Industry Report: Visual Search

N0822299 Li-Hsuan Yang MA Fashion Marketing

VISUAL SEARCH Consumer Experience & Engagement

4.............................I. Rationale

9 ...... II. Aims and Objectives

III. Analysis of secondary sources & theoretical background 1. What is visual Search?........10 1.1. The Leading Technology 1.2 Visual Search on Fashion Retailers 2. Consumer Behavior............18 2.1 Shopping Motivation: Convenience is the key 2.2 Shopping Experience: Consumer Empowerment & Engagement

22......................IV. Discussion 1. Advantages 2. Disadvantages 3. Future Challenges and Possibilities

V. Conclusion & Suggestion....30 VI. Limitation...........................32 VII. Bibliography......................34

Throughout the years, the fashion industry has an interconnection with technology (Melvin, 2016). According to the increasing popularity of social media and e-commerce platforms, the internet is not only a platform for information but plays a vital role in influencing the market (Hanna, Rohm & Crittenden, 2011). A brand-new way of communication has accelerated the pace of the fashion industry, closer interaction with the customers and new marketing skills are required (Svatosovรก, 2013; The Economist Intelligence Unit, 2008). Customers have a higher expectation of shopping experience and creative interaction with the brand. Therefore, visual marketing has become a significant marketing tool to enhance our shopping experiences and was put in more effort by the brands in recent years. Especially in the fashion industry, it is the most direct communication with the target audience which impacts their buying behavior--- first glance can decide whether they are interested in the item.

4

What New Technologies Would UK and US Younger vs. Older Millennial Internet Users Be Comfortable with as Part of Their Digital Shopping Experience? (% of respondents)

30.6% 24.8%

Live chat/messaging (digital assistants)

Older Millennials(21-34) Younger Millennials(18-20)

28.6%

AR (try before you buy)

36.8% 58.5% 57.0%

Shoppable content/ click to purchase

61.7% 62.2%

Ability to search by image (visual search)

Figure 1: Emarketer, 2018

Social media has driven the e-commerce to visual attraction base as we look for images for inspirations daily, the technology of visual search capitalizes this trend. Compared to the traditional image search, the technology recognizes real-world images, screenshots, and photographs (Raconteur, 2019). Following the technology leaders such as Google Lens, Amazon Style Snap or Pinterest Lens, the rapid development of Visual search (or image recognition technology) could soon surpass the outcome of the traditional text-based searching system (Walker, 2016). Besides, there was a 140 percent increase in visual search performed using Pinterest Lens by users worldwide in 2018, which was calculated 600 million users in total (Clement, 2018).

The growing market of visual search can be supported by a report published by Emarketer (2018), figure 1. shows that the younger (age of 18-20) and older millennials (age of 21-34) are much more comfor table with visual search in their shopping experience, with 62.2 percentage and 61.7 percentage respectively.

Figure 2 (Raconteur, 2019) predicts the positive anticipation of visual search growth. It is undoubted that the thriving visual search market worth marketers’ attention.

5

The key reason that I want to point out the importance of the visual search is the growing attention at customer experience nowadays. “Great marketing is now all about delivering experience; a brand is little more than the experience its customers enjoy or endure,� says Europe, Middle East and Africa (EMEA) market ing dire c tor for Adob e, John Watton. As shopping experience has become an indispensable marketing tool with the appearance of concept stores, interactive technology, or the shortening process of online payment, the common significant function is to increase the satisfaction of shopping experience. According to the report from BBC, Beck (2017) declared the possibilities of the industry are going to be driven by experiences and interactive technology rather than the act of buying. It cannot be denied that more and more brands seek out

6

new ways of reaching consumers due to the growth of the online shopping market. With just one click on the screen directly leads the customer to the item which they are interested in, visual search has made a noticeable improvement in the shopping experience by shortening the process of looking for the right pro du c t for c ustome rs . T he convenience of the visual search hits the market. In other words, Visual search provides customers a more controllable, personalized and interactive shopping experience.

We cannot deny that establishing successf ul relationship wit h customers has become more direct, interactive, but challenging simultaneously. It is necessary to point out that visual search needs to be implemented as a marketing tool under this thriving trend.

7

8

The key purpose of this report is to develop a wider understanding of visual search to improve the customers’ shopping experience and the sales growth of retailers in the fashion industry. The following objectives will be discussed in the report: 1. Define the phenomenon, analyze and review the data from the brands and reports to understand the current stage of visual search.

2. Understand the consumer behavior behind the visual and interactive shopping experience based on the mobile app shopping.

3. Analyze advantages and disadvantages of visual search from customer and retailer’s perspectives to identify the potential challenges and future possibilities.

4. Make recommendations from marketer’s perspective.

9

1. What is Visual search?

An image can be proceeded by the human brain in 13 milliseconds (Trafton, 2014). It means a human can understand an image in an instant, but it takes humans a much longer period to understand texts.

Especially in the fashion industry, human’s decisions heavily rely on visual information, we decide if we like the item at first glance. Visual search tackles down the embarrassment for customers by searching by text, as we sometimes find it difficult to describe the image in mind precisely. In general, visual search uses real-world images (screenshots, Internet images, or photographs) as the stimuli for online searches (Boyd, 2019).

Tyagi (2017) explains that visual search is based on the system called Content-Based Image Retrieval (CBIR), which means its search is based on colours, shapes, textures or any other information that can be derived from the image itself. It is defined as an automated technique that takes an image as a query and returns a set of images similar to the query (Tyagi, 2018). In detail, one of the functions of visual search called ‘Shop the Look’ based on the ContentBased Image Retrieval engine, a single click on the picture can directly trace and purchase the items.

Furthermore, the system suggests other similar looks under the item you are looking at. The other main function is after taking a picture from your mobile phone, the artificial intelligence system can recognize the similar items in the picture and guide the customers to the related online shopping platform.

10

Compare to the traditional online shopping platform which has indirect search mode, large search space, and inaccuracy in search results, the limitation of screen size was also mentioned as the inconvenience for customers to find the products, the visualization of searching by image improve the accuracy and efficiency of the searching progress for customers and increase the click-pursue turnover rate (Hu et al., 2014). Study shows that the online purchasing experience can be improved by the product recommendation, and has the potential to improve loyalty and online brokering efficiency (Zhang, 2018).

Despite the intelligence and automation for eff icient searching of images, some disadvantages were mentioned in some researches. Tyagi (2018), Singh and Kumar (2018) argued that there is no direct link between human imagination and computers’ interpretation. In other words, humans tend to use complex concepts to interpret images and measure similarity, such as keyword and text descriptors, while the computer vision techniques are based on low-level features (color, texture, shape, etc.) the similarity measures between visual features do not match human perception. Users interpret similar images semantically and perceptually while the technology cannot have explicit semantic meaning by recognizing neither a single feature nor a combination of multiple features (Tyagi, 2018). Visual search can improve the progress and result of searching, but still cannot completely interpret human’s imagination.

11

1.1 The Leading Technology The trend of visual search could be first attributed to the leader of online platforms that noticed the importance of visualization. A positive influence has been seen on their sales numbers as well as the customer experience. In recent years, Google, Bing, Amazon, and eBay had all launched image search capabilities to amplify the eCommerce experience (Vilner, 2017). Particularly, Pinterest and Google’s visual search technologies are leading the way.

Followed by the release of Google Lens in 2017, which was considered as the direction of its future development (Pichai, 2016), developed visual search technology on using phone’s camera or saved photo on mobile phone to complete tasks,.

As what figure 3.(Google Lens, no date) shows, it can read texts, recognize what species a dog is through camera, or offer detailed information and reviews about a place.

Impressively, Google Lens has been used over 1 billion times (Chennapragada, 2019). The visual search technology used in Google Lens was a breakthrough of convenience for customers’ experience, and an outstanding example of the evaluation of research methods.

Figure 3: Google Lens Website, no date

12

Figure 4: Pinterest Lens-Captured by Wood, 2018

The visual search tool launched by Pinterest in 2017 attracts 600 million visual searches every month across Lens nowadays. It is constantly improved by the users’ interaction and feedback so that the technology can recognize new objects and enhance accuracy (Pinterest, 2018).

It is calculated that brands can target over 5,000 categories through visual search (Smith, 2018).

As it was stated by the CEO of Pinterest, Ben Silbermann, that the future of search will be about pictures rather than keywords. At the same time, Pinterest announced that 49 percent of users develop a c through visual search(Pinterest, 2018). Figure 4. (Wood, 2018) shows how pinterst can identify related items from pictures to improve searching progress. Pinterest plays a significant role as an advertising platform, inspirations for customers, and a stronger connection between brands and consumers.

13

1.2. Visual Search on Fashion Retailers Amongst the online retailers, visual search has not been used widely in the fashion industry yet.

Alex Ok, president of Forever 21, stated that the visual search technology contains the convenience of online shopping, but also add the value of discovery experience of traditional retail. After Forever 21’s investment in AI-powered visual search and navigation, a 20 percent increase in average purchase value was seen within one month in May 2018 (Berns Communications Group, 2018). ASOS claimed to have greater engagement with the customers through their investment in technology such as visual search capability in its mobile app, new payment methods, and additional language sites. The brand holds a positive attitude towards enhancing customer experience by investing in technology (ASOS plc, 2017). Furthermore, BooHoo worked with Syte which is a top visual search technology developer to improve customers’ buying journey.

The results showed an increase in overall page visit by 125 percent, customers who used camera research enjoyed an 85 percent higher conversion rate than those who did not, and the conversation rate increased average order value of 12 percent (Syte, 2019). Lastly, Pretty Little Thing use visual AI Camera Search Funnel including social media images to inspire customers and educational funnel to increase the visual search adoption rate. The technology improves search results and product discoverability of their mobile apps. An increase of conversion rate between 2 percent and 11.7 percent was showed in the result (Syte, 2019).

14

Ted Baker’s Shoppable Video Ted Baker’s #TEDPRESENTS film filled with shoppable products for Christmas Season worth being mentioned as an impressive shoppable video that used visual search technology. Figure 5. (Ted Baker, 2019) shows that the video highlights a range of gifting options and clickable tags in the video. It shortens the time for customers to find the ideal item instead of spending extra time on scrolling down the website or going on streets. The video contained their latest designs, conveying a cheerful but elegant vibe for the Christmas season in a snowbound forest. By clicking the tags in the video, it not only provides a more vivid visual effect but also evaluated customers’ shopping experience. Adding visual search technology into the video enhances the quality of interaction with customers and efficiency in shopping progress.

Figure 5: Ted Baker Website, 2019

15

Shop the Runway with Tommy Hilfiger Ta k e To m m y H i l f i g e r ’s 2 0 1 7 runway show as a great example of enhancing customer engagement by applying visual search technology.

The brand had a partnership launched an image recognition app: TOMMYLAND SNAP: SHOP. The audience can instantly shop the items from taking 3D moving photos on the runway, or 2D images to shop the look. Figure 6. (Shorty Awards, no date) shows the garment's detail which is captured from the runway.

Figure 6: Tommy Hilfiger AppCaptured by Shorty Awards, no date

16

Tommy Hilfiger strengthened the customer exp erience f rom the most powerful parts of the mobile phone---the camera, the processing power, and the social photo feed (Mann, 2017). It was mentioned that the time consumers spend on TOMMYLAND SNAP: SHOP app more than double the average time on the website, and they showed a stronger interest in additional show content (Arthur, 2017). As a result, the visual search technology not only generates exposure to its new collection but also enhance engagement with customers. It is true to point out that turning a photo of a model into a wish-list of all the items was a successful marketing strategy.

In conclusion, the adoption of visual search by the brands in the fashion industry draws insight into enhancing customer engagement in a more creative way. Biron (2018) describes the trend of visual search as a tool for the brands to enhance the online shopping experience, expand larger visibility of the products, and increase the profit. Examples show the rapid growth of technology and positive influence on retailers. Powerful smartphones, developing artificial intelligence and consumer interest drive the growth of this exciting trend. More and more retailers use visual search technology to break down language barriers, increase the exposure of items, and offer a more efficient way for customers to look for products. On a global scale, fashion retailers followed technology leaders such as Google and Pinterest to further enhance the shopping experience for their customers, but they implement it more creatively.

17

2. Consumer Behaviour Technology has changed consumer behaviour in retail (Eriksson,Rosenbröijer and Fagerstrøm, 2017). The relationship between consumers and retailers is different from 10 years ago due to the evolved shopping experience and motivations. To understand the consumer behaviour in terms of visual search, the report investigates the online shopping motives from utilitarian and emotional perspectives, the process and experience of online shopping.

2.1 Shopping Motivation: Convenience Is the Key Studies about shopping motivations can be divided into goaldirected and experience-oriented (Sheth, 1983), which means the buying behavior is based on practical or emotional motives. Studies categorize practicality with functional-related websites and hedonic experience with entertainment-related websites (Childers, 2001; WU, et al, 2018). Dawson, Bloch, and Ridgway (1990) describe practical motives as product motives, while hedonic motives are categorized as experiential motives.

From the practical perspective, Svatosová (2013) defines the price, comfort of shopping, time consumption as the motivations of online shopping. Rohm and Swaminathan (2004) state that variety seeking and convenience are the key strength for online shopping while social interaction, time-saving and recreation motives are bricks-andmortar’s motives. However, Pappas and others (2017) have a different view of online shopping motivation which is identifying price and promotion sensitivity.

18

Researches seem to emphasize more on practical perspectives while analyzing shopping motivation in terms of technology, but the hedonic motives have become more important for online shopping.

Rohm and Swaminathan (2004) state that hedonic and recreation experiences are not the most significant motives for online shoppers.

Practical motives attribute more to online shopping (Childers, 2001).

However, with the evolving technology, hedonic motives become more important for online shopping experience (Ha & Stoel, 2010; Childers, 2001). Ha and Stoel (2010) highlight the significance of recreation for online shopping. They point out the combination of practical motives and experiential features can be a key driver for online apparel shopping. Consumers’ attitudes toward interactive technology have changed and they might expect more enjoyment for online shopping (Childers, 2001).

The key motivation of visual search can be defined from the utilitarian perspective – Convenience is the key. The definition of convenience in terms of online shopping is interpreted as time and effort saving, which can be discussed as travel time, finding the products and check out time (Bhatnagar, et al., 2000; Rohm & Swaminathan, 2004). Although online shopping is regarded as more convenient than in-store shopping (Beauchamp & Ponder, 2010), customers still regard search inconvenience as the main issue while taking a variety of search options, user-friendly website, and the efficiency of finding desired products into consideration (Jiang, Yang & Jun, 2013).

The rise of visual search provides the practical motives for online consumers by removing the major obstacle of traditional on-line shopping: spending too much time on e-commence to look for the products we want. The evolved online shopping process was predicted by Ramirez (2018), saying that the shortened process of going from inspiration to purchasing directly with single click changed customers’ shopping behaviours, they no longer want to spend time browsing the catalog on an online shopping website.

19

2.2 Shopping Experience: Consumers Empowerment & Experimental Value Great experience with a high level of emotional intensity is memorable (Arnould & Price, 1993; Adobe & Goldsmiths University Of London, 2016). The shopping experience has become one of the most important marketing tools nowadays that brands do not only aim to promote their product but to emphasize on providing a pleasant environment and experience, such as AI interactive technology, concept store, customer service, etc. Consumers are not just rational decision-maker based on function and benefit, but emotional who wants to enjoy the experience (Schmitt, 2000). It was suggested that the experienceoriented website has better engagement with customers than the purpose-oriented website (Novak, Hoffman, and Yung, 2000).

The concept of ‘Consumer Empowerment’ represents the idea that consumers have control of their own choices while enjoying the experience of shopping, banking or other service and internet environments offered by the firms with interesting and relevant information, there are bigger possibilities for them to spend longer time and purchase more (Wright, et al., 2006). Consumers can control their shopping path and the information they receive, so that the service and environment offered by the website influence their shopping behaviours (Menon & Kahn, 2002; Alba, et al, 1997).

Retailers benefit from empowering consumers by providing them with what they want. As the classic economic theory states that helping consumers to make decisions is certainly a benefit (Kreps, 1979).

Consequently, the relationship between visual search and customers can be applied to the concept of consumer empowerment. It leads to a closer match of individual needs by offering customers more controllable shopping experience.

20

However, Wathieu (2002) argues that consumer control may have possibilities to hurt both the experiences of decision making and consumption. As the customers will have a higher expectation of the service and products.

The failure of providing a good experience can be particularly harmful to brands (Kawaf & Tagg, 2017).

E x p e r ime nt a l va lue pl ay s a s ig nif ic ant role in visual search. Perceived experience impacts consumer’s decisions, purchases, and satisfaction (Fiore & Kim, 2007). Improving the experience of using the app can enhance the brand’s value, based on consumers’ perception of performance, productivity, and effectiveness of the app (Rezaei & Valaei, 2017).

S ong ( 2 0 1 5 ) prove s t h e i mp or t an c e of experimental value in terms of shopping site’s attractiveness and specifically looked into the utilitarian aspect which are decision convenience, access convenience, and benefit convenience. Furthermore, it was suggested that providing the experience of practicality, hedonism, and social engagement can lead to higher purchase intention (Dlodlo, 2014). This is to say, convenience plays a significant role in improving the experience and is viewed as experimental value which can lead to higher purchase intention. The experimental value of visual search and to what extent it can enhance customer engagement will be further discussed below.

21

Throughout the secondary research, this report investigates aspects of how visual search has been applied in the fashion industry and how it can be defined in theoretical aspects. The resources show that visual search in the fashion industry is still at its infant stage, only prominent brands has adopted the technology, the positive outcome showed the necessity of keeping up with this trend. From the observation of visual search applications in the fashion industry to the extended understanding of theories, advantages and disadvantages of visual search will be put into the discussion to predict the future development and challenges in the fashion industry.

22

1. Advantages:

Motives of Convenience

Visual search creates motives for not only the consumers who seek for efficient research but also for those who do not know how to describe the image in words. Analysis of theoretical sources points out that convenience is one of the key motives of online shopping but indicates the inconvenience of long searching progress. The opportunities can be seen from the trend that Millennials and Gen Z embrace new technology, and willing to pay a premium for convenience (Haslehurst & Saavedra, 2017; Janka & Dagmar, 2016).

The proliferation of social media changes the way we search, consumers are bombarded with vast quantities of images. People nowadays are not only consumers but participants (B ergstrom, 2008). C onsumers look for inspirations, styles, trends through social media.

Searching by images can fulfill consumer’s needs more efficiently than searching by texts.

Especially fashion apparels are frequently purchased that it can form habits and customer loyalty (Singh & Srivastava, 2018), ease of use can be experienced profoundly while the searching progress has been largely improved.

In other words, the shopping experience can be improved by avoiding long searching progress, which might lead to customer’s impatience and exit the shopping website.

23

Customer Engagement and Entertained Shopping Experience

Based on the observation of fashion retailers, the report discovers that the usage of visual search mainly enhances customer engagement and raise their interests in the products. On the other hand, customers establish interactivity and connection with the brand through the camera, but this new way of search draws consumers' attention and increases product discoverability. By improving the shopping experience through visual search, engagement and interactivity are key elements to establish a successful relationship with customers(Ahn, et al., 2014).

Visual search is mainly helpful for practical motives but can be implemented to improve the hedonic experience. It adds the experiential value which is mainly perceived from in-store shopping. In general, consumers who go to bricks and mortar store are more attached to the enjoyment and entertainment experiences (Rajamma, Paswan, & Ganesh, 2007), but visual search breaks the limitation of phone’s screen size, such shopping experience can be enhanced by putting on the camera through shopping process. To support the success of visual search, it has been suggested that the combination of shopping experience and online motivation can predict a higher intention to purchase for customers. (Pappas, L.O., et al, 2017)

24

From Passive to Active Customers

Do consumers actually know what they want before they purchase the item? The technology of visual search triggers this question to be discussed again. Consumer’s decision on purchasing a product is based on their visual saliency, they already made their preference when they browse the products (Gidlöf, et al., 2017). However, Riquelme (2001) argued that customers do not understand themselves as much as marketers. He declared that customers are not able to predict their purchase decision. It was mentioned by Simonson (1993) that consumers’ preferences are fuzzy and imprecise which can be impacted by a variety of factors, including the consideration of alternatives, the manner of purchasing, the description, the timing and quantity, and the features. Hence, there is always a struggle between retailers and customers. How can we illustrate the inner expectation of customers and maximize the effect of marketing? Instead of giving the options and let the customers browse the catalog, visual search offers a chance for customers to show the brand ‘what they are looking for’ and assists them to decide.

The research points out the future trend of technology should emphasize on smart use of data, enhancing engagement by helping customers to make better decisions (Adobe & Goldsmiths University of London, 2016). Instead of just collecting data, clever use of the visual search is required to further improve experiences, deepen relationships and stay relevant in the rapidly-changing fashion industry.

The theories of consumer empowerment which were mentioned above can be interpreted and applied to visual search which empowers customers with a more controllable searching process. Instead of browsing from tedious catalogs and being given the choices, Consumers become a more active character by conveying direct inquiry to the brands. They are capable of telling the brands what they are interested in, and such data can be collected more efficiently and precisely to analyze consumer behavior, including personal preferences and buying habits.

25

Establish Trust and Loyalty

As Zhang (2018) stated that giving recommendations of similar products can improve shopping experience which leads to loyalty and satisfaction. The convenience of visual search can be remembered by the consumers (Adobe & Goldsmiths University Of London, 2016). From consumers’ perspectives, if a brand is willing to invest in new technology to improve their shopping experiences, it can increase consumers’ trust and believe that the brand cares about them.

Increase Conversion Rate

From the marketer perspective, the outcome of those fashion brands who adapted visual search technology has shown growth in conversion rates. Gudigantala and others (2016) claim that higher purchase intention is positively related to conversion rate. Providing additional functionalities such as affiliate programs and advanced search can increase levels of conversion rate(Ayanso & Yoogalingam, 2009).Visual search provides advanced search functionalities and product recommendation which have higher possibilities to make consumer place items impulsively before proceeding to purchase (Vilner, 2017). In addition, personalized services can lead to satisfaction and purchase intention (Thongpapanl & Ashraf, 2011), visual search provides relevant products based on each customer’s different demands to increase purchase intention.

Consequently, the reason why visual search can improve conversion rate is that it provides a more satisfying shopping experience and attract a higher volume of website visitors, so a higher purchase intention appears in this case.

26

2. Disadvantages: Usage of Images: Copyright and Privacy

The technology of visual search is based on the cloud computing environment, so the usage of images by CBIR system has been an issue (Tyagi, 2017). Weng and others (2015) mentioned that privacy should be emphasized on photo-sharing websites because the database might contain private information. People can download images from wherever they want and utilize them as an inspiration to look for similar products, the copyright of the images might be ignored and damage the original creator. As technology can analyze the outfit of random people on the street, taking a picture of people without their permission might also intrude on others’ privacy.

Gap Between Human Understanding and Machine Interpretation

Tyagi (2018) mentioned the problem of Content Base Image Retrieval is the gap between the human imagination and computers’ interpretation. Although visual search improves the efficiency of searching for ideal products, the human mind is more complex than the technology still cannot understand precisely.

The failure of matching with customer’s ideal items and the misinterpretation of the technology might lead to their disappointment of the brand which might impact their shopping preference next time.

27

What about those customers who do not know what they are looking for?

The major concern about visual search is the limitation of utilizing the technology. To use the technology, customers are required to have similar images which represent their imaginations. In details, the convenience of technology is only helpful for those who have ideas, but it does not make any differences for those who are randomly browsing the website. Consequently, different function of visual search compensates each other, such as shoppable contents which play a significant role to arise inspiration and

3. Future Challenges and Possibilities:

Improve the Website’s Cognitive Fluency

Visual search shortened the research process and improved the shopping experience, so the shopping process might accelerate when people are more used to efficient online shopping. It is important to ensure the website’s cognitive fluency so that the visual search can maximumly benefit both customers and retailers. However, the theory of consumer empowerment suggests expanding the time that consumers spend on the shopping process to increase the opportunity of placing purchases while the visual search technology shortens it reversely. Pleasing stimuli can encourage consumers to stay longer at the website and to place purchase impulsively (Menon & Kahn, 2002).

Hence, it is necessary that retailers need to strike a balance between accelerating the shopping progress for consumers but also attracting them to stay longer on the websites simultaneously.

28

Promotion Application in the Visual Search

At the current stage, visual search has not been used as a promotion tool, so there are chances to apply related advertisements on visual search. To illustrate, related products can be recommended by the brands when customers upload pictures. Promotions through visual search can target the market more accurately.

Enhance Value of the Product

Visual search can be considered not only as an improvement of the customer shopping experience but also as another creative way of increasing the value of products.

Transparency and sustainability have become a common awareness among the customers and a significant trend in the fashion industry (Passport, 2019). Therefore, it is a good opportunity for brands to win customers’ trust by showing their concern about this issue through visual search technology. If customers can gain information about the brand or trace the history of each product from putting the camera on its product, it can be more convincing by looking at the product and establish a stronger connection with the brand.

29

This study provides a wider understanding of the current stage of visual search in the fashion industry and further insight into future challenges and possibilities.

Firstly, the report integrates the phenomenon of visual search from the adoption in the fashion industry and the leading technology, defining it through the theoretical lens from online consumers' motivations and shopping experiences. In the analysis of secondary sources, the report defines that visual search can attach practical motives which is more efficient searching progress and concretize consumer’s demand which might be difficult to describe in words, enhance shopping experience from entertainment and engagement with the brand, and empower customers.

Secondly, the report discusses the pros and cons of visual search. The major function of visual search is improving the shopping experience by convenient shopping progress, empowering customers, and a more vivid and creative way of delivering products to the customers.

The advantages of visual search contain the motives of convenience, customer engagement and entertainment, reversing customer’s position from passive to active, the establishment of trust and loyalty, and increase of conversion rate. Disadvantages of visual search are considered as the risks of image copyright and privacy which might be intruded by taking other people’s pictures, the gap between human understanding and interpretation which might cause damages to customer’s trust, and the limitation that customers who do not have concrete inspiration cannot gain benefits from this technology.

30

Based on the analysis and discussion of the phenomenon, the report suggests that marketers in the fashion industry should be aware of this rising trend and consider if the brand’s market position is suitable to adopt this technology to further enhance customer experience and improve sales numbers. For those who had already utilized the technology, future challenges and possibilities of visual search are predicted in the last part. Retailers should also focus to improve the website's cognitive while adopting this technology due to the acceleration of shopping progress and strike a balance between shortening the shopping progress and extend the time that consumers spend on their websites.

From the marketer’s perspective, opportunities for promotion and enhancement of the product’s value can be implemented by utilizing the technology of visual search.

31

Visual search is a new phenomenon that has been widely discussed on media platforms in recent years, but related academic research is hardly found. Due to the time limitation, this report’s research is only based on secondary resources. It is crucial to mention that there are more than 75,000 researches have investigated the technology of CBIR, but the usage of technology on the e-commence is still at the infant stage. There are no theories based on the relationship between CBIR and online retailers, so the academic background of this phenomenon is scarce.

However, the report defines the phenomenon from analyzing the results of visual search among fashion retailers and applying theories of consumer behaviors.

The relationship of fashion retailers and visual search needs to be further discussed in the recent future.

32

33

Adobe & Goldsmiths University Of London, 2016. The Future Of Experience.

[Online] Available at: https://blogs.adobe.com/digitaleurope/files/2016/07/Adobe-Report-The-Future- of-Experience.pdf [Accessed 28 Oct 2019].

Ahn, T., Hong, M. & Pedersen, P., 2014. Effects of perceived interactivity and web organization on user attitudes.. European Sport Management Quarterly[online],14(2), pp. 111-128. Available at: http://www.tandfonline.com/doi/abs /10.1080/16184742.2014.880496.[Accessed 27 Oct 2019].

Alba, J., et al, 1997. Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. Journal of Marketing[online], 61(3), pp. 38-53. Available at: http://search.proquest.com/ docview/227748235/[Accessed 29 Oct 2019].

Arnould, E. & Price, L., 1993. River Magic: Extraordinary Experience and the Extended Service Encounter. Journal of Consumer Research[online], 20(1), p. 24–45. Available via: JSTOR. [Accessed 30 Oct 2019] Arthur, R., 2017. Tommy Hilfiger’s image recognition app drove new web traffic and engagement. [Online]. The Current Daily. Available at: https://thecurrentdaily.com/2017/03/07/tommy-hilfiger-image-recognition/ [Accessed 29 Oct 2019].

ASOS plc, 2017. Global Online Fashion Destination: Final Results for the year to 31 August 2017 [online]. ASOS plc. Available at: https://www.asosplc.com/~/ media/Files/A/Asos-V2/results-archive/statement/full-year-results-2017.pdf [Accessed 29 Oct 2019].

Ayanso, A. & Yoogalingam, R., 2009. Profiling Retail Web Site Functionalities and Conversion Rates: A Cluster Analysis. International Journal of Electronic Commerce [online], 14(1), pp. 79-133. Available at: http:// www.tandfonline.com/doi/abs/10.2753/JEC1086-4415140103.[Accessed 29 Nov 2019] Bailey, P., 2016. The Role of Brand, Advocacy & Trust For Generation Y and Z. [online] Available via: Ipsos Marketing [Accessed 29 Nov 2019] Beauchamp, M. B. & Ponder, N., 2010. Perceptions of retail convenience for in‐store and online shoppers. Marketing Management, 20(1), pp. 49-65. Available via: Ebsco [Accessed 29 Oct 2019]

34

Beck. K, 2017. Why Shopping Is About To Become All About The Experience. BB C[Online], 24 Nov, Available at: https://www.bbc.com/worklife/article/20171123-why-shopping-is-about-to-become-all-about-theexperience [Accessed 26 Oct 2019].

Bergstrom, B., 2008. Essentials of Visual Communication. London: Laurence King Publishing Ltd. Berns Communications Group, 2018. Forever 21 Introduces AI-Powered Visual Search and Navigation from Donde Search. Business Wire[Online].Available at: https://www.businesswire.com/news/home/20180822005090/en/21-Introduces-AI-Powered-Visual-Search-Navigation-Donde[Accessed 26 Oct 2019] Bhatnagar, A., Misra, S. & Rao, H., 2000. On Risk, Convenience, and Internet Shopping Behavior. Communications of the ACM [Online], 43(11), pp. 98-105. Available at: http://search.proquest.com/docview/237053988/.

[Accessed 29 Oct 2019] Biron, B., 2018. FASHION Visual Search Technology Wants To Be The Next Frontier of E- commerce[Online]. Glossy. Available at: https://www.glossy.co/ platform-effect/visual-search-technology-wants-to-be-the-next-frontier-of-ecommerce [Accessed 29 Oct 2019].

Boyd, C., 2019. Visual Search — The Ultimate Guide: Statistics, News, Trends, and Tips. [Online]. Medium. Available at: https://medium.com/@ clarkboyd/visual-search-trends-statistics-tips-and-uses-in-everyday-lifed20084dc4b0a#077a [Accessed 27 Oct 2019].

Chennapragada, A., 2018. The Era of The Camera: Google Lens, One Year In. Google [online blog],19 Dec, Available at: https://www.blog. google/perspectives/aparna-chennapragada/google-lens-one-year/ [Accessed 25 Oct 2019].

Chennapragada, A., 2019. Helpful New Visual Features In Search and Lens.

Google [online blog]. 7 May, Available at: https://www.blog.google/products/ search/helpful-new-visual-features-search-lens-io/[Accessed 25 Oct 2019].

Childers, T. e. a., 2001. Hedonic and Utilitarian Motivations For Online Retail Shopping Behavior. Journal of Retailing[Online], 77(4), pp. 511535. Available via: https://doi.org/10.1016/S0022-4359(01)00056-2 [Accessed 2 Dec 2019] Clement, J., 2018. Number of visual searches performed using Pinterest Lens by users worldwide in February 2017 and February 2018 (in million of searches)[Online]. Available via: Statista [Accessed 16 Oct 2019].

35

Dawson, S., Bloch, P. & Ridgway, N., 1990. Shopping Motives, Emotional States, and Retail Outcomes. Journal of Retailing[Online], 66(4), p. 408. Available at: http://search.proquest.com/docview/228610302/. [Accessed 2 Dec 2019] Dlodlo, N., 2014. Developing An Online Shopping Value Framework For Consumers Of Non-Store Fashion Brands. The International Business & Economics Research Journal [Online], 13(6). Available at: http://search.proquest.com/ docview/1625360377/. [Accessed 2 Dec 2019] Emarketer, 2018. What New Technologies Would UK and US Younger vs. Older Millennial Internet Users Be Comfortable with as Part of Their Digital Shopping Experience? (% of respondents, by age, July 2018). [Online] Available via: Emarketer [Accessed 17 Oct 2019].

Eriksson, N., Rosenbröijer, C. & Fagerstrøm, A., 2017. The relationship between young consumers’ decision-making styles and propensity to shop clothing online with a smartphone.Procedia Computer Science[Online], Volume 121, pp.

519-524. Available via: https://doi.org/10.1016/j.procs.2017.11.069 Emarketer [Accessed 17 Oct 2019].

Fiore, A. & Kim, J., 2007. An integrative framework capturing experiential and utilitarian shopping experience. International Journal of Retail & Distribution Management[online], 35(6), p. 421. Available at: https://doi. org/10.1016/j.procs.2017.11.069 [Accessed 12 Nov 2019].

Fiore, A. M., Hyun-Jeong, J. & Kim, J., 2005. For fun and profit: Hedonic value from image interactivity and responses toward an online store. Psychology & Marketing, 22(8), pp. 669- 694.Available at: http://search.proquest.com/ docview/227745404/.[Accessed 13 Nov 2019].

Gidlöf, K., Anikin, A., Lingonblad, M. & Wallin, A., 2017. Looking Is Buying.

How Visual Attention and Choice are Affected By Consumer Preferences and Properties of the Supermarket Shelf. Apetite[online], Volume 116, pp. 29-38.

Available at: https://doi.org/10.1016/j.appet.2017.04.020 [Accessed 19 Nov 2019].

Google Lens, no date. Google Lens [Online]. Google. Available at: https:// lens.google.com/ [Accessed 13 Dec. 2019]. [Figure.].

Gudigantala, N., Bicen, P. & Eom, M., 2016. An examination of antecedents of conversion rates of e-commerce retailers. Management Research Review[online], 39(1), pp. 82-114.

Available via: Emerald [Accessed 24 Nov 2019].

36

Hanna, R., Rohm, A. and Crittenden, V.L., 2011. We’re All Connected: The Power Of The Social Media Ecosystem. Business Horizons[online], 54(3), pp.

265-273. Available at: http://search.proquest.com/docview/863571847/ [Accessed 22 Oct 2019].

Haslehurst.R, Saavedra.S, 2017. Retailers Play the Generation Game: Lessons From Adapting to Millennials[online], Boston: L.E.K. Consulting. Available at: https://www.lek.com/insights/ei/retailers-lessons-adapting-millennials [Accessed 12Nov 2019].

Ha, S. & Stoel, L., 2010. E-tail Evolution: Motives and Behavioral Intentions of E-shopper Segments[online]. Journal of Global Fashion Marketing, 1(1), pp. 9-18. Available at: http://www.tandfonline.com/doi/abs/10.1080/2093268 5.2010.10593053. [Accessed 2 Nov 2019].

Hu, Y., Yin, H., Han, D. and Yu, F., 2014. The Application of Similar Image Retrieval in Electronic Commerce. The Scientific World Journal[online], Volume 2014. DOI: 10.1155/2014/579401 [Accessed 12 Nov 2019].

Iyer, G & Kuksov, D;, 2012. Competition in Consumer Shopping Experience. Marketing Science[online], 31(6), pp. 913-933. Available via: JSTOR [Accessed 13 Nov 2019].

Janka, K. & Dagmar, K., 2016. Consumers in New Millennium: Attitudes Towards Adoption of New Technologies in Purchasing Process. Studia Commercialia Bratislavensia[online], 9(33), pp. 65-74. Available at: http://search.proquest.com/docview/1813305201/. [Accessed 12 Nov 2019].

Jiang, L., Yang, Z. & Jun, M., 2013. Measuring Consumer Perceptions of Online Shopping Convenience. Journal of Service Management[online], 24(2), pp.

191-214.

DOI:10.1108/09564231311323962 [Accessed 12 Nov 2019].

Kawaf, F. & Tagg, S., 2017. The Construction of Online Shopping Rxperience: A Repertory Grid Approach. Computers in Human Behavior[online], Volume 72, pp. 222-232.Available at: https://doi.org/10.1016/j.chb.2017.02.055 [Accessed 12 Nov 2019].

Kreps, D., 1979. A Representation Theorem For ‘’Preference Flexibility”.

Econometrica(pre1986) [online], 47(3), p. 565. Available via: JSTOR[Accessed 12 Nov 2019].

L. Weng, L. Amsaleg, A. Morton and S. Marchand-Maillet, 2015. A Privacy-Preserving Framework for Large-Scale Content-Based Information Retrieval. IEEE Transactions on Information Forensics and Security[online], 10(1), pp. 152-167. Available via: IEEE [Accessed 12 Nov 2019].

37

Mann, T., 2017. Introducing TommyNow Snap — The 1st Visual Search Runway App, Slyce[online blog], 19 Sep.Available at: https://slyce.it/2017/09/19/ introducing-tommynow- snap-visual-search/ [Accessed 27 Oct 2019].

McMillan, S., Hwang, J. & Lee, G., 2003. Effects of structural and perceptual factors on attitudes toward the website. Journal of Advertising Research[online], 43(4), pp. 400- 409.DOI: 10.2501/JAR-43-4-400-409[Accessed 1 Dec 2019].

Melvin, A., 2016. Dress, Fahion and Technology From Prehistory to the Present. Dress[online], 42(2), pp. 125-127. Available at: http://www.tandfonline.com/doi/abs/10.1080/03612112.2016.1215827.[Accessed 27 Oct 2019].

Menon, S. & Kahn, B., 2002. Cross-category effects of induced arousal and pleasure on the internet shopping experience. Journal of Retailing[online], 78(1), pp. 31-40. Available at: https://doi.org/10.1016/S0022-4359(01)000641[Accessed 27 Nov 2019].

Novak, T. P., Hoffman, D. L. and Yiu-Fai Yung, 2000. Measuring the Customer Experience in Online Environments: A Structural Modeling Approach. Marketing Science[online], 19(1), p. 22. DOI: 10.1287/mksc.19.1.22.15184. [Accessed 27 Oct 2019].

Pappas, L.O., et al, 2017. The interplay of online shopping motivations and experiential factors on personalized e-commerce: A complexity theory approach.

Telematics and Informatics[online], 34(5), pp. 730-742 . DOI: 10.1016/ j.tele.2016.08.021. [Accessed 4 Nov 2019].

Passport, 2019. World Market for Apparel and Footwear[online]. Available via: Passport. [Accessed 27 Oct 2019].

Pichai, S., 2016. This year’s Founders’ Letter, Google [Online Blog], 28 April.

Available at: https://blog.google/topics/inside-google/this-years-founders-letter/ [Accessed 28 Oct 2019].

Pinterest, 2018. Celebrating One Year of Pinterest Lens. Pinterest[online blog], 8 February. Available at: https://newsroom.pinterest.com/en/post/celebrating-one-year-of-pinterest-lens [Accessed 30 Oct2019].

Raconteur, 2019. #VisualSearch[Online] Raconteur. Available at: https://res. cloudinary.com/yumyoshojin/image/upload/v1570113411/pdf/VisualSearch.pdf [Accessed 27 Oct2019].

38

Rahamma, R.K., Paswan, A.K. and Ganesh, G., 2007. Services Purchased at Brick and Mortar Versus Online Stores, and Shopping Motivation. The Journal of Services Marketing[Online], 21(3), p. 200. DOI: 10.1108/08876040710746552. [Accessed 15 Nov 2019].

Ramirez, S., 2018. Farfetch latest luxury retailer to launch on-the-go visual search, Luxury Daily[Online]10 December. Available at: https://www.luxurydaily.com/farfetch-latest-luxury-retailer-to-launch-on-the-go-visual-search/ [Accessed 31Oct 2019].

Rezaei, S. & Valaei, N., 2017. Crafting experiential value via smartphone apps channel. Marketing Intelligence & Planning[online], 35(5), pp. 688-702.DOI: 10.1108/MIP-08-2016- 0141. [Accessed 31 Nov 2019].

Riquelme, H., 2001. Do Consumers Know What They Want?. Journal of Consumer Marketing[online], 18(5), pp. 437-448. DOI: 10.1108/07363760110398772. [Accessed 31Oct 2019].

Rohm, A. & Swaminathan, V., 2004. A Typology of Online Shoppers Based on Shopping Motivations. Journal of Business Research[online], 57(7), pp.

748-757. Available at: http://search.proquest.com/docview/196326567/.[Accessed 31Nov 2019].

Schmitt, B., 2000. Experiential marketing : how to get customers to sense, feel, think, act, and relate relate to your company and brands. New York : Free Press.

Sherman, L. E. et al., 2018. Peer Influence Via Instagram: Effects on Brain and Behavior in Adolescence and Young Adulthood. Child Development[online], 89(1), pp. 37-47. DOI: 10.1111/cdev.12838. [Accessed 26 Oct 2019].

Sheth, J., 1983. An integrative theory of patronage preference and behavior,.

In: Patronage Behavior and Retail. New York: North-Holland, pp. 9-28.

Shorty Awards, no date. TOMMY HILFIGER SNAP APP. [Online] Available at: https://shortyawards.com/10th/tommy-hilfiger[Accessed Oct 2019]. [figure.].

Simonson, I., 1993. Get Closer to Your Customers By Understanding How They Make. California Management Review[online], 35(4), p. 68. Available at: http://search.proquest.com/docview/216141465/.[Accessed 31Oct 2019].

39

Singh, S. & Kumar, P., 2018. User specific context construction for personalized multimedia retrieval. Multimedia Tools and Applications[online], 77(11), p.

13459–13486. DOI: 10.1007/s11042-017-4961-x. [Accessed 31Oct 2019].

Singh, S. & Srivastava, S., 2018. Engaging consumers in multichannel online retail environment: A moderation study of platform type on interaction of e-commerce and m- commerce. Journal of Modelling in Management[online], 14(1), p. 49–76. DOI: 10.1108/JM2-09-2017-0098. [Accessed 29 Nov 2019].

Smith, J., 2018. Pinterest’s Visual Search Platform Is Growing, Business Insider [Online Blog] Available at: https://www.businessinsider.com/pinterests-visual-search-platform-is-growing-2018-2?r=UK&IR=T.[Accessed 26 Oct 2019].

Song, S., 2015. Identifying On-line Shopping Experiences From The Perspective of Shopping Motives. Academy of Marketing Studies Journal [Online], 19(3), pp. 139-148. Available at: http://search.proquest.com/docview/1768357481/.

[Accessed 25 Nov 2019].

Svatosová, V., 2013. Motivation of Online Buyer Behavior. Journal of Competitiveness, 5(3).

Syte, 2019. Case Study: Boohoo.com. [Online] Syte. Available at: https:// www.syte.ai/wp-content/uploads/2019/07/Syte-Case-Studies-Boohoo.pdf [Accessed 31 Oct 2019].

Syte, 2019. Case Study: PRETTYLITTLETHING.COM. [Online]. Syte. Available at: https://www.syte.ai/wp-content/uploads/2019/07/Syte-Case-Studies-PrettyLittleThing.pdf [Accessed 31 Oct 2019 ].

Ted Baker, 2019. #TEDPRESENTS [Online]. Ted Baker.

Available at: https://www.tedbaker.com/row/mens/editorial/shoppable_video_p2[Accessed 28 Oct 2019].[Figure.].

The Economist Intelligence Unit, 2008. Future Tense: The Global CMO[online].The Economist. Available at: http://graphics.eiu.com/upload/Google%20 Text.pdf [Accessed 31 Oct 2019 ].

Thongpapanl, N. & Ashraf, A., 2011. Enhancing Online Performance through Website Content and Personalization. Journal of Computer Information Systems [Online], 52(1), pp. 3-13. Available at: http://search.proquest.com/ docview/903556078/.[Accessed 31 Nov 2019 ].

40

Trafton, A., 2014. In The Blink Of An Eye, MIT News[Online],16 January, Available at: https://news.mit.edu/2014/in-the-blink-of-an-eye-0116[Accessed 26 Oct 2019].

Tyagi, V., 2017. Research Issues for Next Generation Content-Based Image Retrieval. In: Content-Based Image Retrieval. Singapore: Springer.

Tyagi, V., 2018. Content-Based Image Retrieval: An Introduction. Singapore: Springer.

Vilner, Y., 2017. 5 Ways Visual Search Amplifies the eCommerce Experience, Inc[Online Blog] Available at: https://www.inc.com/yoav-vilner/5-ways-visual-search-amplifies-ecommerce-experience.html [Accessed 27 Oct 2019].

Walker, R., 2016. Retailers Eye Brave New World of Visual Search[Online]. Available via: Passport[Accessed 16 Oct 2019].

Wright, L. T., Newman, A. & Dennis, C., 2006. Enhancing consumer empowerment. European Journal of Marketing[online], 40(9), pp. 925-935. [Accessed 18 Nov 2019] Zhang, H., 2018. The Role of Online Product Recommendations on Customer Decision Making and Loyalty In Social Shopping Communities. International Journal of Information Management[online], 38(1), pp. 150-166. [Accessed 18 Nov 2019]

41