers are becoming more aware of the value of their private information and how it can be misused. Although, they face the dilemma of still enjoying personalised recommendations and tailored experiences from brands, therefore, there has to be an acceptance of sharing data in order to receive this.

To conclude, the aim of this report was to investigate the consumer consequences/opportunities of using AI and EI as a tool to enhance brand’s customer relationships. This was achieved by a thorough exploration into relevant theories and debates surrounding this topic through academic sources in the literature review to then structure the methodology for primary research. Key findings from research discovered meaningful insights to spark inspiration going forward into stage two. Through evaluation of primary research, it has been concluded that there is an opportunity for future platforms to combat the consumer frustration of wanting to enjoy the benefits of creative AI, offering personalised experiences whilst providing the correct use of data sharing. This will then develop innovative customer relationships, resulting in brand loyalty and valuable experiences. Examples of direction that further research could pursue is highlighted next in recommendations.

• To answer the question of “where is the line?”, findings from the consumer perspective showed a strong difference in using statistical personal data compared to EI. This neuroscientific understanding is therefore seen to be crossing the line into intrusive technology of the device knowing more about the consumer than they may know about themselves. Fear of the Unknown: • The black box effect has resulted in pre-conceived paranoia and a reluctance to purchase or try products with complex machine learning algorithms. • Consumers portray a worry relating to privacy and data sharing when in actual fact their concern don’t match up with their sub conscious sharing actions, suggesting that users are more embarrassed over their sharing habits rather than being genuinely concerned. The Future: • There is uncertainty relating to the future of intelligent technologies and the rate at which they are advancing is causing society to feel apprehensive of what lies ahead, resulting in a pessimistic outlook of the future.

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7.3 Recommendations • To take better control, guided adoption with the help of political discussion to determine laws and regulations must be the main focus going forward. The way that this can be achieved successfully is to start a political conversation in how to guide technological implementation in a way that is controlled and regulated by laws. Guided adoption can then create an open AI culture to cultivate trust, openness and transparency that supports effective and ethical acceptance of technology. This can result in possibilities of AI predicting fashion trends to reducing waste and benefit the environment. This is an example of how to reap the rewards of intelligent technologies for the greater good of society. • The future of intelligent technologies shows personalisation being fundamental in capturing brand loyalty but personalisation alone will not suffice. It must be complimented with quality, transparency, privacy and respect. The focus from brands needs to be on integrity as consumers are wanting reassurance that a company’s intentions are aligned with the wellbeing of society. Therefore, technological companies must focus on turning the black box into a glass box. This can be achieved by more explicit storage of personal data and putting the customer back in charge through Vendor Relationship Management to provide customers with independence from businesses.

• Society isn’t ready for the implementation of EI in personal devices as it is treading a fine line of intrusive technology. Therefore, brands should optimise the potential of combining creativity and AI to provide constant interactivity and innovative, individualised customer relationships. In the future, sensors and cameras will be added to IPAs to collect contextual information to provide more situation-relevant information to users. Therefore, companies can implement this, along with AI, to create coherent and meaningful service for both businesses and customers, integrating the retail journey experience from online to offline. Individualised subscription services also have the ability to disrupt in the fashion industry in the future in terms of AI curating and buying for consumers, resulting in the next generation of personal stylists.

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8.2 BIBLIOGRAPHY

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Kahn, R. and Cannell, C. (1957). The dynamics of interviewing. New York: Wiley. Kellner, D. (1989). Postmodernism. Washington, D.C.: Maisonneuve Press. Kemp, N. (2018). Body positivity, diversity and strong women: the new rules of beauty advertising. [online] King, M. (2018). AI and Automation. [online] Academic.mintel.com. Available at: http://academic.mintel.com/display/858907/ [Accessed 7 Jan. 2019]. King, M. (2018). Digital Trends UK. [online] Academic.mintel.com. Available at: http://academic.mintel.com/display/918686/ [Accessed 7 Jan. 2019]. Knight (2016). Amazon working on making Alexa recognise emotions. MIT Technology Review. Koss, E. (2014). The importance of individualism | Ella Koss | TEDxGrossePointeSouthHS. [online] YouTube. Lawler, S. (2015). Identity. New York, NY: John Wiley & Sons. Leonardi, P. and Jackson, M. (2004). Technological determinism and discursive closure in organizational mergers. Journal of Organizational Change Management, 17(6), pp.615-631. Lion, d. (2016). H&M New Autumn Collection. [online] YouTube. Available at: https://www.youtube.com/ Lorey, A. (2018). The Future Is Still Empowerment - TrendWatching. [online] TrendWatching. Louie, W., McColl, D. and Nejat, G. (2014). Acceptance and Attitudes Toward a Human-like Socially Assistive Robot by Older Adults. Assistive Technology, 26(3), pp.140-150. LS:N Global. (2018). Will AI make us better human beings?. [online] Available at: https://www.lsnglobal.com/ Lucas, S. (2018). The Future CMO. Racounteur. Lui (2018). Fashion Goes Tech. Wired. Maslow, A. and Frager, R. (1987). Motivation and Personality. New Delhi: Pearson Education. Mayton, T. (2018). Amazon Echo Look rolled out to all US customers | Mobile Marketing Magazine. [online] Mobilemarketingmagazine. com. Available at: https://mobilemarketingmagazine.com/amazon-echo-look-rolled-out-to-all-us-customers [Accessed 19 Jan. 2019]. McKinsey & Company. (2017). What shoppers really want from personalized marketing. [online] Available at: https://www.mckinsey.com/ business-functions/marketing-and-sales/our-insights/what-shoppers-really-want-from-personalized-marketing [Accessed 23 Dec. 2018]. Me Too Movement. (2018). About - Me Too Movement. [online] Available at: https://metoomvmt.org/about/ Mintel.com. (2018). Technology Habits of GenZ. [online] Available at: http://academic.mintel.com/ Moorthy, A. and Vu, K. (2015). Privacy Concerns for Use of Voice Activated Personal Assistant in the Public Space. International Journal of Human-Computer Interaction, 31(4), p.307. Morris, T. and Wood, S. (1991). Testing the Survey Method. 5th ed. Morrison, C. (2018). Thousands of UK Jobs at Risk From Robots and AI. [online] The Independent. Available at: https://www.independent. co.uk/news/business/news/uk-job-loss-risk-ai-robots-artificial-intelligence-technology-bank-of-england-andy-haldane-a8498901.html [Accessed 10 Jan. 2019]. Moss, A. (2018). The Connected Home. [online] Academic.mintel.com. Available at: http://academic.mintel.com/display/859209/ [Accessed 7 Jan. 2019]. Nichols, S. (2018). Your Phone Is Listening and it’s Not Paranoia. [online] Vice. Available at: https://www.vice.com/en_uk/article/wjbzzy/ your-phone-is-listening-and-its-not-paranoia [Accessed 6 Dec. 2018]. Nightingale, O. (2018). Hyper-personalisation: How Spotify knows your music tastes better than you!. [online] Nov. 2018]. Pavliscak, P. (2018). Designing For The Internet Of Emotional Things. [online] Smashing Magazine. Available at: personalization-to-individualization/ [Accessed 16 Oct. 2018]. Peters, S. (2012). The Chimp Paradox. St Ives: Ebury. Phillips-Wren, G. (2013). Various forms of intelligence. Intelligent Decision Technologies, 8(1).

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Pieper, M. and Pieper, W. (2005). Addicted to unhappiness. New York: McGraw-Hill. Reynolds, A. (2018). Login to Mintel Reports - Mintel Group Ltd.. [online] Attitudes Towards Online Security. Available at: http://academic. mintel.com/display/901372/ [Accessed 7 Jan. 2019]. Robson, C. (2002). Real world research. Oxford: Blackwell. Rodriguez, D. (2018). The soft side of branding: leveraging emotional intelligence. Journal of Business, 33(1), pp.117-125. Russell., S. (2016). Artificial Intelligence: A Modern Approach, Global Edition. Pearson. Salesforce UK Blog. (2017). AI for Customer Service: 4 Ways to Get Ahead of the Curve. [online] Available at: https://www.salesforce.com/ uk/blog/2017/08/ai-for-customer-service-4-ways-to-get-ahead-of-the-curve.html [Accessed 1 Jan. 2019]. Salesforce UK Blog. (2017). Artificial Intelligence in Marketing: It’s Time to Get Personal. [online] Available at: https://www.salesforce. com/uk/blog/2017/09/artificial-intelligence-in-marketing-its-time-to-get-personal.html [Accessed 1 Jan. 2019]. Salesforce UK. (2017). Customers Are Happy to Share Data. Marketers, Are You Ready?. [online] Available at: https://www.salesforce. com/uk/blog/2017/01/customers-are-happy-to-share-data-marketers-are-you-ready [Accessed 1 Jan. 2019]. Salinas, S. (2018). Facebook says the number of users affected by Cambridge Analytica data leak is 87 million. [online] CNBC. Available at: https://www.cnbc.com/2018/04/04/facebook-updates-the-number-of-users-impacted-by-cambridge-analytica-leak-to-87-million-. html [Accessed 19 Jan. 2019]. Saunders, M., Lewis, P. and Thornhill, A. (2009). Research methods for business students. 5th ed. Harlow: Pitman. Simmel, G. (2009). Sociology. Leiden: Brill. simplypsychology.org/maslow.html [Accessed 20 Oct. 2018]. Singh, P. (2018). Asos announces ‘Collusion – a new affordable brand for the coming age’. [online] Slonimsk, L. (2018). Tommy Hilfiger Launches Tommy Jeans Xplore. [online] WWD. Available at: https://wwd. sociologyarticles.co.uk/the-individualisation-thesis/ [Accessed 7 Oct. 2018]. Spadafora, A. (2018). Reaching the level of trust needed for mass AI adoption. [online] TechRadar. Available at: https://www.techradar. com/uk/news/reaching-the-level-of-trust-needed-for-mass-ai-adoption [Accessed 10 Jan. 2019]. Stephens (2018). The State of Fashion 2019. [online] Cdn.businessoffashion.com. Available at: https://cdn.businessoffashion.com/ reports/The_State_of_Fashion_2018_v2.pdf [Accessed 22 Dec. 2018]. Stewart, D. and Kamins, M. (1993). Secondary Research 4. Los Angeles: SAGE Publications Inc. Stott, R. (2018). Hasna Kourda on how AI will drive more mindful purchasing. [online] LS:N Global. Available at: https://www.lsnglobal. com/big-ideas/article/22368/hasna-kourda-on-how-ai-will-drive-more-mindful-purchasing [Accessed 16 Nov. 2018]. Sullivan, L. (2018). Amazon Alexa Creates Marketing Model Through Visual Recommendations. [online] Mediapost.com. Available at: https://www.mediapost.com/publications/article/320309/amazon-alexa-creates-marketing-model-through-visua.html [Accessed 19 Jan. 2019]. Tamblyn, T. (2018). Amazon’s New Smart Camera Will Actually Tell You If Your Outfit Is Good Or Bad. [online] HuffPost UK. Available at: https://www.huffingtonpost.co.uk/entry/amazons-echo-look-uses-ai-to-judge-if-your-outfit-is-good-or-bad_ uk_5b18fdc7e4b09578259f434c [Accessed 19 Jan. 2019]. Techworld. (2018). AI Startups to Watch: The Hottest Machine Learning Startups in the UK. [online] Available at: https://www.techworld. com/picture-gallery/startups/uk-ai-startups-watch-hottest-machine-learning-startups-in-uk-3645606/ [Accessed 5 Jan. 2019]. Tegmark, M. (2018). Benefits & Risks of Artificial Intelligence - Future of Life Institute. [online] Future of Life terrifying [Accessed 27 Oct. 2018]. The British Journal of Sociology, [online] 58(4). Available at: http://citeseerx.ist.psu.edu/viewdoc/ The_Evolution_of_Individualization.pdf [Accessed 10 Sep. 2018]. Thrift, N. (2007). Non-Representational Theory. Taylor & Francis Ltd. Transparency Market Research. (2016). Artificial Intelligence Market to reach US$3,061.35 Bn by 2024 - TMR. [online] Available at: https:// www.transparencymarketresearch.com/artificial-intelligence-market.html [Accessed 23 Dec. 2018]. Trend Watching (2014). Post-demographic Consumerism. Trend-Monitor. (2016). Key Trend No.3 Make it Personal - Trend-Monitor. [online] Available at: https://trendmonitor.trend-universe/megatrends/mega-trend-detail/individualisation.html [Accessed 7 Sep. 2018]. Trendone.com. (2018). Mega-Trend: Individualisation. [online] Available at: https://www.trendone.com/en/ trends/5-trends-for-2017/ [Accessed 6 Sep. 2018].

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Trotter, C. (2018). 45 top retail innovations from NRF 2018 Innovation Lab - Insider Trends. [online] Insider Trends. Available at: https:// www.insider-trends.com/45-top-retail-innovations-nrf-2018-innovation-lab/ [Accessed 17 Jan. 2019]. vanityfair.com/style/2018/04/isabella-rossellini-lancome [Accessed 11 Oct. 2018]. Vimeo (2018). Talking to my Digital Self. [video] Available at: https://player.vimeo.com/video/276419297 [Accessed 16 Nov. 2018]. Volmer, A. (2018). Robots have power to significantly influence children’s opinions. [online] University of Plymouth. Available at: https:// www.plymouth.ac.uk/news/robots-have-power-to-significantly-influence-childrens-opinions [Accessed 23 Dec. 2018]. Waller-Davies, B. (2018). Will AI make us better human beings?. [online] LS:N Global. Available at: https://www.lsnglobal.com/opinion/ article/22906/will-ai-make-us-better-human-beings [Accessed 16 Nov. 2018]. Watcher (2018). Fashion Goes Tech. Wired. Weaver, J. (2014). Robots are People Too. Santa Barbara: Praeger. WGSN (2018). The Vision 2020. Create Tomorrow. Williams, G. (2018). Wired. Magazine Wilson, G. (2018). The Secret to Retail Tech Success. [online] Adweek.com. Available at: https://www.adweek.com/digital/the-secret-toretail-tech-success-isnt-the-tech-its-the-planning-and-training/ [Accessed 17 Jan. 2019]. Winarsky, N. (2015). The President of SRI Ventures on Bringing Siri to Life. [online] Harvard Business Review. Available at: https://hbr. org/2015/09/the-president-of-sri-ventures-on-bringing-siri-to-life?autocomplete=true [Accessed 22 Nov. 2018]. Wired (2018) Fashion Goes Tech. Wired. Wired Magazine. (2018). These high-tech clothes make you money by selling your data. (2018). Wired. wired.co.uk/article/mental-health-apps [Accessed 1 Nov. 2018]. Woollaston, V. (2017). Amazon reveals Echo Look – a hands-free camera and style assistant. [online] Wired.co.uk. Available at: https:// www.wired.co.uk/article/amazon-echo-product-new [Accessed 19 Jan. 2019]. Young, S. (2018). Tommy Hilfiger’s new clothing line tracks your movements. [online] The Independent. Ypulse (2018). Trend Report: Borderless Culture. New York. Zaidi, D. (2018). Your Next Personal Stylist Could be A Chatbot – Chatbots Magazine. [online] Chatbots Magazine. Available at: https:// chatbotsmagazine.com/your-next-personal-stylist-could-be-a-chatbot-b37c340d1bd0 [Accessed 5 Jan. 2019].

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8.3 LIST OF ILLUSTRATIONS Front Page, Omolade, K. (2016). Painting by Artist Kip Omolade. [online] Art People Gallery. Available at: http://www. artpeoplegallery.com/painting-by-artist-kip-omolade/ [Accessed 15 Dec. 2018].

A World in Line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/34822151/A-WORLD-IN-A-LINE-too-many-work-for-a-title [Accessed 15 Dec. 2018].

A World in Line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/34822151/A-WORLD-IN-A-LINE-too-many-work-for-a-title [Accessed 15 Dec. 2018].

I.pinimg.com. (2018). Geometric Background. [online] Available at: https://i.pinimg.com/ originals/51/92/31/519231a293f4d52c820a026dadfd0cdf.png [Accessed 23 Dec. 2018]. Han, S. and Yang, H. (2018). Understanding adoption of intelligent personal assistants. Industrial Management & Data Systems, 118(3), pp.618-636. A World in Line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/34822151/A-WORLD-IN-A-LINE-too-many-work-for-a-title [Accessed 15 Dec. 2018].

Two dots and a line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/46036993/two-points-and-a-line-various-illustration-2016 [Accessed 23 Dec. 2019]. A World in Line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/34822151/A-WORLD-IN-A-LINE-too-many-work-for-a-title [Accessed 15 Dec. 2018].

A World in Line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/34822151/A-WORLD-IN-A-LINE-too-many-work-for-a-title [Accessed 15 Dec. 2018].

A World in Line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/34822151/A-WORLD-IN-A-LINE-too-many-work-for-a-title [Accessed 15 Dec. 2018].

A World in Line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/34822151/A-WORLD-IN-A-LINE-too-many-work-for-a-title [Accessed 15 Dec. 2018].

Echo Product, Amazon.com. (2018). Echo Look. [online] Available at: https://www.amazon.com/Amazon-Echo-LookCamera-Style-Assistant/dp/B0186JAEWK [Accessed 23 Dec. 2018].

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Style Check, Pagona, A. (2018). I let Amazon’s new Echo Look choose my clothes for a week — here’s how it went. [online] Business Insider. Available at: https://www.businessinsider.com/amazon-echo-look-alexa-style-assistantreview-2018-5?r=US&IR=T#unboxing-the-echo-look-comes-with-a-screw-in-stand-wall-mount-and-power-cord-1 [Accessed 23 Dec. 2018].

Amazon App, Tillman, M. (2018). What is Amazon Echo Look, how does it work, and when can you buy it?. [online] Pocket-lint. Available at: https://www.pocket-lint.com/smart-home/news/amazon/140903-what-is-amazon-echo-lookand-how-does-it-work [Accessed 23 Dec. 2018]. Two dots and a line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/46036993/two-points-and-a-line-various-illustration-2016 [Accessed 23 Dec. 2019].

Job Loss, Holcroft (2018). Outsourcing – 27 illustrations satiriques de J.. [online] Pinterest. Available at: https://www. pinterest.co.uk/pin/320811173452977791/ [Accessed 14 Dec. 2018].

Logo, Facenote.me. (2019). What we do. [online] Available at: https://facenote.me [Accessed 23 Dec. 2018].

Step 1, Step 2, Facenote.me. (2019). What we do. [online] Available at: https://facenote.me [Accessed 23 Dec. 2018].

Example, Facenote.me. (2019). What we do. [online] Available at: https://facenote.me [Accessed 23 Dec. 2018].

Two dots and a line, Calugi, J. (2018). Behance. [online] Behance.net. Available at: https://www.behance.net/ gallery/46036993/two-points-and-a-line-various-illustration-2016 [Accessed 23 Dec. 2019].

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8.4 APPENDIX 1: ONLINE SURVEY

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Q6: If no, why?

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Q10: Any other comments

APPENDIX 2: FOCUS GROUP 1

Date: 11/12/18 • • • • • •

Participant 1 (female, 21) Participant 2 (female, 20) Participant 3 (female, 20) Participant 4 (female, 21) Participant 5 (female, 22) Participant 6 (female, 20)

Interviewer: I am a final year student studying fashion marketing and branding and as part of my programme of study am undertaking research into how can brands use intelligent technologies to bring their customer relationships to life. To enable me to answer my research questions I wish to talk to you about your opinions on this topic. The focus group will be a focussed discussion and will take approximately 40 minutes. To give you some context, the Individualisation trend has led to consumers wanting to know themselves better and personal devices currently hold a lot of information about their user. Emotional intelligence gives technology the ability to recognise manage and understand our own emotions. This is starting to be implemented into the commercial world whilst being combined with artificial intelligent data to offer highly personal and specific customer service. The focus group will be taped and transcribed, and should you want a copy of the transcription then please ask me and I will arrange for one to be sent to you. The information you give me will be used in support of my work and will be written up in my project. Anything you say will be treated with the strictest confidence and your contribution to the discussion will not be attributed to you as an individual, what you said will be used for illustration only; to reinforce a point that I am making. The tapes will be kept in a locked room and the transcripts on a password protected computer. Both will be destroyed once I have completed my degree and graduated. Interviewer: To start I’m going to tell you a quote and I want you to tell me how it makes you feel, it says: “By 2022, personal devices will know more about an individual’s emotional state than his or her own family”

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2: God 1: It doesn’t surprise me because of the rate that technology is going at the moment 2: It terrifies me though 3: It does but it quite excites me because think about all the people it could help like say if there’s people that can’t talk to anybody but their phone talks to them and it gives them advice on something then that’s really good 2: Yes, but I think it also drives people more to not talk to people 3: True it is important to speak to people 2: It could go either way 4: And if your phone gets it wrong and starts giving you all this advice it could backfire Interviewer: That’s true, technology can make mistakes 6: I don’t actually believe that’s very true 1: Explain? 6: I just don’t agree with it at all (laughs) Interviewer: The quote comes from with the help of AI and EI so it listens to everything you say, it will soon be taking your emotions from facial recognition, voice intonation, heartrate, everything like that 1: I suppose it depends on the person doesn’t it 6: Yes, does it depend on how engage you are with your phone Interviewer: I feel like everyone with an iPhone it will mean 6: Oh, I see 2: But then you could get too attached to your phone, and what if it broke that’s your only source of advice 3: I think I’d fall in love with my phone 5: Say if someone was in genuine need of real help then they find it hard to actually talk to a person anyway, the phone could be unreliable because what’s the phone actually going to do to help you, what point does it turn serious 2: If it could link to like a helpline that would send a call 3: If you feel that way you don’t usually say it out loud would you, so would it read your mind? Interviewer: So it would piece things together and then all your search history will be mixed with the intelligent technology and be able to work it out 3: So if you were searching like am I pregnant it could see that and tell you 2: Imagine if your phone texted you telling you you’re pregnant (laughs) I’d be terrified Interviewer: The next question is, are you happy to hand over personal data to receive tailored experiences from brands? 3: How personal? Interviewer: So when you accept cookies it can see what you’ve been searching for to give you recommendations 1: Like when you’ve been searching for something on your phone and it comes up on Facebook, I quite like it 2: I feel like I do it automatically without thinking, but I do think it’s good because I’d rather see a useful advert than one that doesn’t apply to me at all 1: It is annoying when you have the money and you can’t buy it, so it’s just a constant reminder 2: Yeah but I feel like if there’s going to be adverts there I’d rather it be something tailored to me Interviewer: Agreed, the next question is what is your biggest worry about your device knowing more about you than yourself?

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3: Everyone’s constantly changing who they are so say if your phone goes no Kathryn you don’t normally do that, you’d be like no but I’ve changed, would my phone know that? 2: I guess it would update with like how you are each day 6: Surely you’d feel as though your phone it taking control of your life 2: I feel like that’s an issue already 1: It’s just robots though isn’t it, I feel like we have this big reluctance to technology but it is eventually going to happen and I think people are going to have views about it damaging our health but we won’t know about it until we find out, like it’s the same with a lot of things 3: I think when everything’s new and they’re trying to take it further and further, there has to be a time where you just stop, otherwise it’s going to ruin our population 2: I think like also because they only talk about the exciting new advancements they never talk about the dangers of it 4: I think there’s a lot of danger that if something went wrong and you got hacker there’s so much information on there about you, someone could easily make you believe somethings right because it knows you so well 3: It’s actually like black mirror 4: It could go wrong very quickly 5: especially children as well, because they are even more reliant on it than us 3: Yes, children mimic 2: And as a child technology always looks clever so you would always believe it was right, you’re not going to question it as a child 4: They won’t even see it as new they’ll see it as normal, so very trustworthy 3: That generation is annoying because my cousins who’s 12 will be like “omg I love autumn I love spiced candles” and I’m like do you love that or does Zoella love that, she’s like “Zoella told me it’s nice” 1: Oh really? 6: Feel like we only just missed out on that 2: I’m glad we missed out 6: Because I didn’t get a phone till I was like 13/14 2: I had one for emergencies and left home alone Interviewer: It isn’t all bad, this technology can lead to saving time, personal development and innovative interactions and really high customer service, do these possibilities excite you or do the negatives outweigh the positives? 2: Negative outweighs the positive, people are already dependent on phones but this is just going to make it more of an issue 3: I think there’d be a massive backlash like say if Nike knew so much about you then it recommended something to you based on that but it was a bad thing I would never shop at that brand again because I’d be too scared it knows so much about me 4: It’s almost like making your phone customised to you makes people not unique at all 5: It’s a bit manipulative as well, convincing you that you need something when you don’t 6: you want your privacy still and I feel like that’s invading privacy 1: It should be like your friend that they know you but they don’t know everything about you 3: I just feel like we’re going to lose connection with real people 2: I feel that people who are disconnected will get further disconnected to people Interview: Yes, because I was going to say about the Spotify 2018, that tracked how you were using the app and music and loads of people found that really interesting to see how long you’ve listened, who your favourite artists are 2: I did actually love that like I looked forward to it coming out 3: that doesn’t feel like its listening to you though it just knows what you click on 2: It’s not too personal, like your everyday life and how you feel

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1: But then again there’s been backlash of privacy of what we click on but for me it’s not a big deal if a brand knows what I’ve clicked on, so I think it just depends how useful it is to that company and user Interviewer: Thank you for your time

APPENDIX 3: FOCUS GROUP 2

Date: 18/12/18 • • • • •

Participant 1 (female, 20) Participant 2 (male, 20) Participant 3 (female, 21) Participant 4 (female, 20) Participant 5 (female, 21)

Interviewer: I am a final year student studying fashion marketing and branding and as part of my programme of study am undertaking research into how can brands use intelligent technologies to bring their customer relationships to life. To enable me to answer my research questions I wish to talk to you about your opinions on this topic. The focus group will be a focussed discussion and will take approximately 40 minutes. To give you some context, the Individualisation trend has led to consumers wanting to know themselves better and personal devices currently hold a lot of information about their user. Emotional intelligence gives technology the ability to recognise manage and understand our own emotions. This is starting to be implemented into the commercial world whilst being combined with artificial intelligent data to offer highly personal and specific customer service. The focus group will be taped and transcribed, and should you want a copy of the transcription then please ask me and I will arrange for one to be sent to you. The information you give me will be used in support of my work and will be written up in my project. Anything you say will be treated with the strictest confidence and your contribution to the discussion will not be attributed to you as an individual, what you said will be used for illustration only; to reinforce a point that I am making. The tapes will be kept in a locked room and the transcripts on a password protected computer. Both will be destroyed once I have completed my degree and graduated. Interviewer: To start I’m going to show you a video and I want you to tell me your initial reaction *Plays Amazon Echo Look advert* 3: Is that actually real? Interviewer: Yes it has just come out, what does everyone think of the idea? 4: Great 5: I think it’s a bit “Black Mirror” like 4: I quite like it 1: It’s cool though, and it’s different 3: I think that’s a bit scary 5: Yes I think it’s weird because it’s like phone already listen to what you’re saying but this sees as well 1: I can see how it’s helpful, but also where is that information going Interviewer: So if you think it’s weird and creepy what would you change about it? Or would you just not think about purchasing it? 3: I wouldn’t purchase it Interviewer: Next I’ll read you this quote and I want you to tell me how it makes you feel, it says: ““By 2022, personal devices will know more about an individual’s emotional state than his or her own family” 1: Yes I believe that 5: It’s like when you talk about something then your phone gives you suggested ads

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3: The quote makes me feel uncomfortable 1: Unsafe 4: Creepy and intrusive Interviewer: Do you not trust your personal devices is that why? 1: I trust the device I just don’t trust the things behind it, the stuff I can’t see 3: I just think the more information it knows about you like where is It going? Interviewer: The next question is, are you happy to hand over personal data to received tailored experiences from brands? 2: Depends what the information is Interviewer: Like when Asos gets you to input your kind of style then it can recommend you products that you might like 5: I think for that that’s fine, because if it’s to do with clothes I think it’s fine 1: I think it also depends on the brand like whether I trust them or not and if I do then I’m more likely to 4: the credibility of the brand Interviewer: What’s your biggest worry about your personal devices knowing more about you than yourself? 4: Maybe if it even got hacked 3: Yes, ever got hacked, if people found that information, with bank details Interviewer: How would you feel if technology could sense and then adapt to your emotions? 5: Weird 4: It would be like a roller-coaster 3: I don’t know it feel like it’s strange that a device can do that and it’s too smart 5: If it’s too personal it can intrude 1: That unsettles me Interviewer: An example of a brand using personal data is Spotify when it did their top 2018 songs, did you like that do you find this information interesting that you didn’t know about yourself? 3: I think because that was a matter of statistics, it wasn’t personal 1: Also, because its music it’s not data about me as such 2: I found it really interesting Interviewer: Does anyone here own a technological personal assistant, if not why? If you do what do you use it for 3: I just use it for music, my dad uses it for an alarm 2: Same, for music Interviewer: Is it useful? 2: Not really 3: The google one is always like I don’t understand what you’re saying 1: I see how it is useful, you need to get into the habit of using it though and I think that’s hard to do 3: Because they have ones with screens on and you can watch videos which is useful but I forget it’s there 1: I always just use my phone

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APPENDIX 4: IN-DEPTH INTERVIEW 1

1 to 1 Interview: 1 Date: 8/01/19

Participant: (23, Female) Interviewer: I am a final year student studying fashion marketing and branding and as part of my programme of study am undertaking research into how can brands use intelligent technologies to bring their customer relationships to life. To enable me to answer my research questions I wish to talk to you about your opinions on this topic. The interview will be a focussed discussion and will take approximately 40 minutes. To give you some context, the Individualisation trend has led to consumers wanting to know themselves better and personal devices currently hold a lot of information about their user. “By 2022, personal devices will know more about an individual’s emotional state than his or her own family” (Zimmerman, 2018). With the rising use of emotional intelligence, this context can be added to AI data to give humans the tool to learn from themselves. Will this deeper understanding of consumers lead to self-optimisation, innovative interactions and a flourishing civilisation or will it introduce dangers of outsourcing decision making, constant monitoring and intrusive technology? The interview will be taped and transcribed, and should you want a copy of the transcription then please ask me and I will arrange for one to be sent to you. The information you give me will be used in support of my work and will be written up in my project/dissertation. Anything you say will be treated with the strictest confidence and your contribution to the discussion will not be attributed to you as an individual, what you said will be used for illustration only; to reinforce a point that I am making. The tapes will be kept in a locked room and the transcripts on a password protected computer. Both will be destroyed once I have completed my degree and graduated. For each of these steps please screenshot your phone and send me it to refer to in my project. Go to the settings page>passwords & accounts and print screen. How many website & app passwords does your phone know, do you have autofill passwords? P: It knows 18 passwords and yes I do have autofill Interviewer: Is that surprising to you? P: No not really Interviewer: And it’s autofill P: I suppose if it’s autofill that’s quite dangerous if someone were to get my phone Interviewer: If someone were to have your phone they would have access to all those passwords, does that scare you or make you want to change anything? P: Yes Interviewer: does it really or are you not bothered, you didn’t seem convincing P: Well no not particularly, because a lot of my websites aren’t that important, like amazon, BBC, Fitbit, google, Netflix, twitter Interviewer: So you would rather your phone remembers them all and autofill them rather than you having to remember them and fill them out all the time? P: Yes it’s helpful, it just saves time and is easier Interviewer: Go to settings>privacy and screenshot, all these apps hold your personal data, your phone knows where you are, your friends, your calendar, your reminders, photos, what you’re saying, your health, the music you like and more. How does this make you feel? P: Um I suppose it can be quite helpful for location and stuff so it knows where I am or if I want to find somewhere, but it is quite scary that it knows all that Interviewer: But you don’t notice it do you so does it really bother you or not much? P: I’m not bothered to be honest haha

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Interviewer: So your location services are turned on, click onto location services and print screen. All the apps listed below with a grey tick have viewed your location in the last 24 hours, count how many this is. Is this surprising to you? P: 3 in the last 24 hours, I knew snapchat knows where I am because of snapmaps Interviewer: And do you like people being able to see where you are? P: Yes, I turn it on ghost mode sometimes Interviewer: When would you do that? P: Well I’ve only got certain friends who can see where I am Interviewer: What about Instagram? Is that surprising? P: Yes it is, I didn’t know that it was all the time but I knew that you could put your location on when you’re tagging, it doesn’t worry me but it’s interesting to find that out Interviewer: So after hearing all of this are you going to change anything? P: Not really, but it’s good to know Interviewer: Do you think that apple should make you more aware on what your phone knows about you P: Yes definitely Interviewer: And does it shock you how much it knows about you P: Yes it does

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APPENDIX 5: IN-DEPTH INTERVIEW 2

Date: 8/01/19

Participant: (Male, 25) Interviewer: I am a final year student studying fashion marketing and branding and as part of my programme of study am undertaking research into how can brands use intelligent technologies to bring their customer relationships to life. To enable me to answer my research questions I wish to talk to you about your opinions on this topic. The interview will be a focussed discussion and will take approximately 40 minutes. To give you some context, the Individualisation trend has led to consumers wanting to know themselves better and personal devices currently hold a lot of information about their user. “By 2022, personal devices will know more about an individual’s emotional state than his or her own family” (Zimmerman, 2018). With the rising use of emotional intelligence, this context can be added to AI data to give humans the tool to learn from themselves. Will this deeper understanding of consumers lead to self-optimisation, innovative interactions and a flourishing civilisation or will it introduce dangers of outsourcing decision making, constant monitoring and intrusive technology? The interview will be taped and transcribed, and should you want a copy of the transcription then please ask me and I will arrange for one to be sent to you. The information you give me will be used in support of my work and will be written up in my project/dissertation. Anything you say will be treated with the strictest confidence and your contribution to the discussion will not be attributed to you as an individual, what you said will be used for illustration only; to reinforce a point that I am making. The tapes will be kept in a locked room and the transcripts on a password protected computer. Both will be destroyed once I have completed my degree and graduated. For each of these steps please screenshot your phone and send me it to refer to in my project. Go to the settings page>passwords & accounts and print screen. How many website & app passwords does your phone know, do you have autofill passwords? P: It doesn’t say I don’t think, oh wait I can count, I think there’s about 20 and yes autofill is on Interviewer: Is that surprising to you? P: Not really, I like having autofill on, especially with facial recognition because it’s so quick and easy Interviewer: Your phone stores 20 of your password, does that make you want to change anything? P: When it comes to banking and stuff I guess it is quite worrying Interviewer: Go to settings>privacy and screenshot, all these apps hold your personal data, your phone knows where you are, your friends, your calendar, your reminders, photos, what you’re saying, your health, the music you like and more. How does this make you feel? P: I knew it was listening to me haha! Interviewer: Not only listening but a lot more P: Yes that is a bit creepy, what does it use all that for though? Interviewer: Well to give to recommendations based on what you’re doing, all your health apps can track your steps, give you reminders and Spotify can give you recommended songs based on what you’ve been listening to P: Oh yes, it does it behind the scenes without even realising doesn’t it Interviewer: So how does that make you feel? P: I’m not too fussed really, I like what Spotify music recommends and tracking my fitness so things like that are fine to me, creepy that it’s listening to me though Interviewer: Apple claims that it only listens to a small fraction when you say “siri” in order to complete the action but people seem to think it’s more than that P: Yes because I’ll be talking about something with my friends and I swear I’ll get like adverts for it the next day Interviewer: That could be based on your google history

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P: Maybe, who knows Interviewer: Your location services are turned on, click onto location services and print screen. All the apps listed below with a grey tick have viewed your location in the last 24 hours, count how many this is. Is this surprising to you? P: 7 apps have in the last 24 hours, mm why do they want to track me Interviewer: Well things like Instagram you tag your location don’t you and snapchat P: True, but surely it doesn’t have to know 24/7 Interviewer: You can change the location restrictions if you want P: No but everyone has them don’t they Interviewer: Most people do, yes. So after hearing all of this are you going to change anything? P: Probably not, it’s just interesting to know isn’t it Interviewer: Do you think that apple should make you more aware on what your phone knows about you P: I guess so, I mean it’s not really clear and I would have never looked on these settings things if it wasn’t for this interview

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APPENDIX 6: IN-DEPTH INTERVIEW 3 Date: 10/01/19

Participant: (Female, 24) Interviewer: I am a final year student studying fashion marketing and branding and as part of my programme of study am undertaking research into how can brands use intelligent technologies to bring their customer relationships to life. To enable me to answer my research questions I wish to talk to you about your opinions on this topic. The interview will be a focussed discussion and will take approximately 40 minutes. To give you some context, the Individualisation trend has led to consumers wanting to know themselves better and personal devices currently hold a lot of information about their user. “By 2022, personal devices will know more about an individual’s emotional state than his or her own family” (Zimmerman, 2018). With the rising use of emotional intelligence, this context can be added to AI data to give humans the tool to learn from themselves. Will this deeper understanding of consumers lead to self-optimisation, innovative interactions and a flourishing civilisation or will it introduce dangers of outsourcing decision making, constant monitoring and intrusive technology? The interview will be taped and transcribed, and should you want a copy of the transcription then please ask me and I will arrange for one to be sent to you. The information you give me will be used in support of my work and will be written up in my project/dissertation. Anything you say will be treated with the strictest confidence and your contribution to the discussion will not be attributed to you as an individual, what you said will be used for illustration only; to reinforce a point that I am making. The tapes will be kept in a locked room and the transcripts on a password protected computer. Both will be destroyed once I have completed my degree and graduated. For each of these steps please screenshot your phone and send me it to refer to in my project. Go to the settings page>passwords & accounts and print screen. How many website & app passwords does your phone know, do you have autofill passwords? P: I have 24 and autofill is on as well Interviewer: Is that surprising to you? P: Yes it is actually, 24 is quite a lot but I know autofill has been on because it saves time Interviewer: If someone were to have your phone they would have access to all those passwords, does that scare you or make you want to change anything? P: It does scare me but I don’t even how I would change that in the first place, just think I have to accept to be careful with password but it’s the type of world we live in isn’t it Interviewer: So you would rather your phone remembers them all and autofill them rather than you having to remember them and fill them out all the time? P: Yes definitely, it’s so much easier Interviewer: Go to settings>privacy and screenshot, all these apps hold your personal data, your phone knows where you are, your friends, your calendar, your reminders, photos, what you’re saying, your health, the music you like and more. How does this make you feel? P: Umm I’m not quite sure really, I feel like I knew that already but not to what extent Interviewer: So because you don’t know to what extent does it really bother you or not much? P: Not that much, maybe it’s better not to know hahah Interviewer: So your location services are turned on, click onto location services and print screen. All the apps listed below with a grey tick have viewed your location in the last 24 hours, count how many this is. Is this surprising to you? P: It’s 5, yes that is annoying because I haven’t even been on them it’s like it’s always watching Interviewer: So you don’t think it’s necessary? P: No not at all

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APPENDIX 7: ALEXA CONVERSATION Key Examples:

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Main Commands: 54x play radio, 16x personal music, 10x set alarm, 2x ask factual questions, 1x conversation, 1x time.

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APPENDIX 8: ANSWER THE PUBLIC Technology key word:

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AI key word:

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APPENDIX 9: EXPERT INTERVIEW 1 Date: 10/01/19 1) In recent years the physical retail space has been in decline but your Facenote technology increases customer engagement in an innovative way. Do you think this personalised shopping experience will be the only way to capture brand loyalty in the future? Yes, I believe that personalization will be one of the fundamental factors in capturing brand loyalty in the future. But personalization alone will not suffice. It must be complemented by other factors like quality, transparency, sustainability, and absolute respect for customer privacy. Consumers are increasingly demanding this from brands. Being able to give your customers an extremely personalized experience should be complemented with a deeper connection with them. 2) Your brand has a core belief in privacy first. With consumers increasingly becoming less trusting of technology, where do you think technology might overstep the line of becoming intrusive and what regulations do you think need to be implemented to combat this risk? I wouldn’t say that consumers are becoming less trusting of technology, as they are increasingly leaving everyday decisions to technology but, instead, that they are becoming much more aware of the value of their private information, and how it can be misused by the operators of the technology. The EU did a great job with the GDPR regulation, setting the basis on how the technology should be implemented without overstepping privacy or being intrusive.The key elements of this regulations rely on customer consent, transparency, data security and overall, having a trusting relation with your customers. As long as the implemented technology follow this guidelines and regulations, you are on a good path. Of course, we all must be constantly revisiting this issues and looking for ways to protect end users. 3) How do you think combining consumer data with AI can build customer relationship and lead to competitive advantage in the fashion/ retail industry? AI, when combined with a store CRM, a good online presence and a great store team, can be a super powerful tool to anticipate customer needs, reduce friction, and make all the process much more enjoyable. This can offer a complete experience while interacting with the brands at any level. While a lot has been done online, the store experience in many ways feels detached and standalone, so offering a personalized experience at the store tied with the online experience can provide a competitive advantage (imagine entering a store and been reminded of something you left at the shopping cart, or buying online and picking up at the store without even showing your id) 4) How will artificial and emotional intelligent technology be used in the future to create innovative interactions with customers? Emotion analysis should be taken carefully, as detecting you how you feel and acting upon that might be intrusive in many ways. I can imagine certain scenarios where detecting people emotions can be beneficial in the future for many industries, but regarding retail and fashion, we should find ways that are useful for the end users. The question should always be, “What’s in it for the customer?”. I can imagine implementations where I can check my reactions to different color combinations, or designs. There are thousands of ways that brands can benefit from this technology, but the most important this is always finding the implementation where the end user gets the major benefit. How can we help them? How can we provide a better experience for them?.

APPENDIX 10: EXPERT INTERVIEW 2

Date: 6/01/19 1) Who do you think benefits the most by implementing AI and consumer data into the fashion industry, the consumer or the company? And what do you think these key benefits are? The consumer benefits most: more fluent and optimised customer journey with less frictions. more personalised, relevant offerings in content, price and timing. Aligned among relevant channels of behaviour. The company benefits, those who embrace AI and AI potential. This is true for all steps in the fashion value chain. Not only in the marketing and sales processes. Also in design, production and distribution is a lot of potential to gain. Benefits are cost reduction, waste reduction (eg less return orders in online channel; less unsold merchandise at the end of the sale period), etc. Remark: we use less and less consumer (personal) data in AI solutions so we can be relevant without being intrusive, etc. Remark: we help companies in becoming more profitable AND have impact, ie become more sustainable, less waste. Both can go hand in hand. 2) With consumers increasingly becoming less trusting of technology and personal data, where do you think technology might overstep the line of becoming intrusive and what regulations do you think need to be implemented to combat this risk?

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Regulations like GDPR are good. In addition our (AI) industry needs more self regulation as government and law are behind and will always be behind giving the pace of speed in innovation. Code of conduct within our industry is a must and needs to be organised from within. Initiatives are starting to pop up. But goes slow. On the other hand you see that AI is still a black box. Why is the algorithm doing what it is doing. As an example, we have a guiding principle of ’no to black box, yess to glass box’. We want to know and understand why AI is doing what it is doing. And have ’self’ control mechanisms in place to quality assure the process. Vendor Relationship Management initiatives have started but not getting momentum. In this the customer is back in charge. Long way to go though... 3) How do you think combining consumer data with AI can build customer relationship and lead to competitive advantage in the fashion/ retail industry? Linking AI with consumer data will improve the relevancy in the demand and supply. Both in content, timing, channel, etc. This will impact the competitive advantage of the companies using these technologies. Total customer life time value - to throw in another buzz word - will improve significantly with AI. Human and machine interaction becomes more and more important. Make sure that AI is not becoming too intrusive to the consumer and hence backfire the relationships. 4) How will artificial and emotional intelligent technology be used in the future to create innovative interactions and build brand loyalty with customers? Emotional intelligence will help in increasing the relevance between demand and supply even more. Knowing the emotional state and align the message and timing to this can indeed help. I have no experience in this area yet. We started with speach recognition in call center where this could be an interesting topic to research further on.

APPENDIX 11: INSTAGRAM POLL

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APPENDIX 12: AMAZON 4 P’S

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APPENDIX 13: STEEPLE

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APPENDIX 14: AAKER BRAND EQUITY MODEL

APPENDIX 15: MASLOW’S HIERACHY OF NEEDS

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Profile for Alice Walker

How can brands use intelligent technologies to bring their customer relationship to life?  

In the era of unlimited choice, artificial intelligence (AI) has the potential to provide highly personal experiences in an impersonal envir...

How can brands use intelligent technologies to bring their customer relationship to life?  

In the era of unlimited choice, artificial intelligence (AI) has the potential to provide highly personal experiences in an impersonal envir...

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