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Why: India’s luxury market is expanding rapidly, driven by a rising middle class and affluent young consumers. While still relatively untapped, the combination of a youthful population and increasing disposable income presents vast growth potential.

Gen Z appeal: Indian Gen Z consumers have a growing appetite for luxury fashion, fueled by social media exposure and a desire for global trends, despite India’s traditionally conservative market.

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1. Demographic dividend：

Large proportion of young population/increased spending power

2. Economic growth：

India's continued economic growth/wealth accumulation

3. Entry and expansion of luxury brands：

Increased interest from international brands/localized cooperation and strategy

4. Promotion of digitalization and e-commerce：

The rise of e-commerce platforms/social media influence

5. Cultural and psychological changes：

Changes in consumer mentality/international fashion sense

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Circular Fashion and Extended Product Life Cycles

Focus: Brands will increasingly adopt circular business models, where products are designed to be reused, repaired, or recycled. Companies will emphasize take-back programs, resale, and upcycling initiatives.

Key Drivers: Pressure to reduce waste and environmental impact, particularly in light of growing environmental regulations.

Example Trends: Resale markets, rental fashion, repair services, and upcycling collections.

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Sustainable Practices and Recycling Initiatives

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Sustainable Practices and Recycling Initiatives

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There's a growing emphasis on sustainability, with brands investing in textile-to-textile recycling to reduce waste and reliance on virgin materials. Startups like Reju, Circ, and Syre are developing new processes and facilities to enhance recycling capabilities within the fashion industry.

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Is fashion recycling finally heading for a breakthrough?

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Textile-to-textile recycling is crucial for enabling a circular ecosystem, but commercialisation has been evasive. That may be starting to change.

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The manufacturing industry is undergoing a profound transformation, driven by:

Low-Cost Fabrication Tools: Affordable and user-friendly tools like 3D printers and CNC machines enable more people to participate in manufacturing.

Digital Customization: Digital technologies and automation make personalized production possible, catering to consumer demand for customization.

Lower Barriers to Entry: More individuals can become "makers," promoting small-scale and creative production.

Potential Impacts

Industry: Traditional mass production faces challenges as supply chains become more flexible and decentralized.

Commerce: Retail methods are shifting, with on-demand production and customized products on the rise.

Society: Urban layouts may change with the increase of maker spaces, and more opportunities for entrepreneurship emerge.

Sustainability: Localized, on-demand production reduces waste and supports environmental sustainability.

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Emergence: flexible electronics combined with textiles (e.g. heated jackets, health monitoring clothing).

-Evolving: 5G and IoT driving real-time data interaction, e.g. NFC chips enabling clothing authentication.

-Evolution over the next decade: AI-powered adaptive clothing (adjusting temperature/shape to the environment), crossover applications of brain-computer interfaces and fashion.

- Supporting data: citing IDC wearables market forecasts, MIT Media Lab case studies, etc.

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Development:

Currently, digital tools are transforming every aspect of the fashion industry. AI-powered design tools enable hyper-personalization and rapid prototyping (ArXiv, 2024). Virtual try-ons using AR and VR are enhancing online shopping experiences, reducing returns and waste (Statista, 2022). The rise of digital fashion on platforms like Roblox and Decentraland is creating new revenue streams (BoF, 2023). Furthermore, blockchain is being used to authenticate luxury items and ensure supply chain transparency (McKinsey, 2023).

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Emergence: social media and independent designer platforms （ such as Dropr) to break the fashion discourse dominated by Europe and the US.

-Development: globalisation of indigenous cultural symbols (African batik, Middle Eastern embroidery) through digital tools (NFT, virtual fashion).

-Evolution in the next decade: the rise of cross-cultural collaborative design in the meta-universe, the revival of niche cultures through AI-generated technologies.

-Supporting data: reference to UNESCO Cultural Diversity Report, Vogue Business Emerging Markets Analysis, etc.

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1.Modest Growth:

Fashion industry growth remains low, stabilizing at low single-digit rates for 2025.

Non-luxury fashion is expected to drive growth for the first time since 2010, as luxury slows down.

2.Challenges:

Persistent macroeconomic uncertainty and declining consumer confidence.

70% of executives highlight consumer spending as a major risk, driven by price sensitivity.Geopolitical instability and supply chain disruptions remain top concerns.

3.Focus Areas for Brands:

Differentiation: Executives are emphasizing new designs, customer experiences, and expanding price ranges to appeal to a broader audience.

Localization: Tailoring assortments and pricing to local markets is seen as essential.Sustainability has taken a backseat to immediate profitability goals.

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1.Asia’s Role:

China’s deceleration: Economic growth slows to 4.5%, with consumer spending lagging. International brands shift focus to India, Japan, and other APAC markets.

India is set to be a major driver, with mid-market fashion growing 12–17% and luxury bolstered by rising incomes and UHNWIs.

2.Global Trade Reconfiguration:

Increased trade barriers and sourcing diversification.

A rise in nearshoring (e.g., Mexico for the U.S., Turkey for Europe) is reshaping supply chains.

3.Consumer Behavior:

Price sensitivity persists, with shoppers favoring resale, off-price, and value-focused offerings.

Generative AI is reshaping product discovery, improving personalization and customer engagement.

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Find the most up-to-date statistics and facts on wearables

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1. Smartwatches and health trackers (health monitoring, exercise analysis)

2. Wearables integration with Internet of Things (IoT)

3. Wearable payment systems (NFC/RFID)

4. Smart Clothing (Smart Shoes, Smart Underwear, Temperature Regulating Clothing)

5. Integration with smart glasses/AR devices (e.g. Meta Ray-Ban, Apple Vision Pro)

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1. Cloud & Edge Computing (Cloud & Edge Integration)

2. Artificial Intelligence & Automated Processes (AI + Business Automation)

3. Data Analytics & Customer Insight Systems (Big Data / CRM / CDP)

4. Cross-Platform Technology Integration (Omnichannel Integration / API Ecosystem)

5. Intelligent Internet of Things (IoT-enabled business)

6. Digital Twin

7. Digital Culture & Upskilling

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1. Cultural Decentralisation: Instead of traditional institutions (media, big brands, authorities) determining the dominant culture, there is a common voice from different groups, communities, sub-cultures.

2. Multicultural coexistence: cultures coexist across ethnic groups, languages, and identities, and marginal cultures are moving into the mainstream.

3. Technologically empowered cultural expression: Web3, DAO, NFT, social media allow individuals and niche communities to have more cultural discourse.

4. Decentralised distribution mechanisms: more egalitarian approaches from content creation to distribution, e.g. TikTok algorithm, community collaboration platforms, ecosystem of independent content creators.

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1. Fashion and aesthetics: cultural aesthetics of different communities are reinterpreted as trends (e.g. Y2K + Asia Remix).

2. Brand Marketing: Brands go from being ‘voices’ to being ‘community members’ (e.g. Gucci Vault, Nike x Afrofuturism).

3. Media creation: independent creators lead the narrative (podcasts, Substack writers, independent magazines).

4. Web3 art communities: the rights and distribution of art creation is entirely dominated by the community on the chain (ArtBlocks, Zora)

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Leveraging new generation Wearable data to Improve Patient Outcomes and Increase Reimbursement

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Leveraging new generation Wearable data to Improve Patient Outcomes and Increase Reimbursement

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The LilyPad Arduino: Toward Wearable Engineering for Everyone

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The LilyPad Arduino: Toward Wearable Engineering for Everyone

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The study explores the initial design considerations, implementation challenges, and educational implications of integrating modular electronics into everyday clothing items. By enabling children to personalise their garments with interactive features, ReWear serves as an educational tool that combines aspects of fashion, technology, and user-centred design.

# data[].attributes.attachment_link.title
The LilyPad Arduino: Toward Wearable Engineering for Everyone

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Electronic textiles, or e-textiles, are an increasingly important part of wearable computing, helping to make pervasive devices truly wearable. These soft, fabric-based computers can function as lovely embodiments of Mark Weiser’s vision of ubiquitous computing: providing useful functionality while disappearing discreetly into the fabric of our clothing. E-textiles also give new, expressive materials to fashion designers, textile designers, and artists, and garments stemming from these disciplines usually employ technology in visible and dramatic style. Integrating computer science, electrical engineering, textile design, and fashion design, e-textiles cross unusual boundaries, appeal to a broad spectrum of people, and provide novel opportunities for creative experimentation both in engineering and design. Moreover, e-textiles are cutting- edge technologies that capture people’s imagination in unusual ways. (What other emerging pervasive technology has Vogue magazine featured?) Our work aims to capitalize on these unique features by providing a toolkit that empowers novices to design, engineer, and build their own e-textiles.

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Digital atmosphere of fashion retail stores

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Digital atmosphere of fashion retail stores

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Fashion and Textiles 7, Article number: 30 (2020) Cite this article

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Abstract

This study sheds light on a prominent issue in retailing: how the digital atmosphere can affect the consumer decision-making process in a fashion retail store. Digital devices and services such as digital screens and digital signage are widely employed in fashion retail stores, transforming the way consumers make decisions about purchasing fashion products. This research investigates how the digital atmosphere affects consumers' purchase behavior patterns based on the attention-interest-desire-search-action-share (AIDSAS) model. The findings show that attention is a key antecedent to interest, desire, and behavioral responses (search, action, and share) triggered by the digital atmosphere. The findings further suggest that attention has significantly positive effects on consumers' purchasing patterns of utilizing the digital atmosphere in two types of fashion retail stores: sports and luxury stores. However, we find that these positive effects are more pronounced for sports retail stores than luxury retail stores. This research contributes to understanding consumer behavior related to the digital atmosphere of fashion retail stores by applying the AIDSAS model and helps uncover the stepwise relationships between attention to the store atmosphere-interest/desire and the products-behavior response. These findings have practical implications that can be applied in the fashion industry.

Introduction

Radical development and proliferation of information and communication technology (ICT) have transformed the way people interact, connect, and communicate, not only with other people but also with their surroundings and business environments (Pantano and Viassone 2014; Henke et al. 2016). ICT refers to technology that enables access to information through telecommunication and can be implemented based on a medium that enables communication with others, such as the Internet, mobile phone, and digital devices (Zhang et al. 2008). Digital devices and services, such as smartphones, digital screens, cloud services, and electronic transfer of information between objects (e.g., smart home services and Amazon dash buttons) have already been an integral part of managing and organizing people's everyday lives (Mitrea et al. 2010; Henke et al. 2016). In addition, the increasing adoption of ICT by traditional industries (i.e., convergence) has further transformed the way people interact with products, brands, and companies (Pantano 2014).

The retail industry has been riding the wave of ICT-driven transformation by integrating ICT into retail stores to enhance communication and interaction with consumers. For example, numerous retail stores have adopted digital kiosks allowing consumers to easily check the location and the level of inventory of an item by themselves. Digital signage such as digital displays and touch screens are also popular ICT devices in retail stores (Dennis et al. 2010; Kent et al. 2018). For example, some ICT services in stores allow shoppers to virtually try on clothing to conveniently check size, fit, or style, and then pay immediately after trying it on (Roggeveen et al. 2016). A retail environment with interactions and experiences that are enhanced through these ICT applications is defined as the digital atmosphere (Inman and Nikolova 2017).

Recent literature points to the significant role of the retail atmosphere in shaping key aspects of consumer decision making in stores (Grewal et al. 2017). Retailers have increasingly employed various sensory elements such as color, music, and scent to attract consumers' feelings, perceptions, and behavior in their stores (Donovan et al. 1994; Grewal et al. 2014; Spence et al. 2014). Given the increasing significance consumers place on the overall experience in decision making, retailers have endeavored to enhance consumers' in-store experiences by offering fun, unique, idiosyncratic, immersive, and interactive engagement (Cearley et al. 2017). Most recently, retailers have adopted digital devices and ICT technologies, such as digital kiosks, virtual mirrors, self-checkout, and augmented reality in offline stores. These innovations allow consumers to choose items, try them on, and coordinate various items with a simple touch (Dennis et al. 2012; Duncan et al. 2016).

Retailers have also utilized ICT to integrate operations of different retailer channels to offer consumers more streamlined experiences (Verhoef et al. 2015). For example, a touch screen, self-service kiosk in an offline store allows consumers to return items that were purchased online and/or through mobile channels (Piotrowicz and Cuthbertson 2014). These digital devices installed in store can also integrate retail channels into a system that shares data. For instance, consumers can easily transmit information acquired from the in-store digital devices to their mobile devices with only a few taps on the digit al screen, thus promoting online world-of-mouth behavior (Dennis et al. 2013, 2014).

Despite the significant transformation of the retail environment using in-store digital devices, systematic research investigating the effects of stores' digital atmosphere on consumer behavior is still sparse. The prominent trends and increasing investment in exploring ways to enhance the consumer experience with ICT applications in store call for further studies investigating how a store's digital atmosphere impacts the way consumers evaluate and form behavioral intentions while shopping in retail stores. This study aims to fill this void. In particular, the current study examines how the digital atmosphere, which is widely employed in fashion retail stores, affects consumers' purchase behavior patterns in two different retail contexts: sports (e.g., Adidas) and luxury (e.g., Burberry) brands in fashion retail stores. Sports and luxury brands are chosen because they are in the two most significant merchandise categories that have been most affected by the adoption of ICT technologies in a retail environment.

This study is organized using the following structure. First, we review the literature used to build our conceptual framework and hypotheses. We then present the data collection methods and analyses. Lastly, we discuss our results along with the conceptual and practical implications of the study.

Literature review

Digital atmosphere in fashion retail stores

"Atmospherics" is a practice that recognizes that a marketing environment should be carefully sculpted to induce particular behaviors and evaluations from consumers, and it should appeal to a specific target market (Turley and Bolton 1999). The space created through atmospherics is the store's atmosphere. It is important for retailers to create the appropriate atmosphere to induce consumers' desirable thoughts and feelings about the brands (Kotler 1973; Chebat and Dubé 2000). The store atmosphere is particularly critical for product categories where purchase decisions are affected by in-store experiences in addition to product attributes, such as clothing (Donovan et al. 1994). As such, researchers have paid considerable attention to understanding how experience-focused consumption decisions are affected by sensory variables in the store such as the choice of music (Yalch and Spangenberg 2000; Mattila and Wirtz 2001; Areni 2003), scent (Mattila and Wirtz 2001; Michon et al. 2005), layout (Smith and Burns 1996), lighting (Summers and Hebert 2001) and color (e.g., Babin et al. 2003). It is also becoming more common that retailers incorporate information and communication technology into creating a retail atmosphere that enhances the in-store experience, referred to as the "digital atmosphere."

For instance, Neiman Marcus introduced a new technology called "Memory Mirror," which allows customers to see outfits from various angles and remembers what customers have already tried on. Adidas is offering an "Adidas Wall," a three-dimensional interactive screen that shows a whole range of products and enables customers to quickly search for shoes and make purchases. More fashion retailer digital atmosphere innovations include "Window Shopping" for Tommy Hilfiger, "Interactive Fitting Room" for Rebecca Minkoff, and "Magic Mirror" for Top Shop to make the shopping experience more convenient for consumer. Burberry was praised for its success by creating a technological digital atmosphere with large digital displays and touchscreens at its flagship store in London. Retailers have also found that adding digital devices to the environment stimulates and amplifies the senses and feelings together with color, sound, and scent. These cases of digital displays using magic mirrors and touch screens are all types of digital signage that are used as an influential tool to determines the digital atmosphere in the store. However, there is a lack of research on the effect of a digital atmosphere in fashion retail stores on consumers' purchasing decision-making process.

Extended model of AIDSAS

To systematically investigate consumer behavior in a digital atmosphere, we use the attention-interest-desire-search-action-share (AIDSAS) model as our conceptual framework modified from the AIDA model proposed by Hall ( 1924). The AIDA, a classic promotional theory in marketing, posits that the consumers make behavioral decisions after they go through the attention-interest-desire process. The AIDA model has mainly been used to identify the effectiveness of promotion and advertising. It has recently become well-known in academia and practice and has been widely applied in the marketing field (Strong 1925; Wiyaya 2012; Hassan et al. 2015). When consumers pay attention to a product or brand, they perceive the product with interest. In this process, they evaluate the product based on their desire and then take action.

The AIDA model has been modified and applied in research with changes in consumer purchasing behavior resulting from ICT development (e.g., Wiyaya 2012; Wei and Lu 2013). Current consumers tend to be much more information savvy than before. They search and collect information from multiple channels, particularly from the Internet, to compare prices and search for alternative products from other brands before making a purchase (Kotler and Armstrong 2010; Sugiyama and Andree 2010). The critical facet of the Internet and social media is sharing of opinions. Consumers are also more willing and even eager to share their experiences about products on social networking sites (SNS) (Solomon 2018). Millennials prefer to record their everyday experiences on SNS, and are not offended to communicate with other users by clicking the Like button and/or commenting on certain newsfeeds (Solomon 2018). Thus, retailers must pay attention to consumers' behavior of sharing their experiences about brands and/or products on SNS. Hence, the original AIDA model was modified to the attention, interest, search, action, and share (AISAS) model by adding search and share (Sugiyama and Andree 2010). Because "desire" in Hall's ( 1924) model is considered a precedent that makes the intention of the action stronger, this study adopted a modified model by adding "desire" to the AISAS model, to create AIDSAS.

Large-scale use of digital signage in fashion retail stores evokes a digital atmosphere within the store to improve the in-store experience by providing information about products that will help consumers search and make decisions (Burke 2009; Dennis et al. 2010). This leads consumers to think about how to use digital signage, which will impact on consumers' cognition processes. The AIDA model has helped identify the effect of a digital atmosphere on consumer behavior in stores with digital signage.

Hypotheses development

Studies have indicated that the store atmosphere affects the mental and emotional state of consumers while shopping and influences momentary and immediate behaviors in the store (Donovan Rossiter 1982). Recently, it is important to note that among the various forms of ICT technologies incorporated into the retail atmosphere, digital signage, such as LED billboards, and digital or touch screens dispensing product information, has been the most prevalent adoption strategy in fashion retail stores (Kim and Sung 2016; Kent et al. 2018), and its application in stores is growing fast (Roggeveen et al. 2016).

Utilizing digital technology in retail stores could also help enhance consumer satisfaction, brand trust, and brand value, and give consumers a positive perception of the products and retail stores (Inman and Nikolova 2017). Past studies have indicated that the store atmosphere is a particularly important factor for retailers to consider because consumers are more likely to purchase products when they are satisfied with the store atmosphere (Berry et al. 2002). This study identifies how the digital atmosphere affects consumers' purchasing process based on the AIDSAS model.

Consumers become aware of the digital atmosphere when they see the large size of digital signage installed in the store; thus, they pay more attention to the store. Attention is the first step, a cognitive step, in the AIDSAS model (Ashcroft and Hoey 2001). This attention then attracts consumers' interest, which is the affective step (Ashcroft and Hoey 2001; Wiyaya 2012; Hassan et al. 2015). Once the atmosphere draws consumers' attention, they become interested in what products are being sold and what services are being offered in the store (Wiyaya 2012; Hassan et al. 2015). Thus, the following hypothesis was developed.

H1: The greater the attention to the digital atmosphere of a retail store, the greater the interest in products in the retail store.

H2: The greater the interest in the products in the retail store, the greater the desire to obtain the products in the retailer store.

Search and sharing intention are important because they have a direct and indirect effect on purchasing decisions as part of the consumption behavior before and after the purchase. Consumers, especially millennials, usually search for information about the products they want to buy from online reviews and SNS postings before they make a purchase (McGee 2017). After the purchase, they are also more willing to share their opinions and experiences about the product and/or service on SNS (McGee 2017; Solomon 2018). The content shared by consumers (e.g., reviews regarding products and/or brand) will then be searched by other consumers before they purchase. Sharing experiences on SNS is an ICT-facilitated word-of-mouth behavior. Word-of-mouth sharing has been a significant research topic for a decade as consumers tend to trust information more from other consumers than any other type of commercial advertisement (Richins 1983; Schiffman and Kanuk 1997). Information-savvy consumers also have more trust in online word-of-mouth information that they can easily search on the Internet including social media (Mangold and Faulds 2009; Kotler and Armstrong 2010). Consumers' online reviews of products and/or brands are shared on social media for other consumers, and it can be influential as more consumers share with others (Vollmer and Precourt 2008). When the shared word-of-mouth information contains rather positive content, companies may be able to reduce their marketing costs (Mangold and Faulds 2009). However, although few studies have shown that desire has a significant effect on sharing and search intention, it can be predicted that consumers with a purchasing motivation for product incentives (i.e., desire) will search and share product information.

Sugiyama and Andree ( 2010) also argued that the AISAS model is less likely to be a linear step-by-step process; rather, consumers may show behavioral responses (search, share, action) simultaneously after they pay attention, are interested, and have desire for a product.

Therefore, we expect that in-store experiences enhanced by the digital atmosphere would draw consumers' attention to the retail store and increase their interest in the products in the store. In addition, the interest would generate the desire to obtain the products, and end with a behavioral response, such as search, action (purchase), and share. Thus, the following hypotheses were developed.

H3: The greater the desire to obtain the products in the retail store, the greater the endorsement intention to (a) search for, (b) take action - purchase, and (c) share about the product.

Differences between luxury and sports items

This study also examined whether the effect of digital atmospherics on consumers' perceptions and behaviors is different among stores carrying different types of products: luxury versus products. For instance, a luxury retail store sells high quality products using images that convey sophistication, affluence, and high class (Bourdieu 1984; Holt 1995; Kapferer and Bastien 2009; Chadha and Husband 2010; Kapferer and Bastien 2012; Okonkwo 2016) as well as being creative and unique (Kapferer and Bastien 2009, 2012). In contrast, for sports products and their retail stores, consumers focus on functionality and convenience (Choi and Lee 2011). This means that consumers expect and want different parts of luxury brands and sports brands respectively.

Despite these differences, both many retailers including luxury and sports retailers need to utilize information and communication technology by incorporating digital signage in a store (Grewal et al. 2017). From a consumer's perspective, they would like to use digital devices such as their mobile devices and/or in-store interactive digital screens to search for information to make a purchasing decision. It is also is advantageous for luxury retailers to apply ICT in a store to collect elaborate personal information from consumers to provide advanced personalization services to consumers (Jain et al. 2017). Acquiring high-quality personal information is more feasible due to the compatibility between in-store digital devices and consumers' mobile devices. Sports retailers also attempt to showcase advanced technology material and smart clothing every season. For example, they launch smart products in collaboration with a mobile company that are designed to help consumers' exercise using a mobile application so they can easily check their athletic performance (Draper 2018).

Although digital atmospherics can benefit both luxury and sports stores and brands, how consumers evaluate digital atmospherics and the extent to which digital atmospherics affect consumer behavior can differ given the unique characteristics of products and consumer expectations. For example, consumer expectations for luxury and sports stores are different. In addition, the merchandise consumers want to purchase, the consumption value, and the purpose of the purchases are different in these two types of stores. For instance, when consumers want to buy sneakers, a luxury brand will be meaningful in term of the social or emotional value compared to the functional value. In contrast, utilitarian and functional value will be more important when buying sneakers from sports brands. Therefore, it is expected that there will be differences in the processes of consumers' purchasing decisions in luxury stores versus sports stores with large-sized digital signage to deliver information. Our study explores this aspect. Given the lack of research on these differences, however, we formulate a hypothesis predicting differences without specifying particular functionalities to allow them to be empirically identified.

H4: Luxury retail stores and sports retail stores with a digital atmosphere will have differences in the average value in each process of the consumer behavior model.

Method

Stimuli development

The stimuli for our study included the typical digital signage used in many retail stores. Digital signage attracts consumers' attention since it is active media (Bauer et al. 2012), and creates a user experience at a touch point for purchasing by adding interactive functions. It is also the most widely used medium in actual fashion retail stores.

Thus, we focus on stores' digital signage to examine the effect of the digital atmosphere on consumers' internal evaluations in fashion retail stores and to measure how this atmosphere affects online behavior and purchase behavior. The photos are of two existing luxury and sports stores that were used as stimuli. The three photos of the luxury store included (1) a photo with a large digital screen on one wall of the store, (2) a photo with digital devices to enable consumers to search products, and (3) a photo of consumers searching for information in front of a large touch screen. The other three photos were used as stimuli for the sports store including (1) a photo with a large digital screen in the center of the store, (2) a photo of a treadmill connected to digital signage, and (3) a photo of consumers searching for information in front of a large touch screen (the same people as in the luxury store). The descriptions of the technology devices used in each picture were also presented along with the pictures of actual stores where consumers could find such devices.

Survey procedure

At the beginning of the questionnaire, three photos of actual digital signage from luxury stores (or sports stores) were presented as stimuli. The photos showed a brand advertisement on an oversized digital display that was installed in the most prominent place in the store, such as an entire wall or the center of the store. Other photos showed consumers directly managing the touch screens in front of the displayed products to get information on colors and sizes. Additional descriptions were under the photos (e.g., "You can search for in-store inventory, colors, and sizes, and can purchase directly through the touch screen without standing in line"). After reviewing the stimuli, participants were asked to fill out the questionnaire to measure the variables included in our study.

Measures/data collection

The data were collected in Korea via an online survey administered by a market research agency. Data were collected from 212 responses. Among these, 103 responses were gathered on luxury stores and 109 were on sports stores. Frequency analysis and crossover analysis were conducted to identify the characteristics and differences between the luxury retail store respondents and the sports store respondents. Demographic information on the 212 participants' age, gender, and marital status was gathered, and no differences were found in the groups in terms of gender, educational background, and monthly household income of the respondents (shown in Table 1).

All items (except for demographic characteristics) were measured on a 5-point Likert scale (1 = strongly disagree; to 5 = strongly agree). Specific items used to measure our variables are presented in Table 2. The data were statistically analyzed using SPSS 21.0 and AMOS 18.0.

Results

Preliminary analysis

Reliability and validity

To test the reliability and validity of the scales, we conducted exploratory and confirmatory factory analyses. With the data ( n = 103 for luxury, n = 109 for sports), we first confirmed that the Cronbach's α coefficients for the variables ranged from 0.781 to 0.911, as shown in Table 2. Cronbach's α coefficients above 0.7 represent the measurements of reliability (Henseler et al. 2009; Hair et al. 2013). Validity of the constructs of the seven latent variables was also examined to check whether the measurements of this study were appropriate. First, the results of the confirmatory factor analysis indicated that our measurement model was a good fit (χ ²(d.f) = 295.922(155), GFI = .878, CFI = .960, IFI = 0.961, RMSEA = 0.066). Convergent validity, which examines the degree to which two or more measurement tools have a correlation with a single factor, can be measured as average variance extracted (AVE) and construct reliability (CR). The factor loadings of all indicators were greater than 0.60, which indicates that the measures all had acceptable convergent validity for each construct (Henseler et al. 2009; Hair et al. 2013). The CR ranged from 0.978 to 0.990, and the AVE ranged from 0.701 to 0.849, as shown in Table 2. Thus, we confirmed that the data met the required levels of the constructs as suggested by Fornell and Larcker ( 1981): .7 for the CR and .5 for the AVE.

We also checked the discriminant validity (i.e., one factor differs from another) by calculating the square of the correlation coefficients between the AVE of each latent variable and each of the two variables (Fornell and Larcker 1981). Discriminant validity is demonstrated when the AVE is larger than its squared correlation coefficients in the rows and columns. The square of the correlation coefficients between all the latent variables in our model ranged from 0.370 to 0.637 and were smaller than the AVE index for each variable with a range of 0.735 to 0.849 (Table 3). Thus, we concluded that our measures satisfied discriminant validity.

Hypothesis testing

To test the hypotheses depicted in our model, we conducted structural equation analysis using AMOS. The model's goodness of fit was within the standard range (χ ² (df) = 366.290 (165), normed χ ² = 2.220; p = 0.000; CFI = 0.943; GFI: 0.85; IFI = 0.944; TLI = 0.935; RMSEA = 0.076). Specifically, in the retail store with installed digital devices, consumers tended to pay attention to the digital atmosphere, which focused consumers' interest on the displayed products in the retail store ( β = .813, p < 0.0001). The results also show that consumers were interested in the products displayed in the digital atmosphere retail store and they wanted to own the products ( β = .913, p < 0.0001). Thus, H1 and H2 are supported.

In addition, the results show that the desire to obtain products in the digital atmosphere retail store had a significant effect on consumers' behavioral responses. First, there was a positive effect of the desire to obtain products in the digital atmosphere retail store on online search intention ( β = .869, p < 0.0001). Thus, H3a is supported. Moreover, the desire to obtain products in the digital atmosphere retail store had a positive effect on intention to share ( β = .843, p < 0.0001). Thus, H3b is supported. H3c was to identify the effect of the desire to obtain products in the digital atmosphere retail store on purchase intention ( β = .913, p < 0.0001). The result shows that the positive evaluation of the products on the environment of the technology-equipped retail store led to purchase intention. Thus, H3c is supported (Fig. 1).

Summary of the SEM analysis

Difference in behavioral intention by store type: luxury vs. sports

As seen in Table 4, the results support H4. Specifically, we found that the respondents in the sports stores that displayed technological instruments paid more attention to the store itself than the respondents in the luxury stores with a digital atmosphere (M luxury = 3.052 < M sports = 3.844; F = 54.128, p < 0.001). Respondents showed more interest in the products in the sports retail store even though both the sports and luxury retail stores had installed digital technologies in the stores (M luxury = 3.003 < M sports = 3.584; F = 26.988, p < 0.001). The desire to obtain products in the digital atmosphere sports retail store was higher than the luxury retail store (M luxury = 2.877 < M sports = 3.517; F = 30.238, p < 0.001). Furthermore, consumers' intention to search for products (M luxury = 2.959 < M sports = 3.534; F = 24.578, p < 0.001), to share information about the products in the store with peers, friends, and other consumers (M luxury = 3.016 < M sports = 3.526; F = 19.778, p < 0.001), and to purchase products (M luxury = 3.080 < M sports = 3.500; F = 18.728, p < 0.001) in the retail store were all higher in the sports retail store than the luxury retail store.

By installing technological devices, consumers experience digital atmosphere in both sports and luxury retail stores, but they show different processes of consumer purchasing patterns, AIDSAS, and different behavioral intention. The average value of each process of consumer purchasing pattern was statistically significant and higher in the sports retail store than the luxury retail store. This result confirms that the digital atmosphere is more effective with consumers in the sports retail store than the luxury retail store.

Discussion

Influence of digital technology

Fashion retailers have strategically adopted digital devices in their stores to offer consumers immersive in-store experiences. Digital devices installed in retail stores have been found to shape customers' experiences and decision-making by improving the quality and delivery of information (Dennis et al. 2012). This trend has grown significantly through the development of ICT and the consumer trend of demanding greater convenience and instant services. This study demonstrates the pivotal role of an in-store digital atmosphere in enhancing product purchases as well as encouraging e-word-of-mouth sharing of one's experience. Moreover, a technological atmosphere with large-sized digital displays promotes interest in the products, and intensifies the desire to own the products displayed in the fashion retail store.

The results of this research can be summarized as follows. First, the results confirm that the digital atmosphere in retail stores can be a significant tool to attract consumers' attention to the store. We find that attention is a key antecedent to interest, desire, and behavioral responses (search, action, and share) in consumers' purchasing patterns triggered by digital atmosphere. This could mean that if the digital atmosphere fails to attract enough attention from the consumers, the store will not be able to induce desirable and necessary subsequent reactions. Particularly when retailers work with small devices and kiosks to promote digital atmosphere, it is important to place them in a strategic location that can attract the maximum level of attention to the devices.

The results also emphasize that oversized digital displays and touch screens installed in stores are worth using to offer product information and help consumers positively perceive the products. This positive evaluation of the products also enhances consumers' intention to share the product information acquired directly from their experience in the store on social media, leading to successful word-of-mouth advertisement. In general, when consumers visit a fashion retail store and have a new and unique experience, electronic word-of-mouth (eWOM) advertising is expected. When consumers voluntarily share user-generated content with the majority of other consumers, it can be very effective (Vollmer and Precourt 2008); hence, companies should take the opportunity to promote brands and products through oversized digital displays and touch screens (Mangold and Faulds 2009). Our study indicates that digitally enhanced retail stores can significantly increase consumers' willingness to share their experiences online.

Consumers are also more likely to search for products that are displayed in a digital-atmosphere store before purchasing using other channels. The adoption of digital installations in the store and consumers' own digital devices including cellphones and wearable devices will continue to increase. Consumers will quickly become accustomed to searching and purchasing products using in-store digital devices, sharing their experiences via their mobile phones, and searching for other brands of products. These processes are expected to become more common in the near future. This suggests that in the omni-channel era, companies should disclose transparent and consistent policies related to prices and product information because consumers can quickly search for this information using mobile or/and digital devices in a purchasing context.

Finally, the results of this study show significantly positive effects of a digital atmosphere in both sports and luxury retail stores on consumer's purchasing patterns. However, we find these positive effects are more pronounced for sports retail stores than luxury retail stores. This may be due to the stronger desires for consumers to receive personal touches in luxury stores than they might expect in stores selling sports equipment (Cillo et al. 2016). This could mean that utilizing digital devices in luxury retail stores may not be as effective as in sports retail stores. This may further suggest that luxury retail stores may utilize digital devices for inventory management, and to provide product information, while still maintaining a high level of in-store personal services.

Implications, limitations, and future research

The development of digital technology and ICT has brought about a significant transformation in the VMD of fashion stores. This study is meaningful in both academic and business fields. The current study contributes to the academic literature in several ways. First, the study contributes to understanding consumers' behavior and decision-making processes related to the digital atmosphere of fashion retail stores based on the AIDSAS model. This empirical study using the AIDSAS model reveals the concrete mechanism of the effect of the perceived store atmosphere on consumer behavior because the AIDSAS model makes it possible to uncover the stepwise relationships between attention to the store atmosphere-interest/desire and to the products-behavior response.

Although numerous previous studies have demonstrated the pivotal role of the atmosphere in fashion retail stores, this model makes the study results more robust, and is expected to be applied in future retail atmospheric studies. In addition, this can fill the gap in the literature in the context of the significant transformation of the retail environment using in-store digital devices by systematically identifying the effects of the digital atmosphere on consumer behavior.

This study also contributes to the digital technology application literature by investigating the effect of the retail store's digital atmosphere on consumers' decision-making process. Through AIDSAS, the underlying model of this study, it was revealed that the digital atmosphere in fashion retail stores affects consumers' cognition of a retail store and products displayed in the store and induces positive emotion and buying motive to encourage them to buy. Therefore, it is necessary to actively utilize digital devices in the store. In particular, fashion retailers can employ digital devices in their retail stores as marketing tools by promoting interaction between consumers and digital devices, which can be used in conjunction with the consumer's own mobile devices using technologies such as Bluetooth or Beacon.

Identifying the differences between technology used in the sports and luxury industries will provide practical implications that can be applied in the fashion industry. The results of this study indicated that the digital atmosphere has a higher effect on consumers' cognition (attention), affect (interest), buying motive (desire), and behavior intention (search, purchasing, sharing) in sports stores than in luxury stores. Sports brands including outdoor brands need to install digital devices in their stores to create a digital atmosphere to speed up consumers' decision making process. The results of this study suggest that fashion retailers, especially sports brand retailers, could employ large digital devices such as digital signage, treadmills that can measure heart rate and gait, and touch screens that allow customers to search for information such as size, color, inventory and product features. The use of such technology is expected to be effective in creating a digital atmosphere in fashion retail stores, especially sports stores.

We note, however, that the study was conducted in South Korea where the average population is highly receptive to technological advancement. An interesting future study may examine whether the relationships depicted in our model is consistent in other nationality or cultural contexts. Another limitation of this study is that consumers' perceptions toward different brands (i.e., Burberry vs. Adidas, Nike) were not considered as covariates. Future studies should include brand familiarity as a covariate or stimuli that need to be incorporated into fashion retail stores that are not branded but identified by the brand category (e.g., luxury vs. sports). In addition, more case analysis is needed in future research to determine whether the results of this study are generalized and applicable to the sports and luxury industries.

Another limitation of this study is that it did not compare consumer behavior in retail stores with a digital atmosphere and those without digital technology. This is an opportunity for future study.

Availability of data and materials

The datasets used and analyzed during the current study are available from the first author on reasonable request.

References

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Acknowledgements

Not applicable. This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2016S1A2A2912526).

Funding

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2016S1A2A2912526).

Author information

Authors and Affiliations

1. Professor, Department of Textiles, Merchandising and Fashion Design, Seoul National University, 222Dong 305Ho, 1, Gwanak-ro, Gwanak-gu, Seoul, South Korea

Ha Youn Kim, Yuri Lee & Yeo Jin Jung

2. Strategic Design Management, School of Design Strategies, Parsons, New York, NY, 10011, USA

Erin Cho

Contributions

HYK analyzed and discussed the result with YL, and EC. YL developed research background. EC discussed the result with HK. YJJ collected literatures and data. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yuri Lee.

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Competing interests

The authors declare that they have no competing interests.

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Kim, H.Y., Lee, Y., Cho, E. et al. Digital atmosphere of fashion retail stores. Fash Text 7, 30 (2020). https://doi.org/10.1186/s40691-020-00217-6
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Digital atmosphere of fashion retail stores - Fashion and Textiles

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This study sheds light on a prominent issue in retailing: how the digital atmosphere can affect the consumer decision-making process in a fashion retail store. Digital devices and services such as digital screens and digital signage are widely employed in fashion retail stores, transforming the way consumers make decisions about purchasing fashion products.

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Revolutionary Smart Fabrics: 5 Key Innovations Transforming Textiles

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Revolutionary Smart Fabrics: 5 Key Innovations Transforming Textiles

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Smart fabrics. The very term conjures images of futuristic clothing with built-in sensors, self-cleaning capabilities, and perhaps even the power to generate electricity. While this vision might seem like science fiction, the reality is far closer than you might think. The rapid advancements in materials science, nanotechnology, and electronics are fueling an unprecedented surge in the development and application of smart fabrics, poised to revolutionize numerous industries, from healthcare and athletics to fashion and defense. This article will explore five key innovations driving this exciting revolution and delve into the potential implications for our lives.

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Revolutionary Smart Fabrics: 5 Key Innovations Transforming Textiles

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Revolutionary Smart Fabrics: 5 Key Innovations Transforming Textiles

Smart fabrics. The very term conjures images of futuristic clothing with built-in sensors, self-cleaning capabilities, and perhaps even the power to generate electricity. While this vision might seem like science fiction, the reality is far closer than you might think. The rapid advancements in materials science, nanotechnology, and electronics are fueling an unprecedented surge in the development and application of smart fabrics, poised to revolutionize numerous industries, from healthcare and athletics to fashion and defense. This article will explore five key innovations driving this exciting revolution and delve into the potential implications for our lives.

1. Wearable Sensors and Health Monitoring: One of the most impactful applications of smart fabrics lies in the realm of health monitoring. Integrating miniature sensors directly into clothing allows for continuous and non-invasive tracking of vital signs such as heart rate, body temperature, respiration rate, and even blood pressure and ECG data. These sensors, often based on conductive yarns or printed electronics, can be seamlessly woven into garments, making them comfortable and unobtrusive for the wearer.

The implications for healthcare are profound. For patients with chronic conditions, continuous monitoring can provide crucial data to physicians, enabling early detection of potential problems and facilitating timely interventions. This can be particularly beneficial for individuals with heart conditions, diabetes, or respiratory illnesses. For athletes, smart fabrics can offer valuable insights into training performance, allowing for personalized training regimens and injury prevention. Beyond clinical applications, wearable sensors integrated into smart fabrics are also finding their way into consumer fitness trackers and smartwatches, providing convenient and accessible health monitoring for the general population.

The development of flexible and biocompatible sensors is crucial for the success of this technology. Researchers are exploring various materials, including conductive polymers, carbon nanotubes, and graphene, to create sensors that are both sensitive and comfortable to wear for extended periods. Furthermore, advancements in data processing and wireless communication technologies are essential for effectively transmitting and analyzing the data collected by these sensors. The challenge lies in miniaturizing the sensors further while maintaining accuracy and reliability, and in developing power-efficient systems to extend the operational lifespan of wearable devices.

2. Energy Harvesting and Power Generation: Imagine clothing that can power itself, eliminating the need for frequent battery replacements. This seemingly futuristic concept is becoming increasingly feasible thanks to the integration of energy harvesting technologies into smart fabrics. These technologies leverage various energy sources, including solar energy, body heat, and even mechanical energy from movement.

Solar cells woven into fabrics can convert sunlight into electricity, providing a sustainable power source for wearable electronics. Thermoelectric generators, which convert heat energy into electricity, can harness the body's heat to power sensors and other devices. Piezoelectric materials, which generate electricity in response to mechanical stress, can harvest energy from movement, potentially powering devices simply through the wearer's activity.

The efficiency of these energy harvesting technologies is a critical factor in their widespread adoption. Research is focused on improving the conversion efficiency of solar cells and thermoelectric generators, while also exploring new materials and designs to maximize energy harvesting from movement. The challenge lies in balancing energy generation capacity with the comfort and flexibility of the fabric. Successfully integrating these technologies into clothing without compromising aesthetics or wearability will be key to their market success.

3. Self-Cleaning and Antimicrobial Fabrics: Maintaining hygiene is paramount, especially in healthcare and athletic settings. Smart fabrics are addressing this need through the incorporation of self-cleaning and antimicrobial properties. These fabrics can be treated with nanomaterials that possess antimicrobial properties, preventing the growth of bacteria and other microorganisms. Some fabrics are even designed to self-clean, using photocatalysis or other mechanisms to break down dirt and stains.

Nanomaterials such as silver nanoparticles, titanium dioxide nanoparticles, and zinc oxide nanoparticles have shown promise in imparting antimicrobial properties to fabrics. These nanoparticles disrupt the cell walls of bacteria, effectively inhibiting their growth. Photocatalytic materials, such as titanium dioxide, can be activated by sunlight to break down organic pollutants and stains, providing a self-cleaning effect. The challenge lies in ensuring the safety and long-term stability of these nanomaterials, as well as preventing potential environmental impacts from their use.

Self-cleaning fabrics offer numerous advantages, reducing the need for frequent washing and potentially extending the lifespan of garments. This is particularly beneficial for athletic wear, where sweat and bacteria accumulation can lead to odor and hygiene issues. In healthcare settings, self-cleaning fabrics can help prevent the spread of infections, improving patient safety and reducing the burden on healthcare workers. The development of environmentally friendly and biocompatible self-cleaning technologies is crucial for the sustainable and responsible adoption of these fabrics.

4. Shape-Memory and Adaptive Fabrics: Smart fabrics are also exhibiting the ability to change shape and adapt to their environment. Shape-memory alloys and polymers can be integrated into fabrics to create garments that can adjust their fit or even their functionality based on external stimuli such as temperature or pressure. These fabrics can be used to create adaptive clothing that responds to changes in weather conditions, providing optimal comfort and protection.

Shape-memory alloys (SMAs) are metals that can "remember" their original shape and return to it after being deformed. These materials can be woven into fabrics to create garments that can adjust their fit based on temperature changes. Shape-memory polymers (SMPs) exhibit similar properties but offer greater flexibility and design possibilities. These materials can be programmed to respond to specific stimuli, allowing for the creation of garments that can adapt to different situations.

The applications of shape-memory fabrics are diverse. They can be used to create clothing that automatically adjusts its fit based on the wearer's body temperature, providing optimal comfort in varying weather conditions. They can also be used to create protective clothing that adapts to changes in environmental conditions, providing enhanced safety and protection. The challenge lies in developing shape-memory materials that are durable, washable, and comfortable to wear. Further research is needed to optimize the responsiveness and reliability of these materials.

5. Conductive Fabrics and Electronic Integration: The integration of conductive fabrics into clothing is enabling the development of wearable electronics and interactive garments. Conductive yarns and fabrics can be used to create circuits, sensors, and actuators, allowing for the creation of garments with a range of interactive features. These fabrics can be used to create clothing that can monitor vital signs, communicate wirelessly, or even respond to touch input.

Conductive yarns are made from materials such as silver-coated fibers, carbon nanotubes, or conductive polymers. These yarns can be woven into fabrics to create circuits and sensors that can be integrated into clothing. The integration of conductive fabrics with flexible electronics is enabling the development of wearable devices that are comfortable and unobtrusive. These devices can be used for a range of applications, including health monitoring, fitness tracking, and communication.

The challenge lies in developing conductive fabrics that are durable, washable, and aesthetically pleasing. Research is focused on developing new materials and manufacturing techniques to improve the performance and reliability of conductive fabrics. The integration of conductive fabrics with flexible electronics is opening up new possibilities for wearable technology, enabling the creation of more sophisticated and user-friendly devices.

The rise of smart fabrics is transforming the textile industry and impacting numerous other sectors. While challenges remain in areas such as cost, scalability, and long-term durability, the potential benefits are immense. As research and development continue, we can expect to see even more innovative applications of smart fabrics emerge, further blurring the lines between technology and clothing, and ultimately enriching our lives in countless ways. The future of textiles is undeniably smart, and its impact is only beginning to be felt.

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ByBernard Marr, Contributor.

British fashion brand Burberry is one of the most recognized luxury clothes labels in the world. Starting in 2006, the company aimed to reinvent itself as an “end to end” digital enterprise. Its strategy was to use Big Data and Artificial Intelligence (AI) to boost sales and customer satisfaction.

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British fashion brand Burberry is one of the most recognized luxury clothes labels in the world. Starting in 2006, the company aimed to reinvent itself as an "end to end" digital enterprise. Its strategy was to use Big Data and Artificial Intelligence (AI) to boost sales and customer satisfaction.

It does this by asking customers to voluntarily share data through a number of loyalty and reward programs. This information is used to offer personalized recommendations, online and in store. When an identified customer enters a store, sales assistants use tablets to offer buying suggestions based on their customers' purchase history as well as their social media activity.If Burberry knows that a customer has recently bought a particular coat, for example, then assistants may be encouraged by the app to show them a handbag which is popular with other buyers of the coat.

Products in their 500 stores spread across 50 countries are also fitted with RFID tags which can communicate with shoppers' mobiles, giving information about how items were produced or recommendations on how they can be worn or used.

This usage of technology and tactics usually confined to online retail in a "bricks and mortar" setting prompted then CEO Angela Ahrendts (now SVP of retail at Apple) to state that "walking through our doors is just like walking into our website", in 2014.

In 2015, the company announced that their investment in personalized customer management programs had resulted in a 50% increase in repeat custom.

One specific insight was the impact that product images had on sales of items that performed well in-store but not so well online. By creating new images for products where the data showed this was occurring, the company saw a 100% increase in sales for one particular bag.
Cutting edge
Always keen to lead the pack rather than follow, Burberry is an earlier adopter of new technology and channels - as well as a vibrant following on social media, the brand was the first in the world to make use of Snapchat's Snapcode feature. This allows customers to unlock information by scanning barcodes attached to their products.

It was also the first brand to launch its own dedicated channel on Apple Music, with the aim of connecting with customers by promoting British musical talent.

Another innovative engagement initiative allowed customers to appear alongside celebrities in their own personalized version of one of their TV ads, by filming themselves inside in-store booths.

Facebook "chatbots" were used for the first time last year, during London Fashion Week, to share information and updates on new products with customers through the social media site's chat functions.

Since then the offering has been expanded to provide customer services, options for browsing and shopping new collections - and even the possibility to book an Uber ride directly to their store, simply by "chatting".

All these initiatives show that the focus of Burberry's tech transformation is clearly put on building personalized relationships with individual customers - taking techniques pioneered by online retail giants and applying them to the more intimate world of luxury direct marketing.
Cracking down on counterfeits
Burberry is one of the most counterfeited brands in the world, so it makes perfect sense that this is an area where it has already put AI and machine learning technology to work.

The brand uses technology provided by Entrupy which is based around image recognition, and capable of determining from one photograph of a tiny section whether or not a product is genuine. It does this through examination of minute details in the texture and weaving, and can reportedly spot a counterfeit with 98% accuracy. This means retailers offering bootleg products can quickly be shut down and brought to justice.
Looking forward
After proving the concept of a tech-led, luxury fashion and retail enterprise, with personalization and direct marketing initiatives, Burberry has spoken about its plans to roll out AI tech into other areas of its operations, including production and product development, although here it appears to be taking a more cautious approach.

Their senior VP of IT, David Harris, has said "We are formulating our AI strategy now ... we believe that AI can deliver business value through making better products, faster, cheaper processes and more insightful analysis.

"For instance, we certainly see the potential for machine learning to improve and automate a number of our support processes - dev ops, testing, etc."

Harris went on to say that possible uses include insights from pattern recognition, scenario modelling for logistics purposes, as well as increasing security and preventing fraud.

Burberry was built on innovation - its earliest products were made from durable new fabrics such as Gabardine developed by founder and inventor Thomas Burberry in the 19 th century. It makes complete sense that today the brand still looks to leverage new developments to maintain its competitive edge.

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How Generative AI Is Revolutionizing Customer Service

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How Generative AI Is Revolutionizing Customer Service

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Customer service is proving to be one of the most popular applications of generative AI. But how exactly can generative AI aid customer service teams (without alienating customers)? And which companies are already making great use of generative AI? Read on to find out.

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How Generative AI Is Revolutionizing Customer Service
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Customer service is proving to be one of the most popular applications of generative AI. But how exactly can generative AI aid customer service teams (without alienating customers)? And which companies are already making great use of generative AI? Read on to find out.

The Capabilities Of Generative AI

One of the obvious uses of generative AI is customer-facing chatbots. If you've ever had a frustrating interaction with a chatbot that is not particularly helpful, take heart because, with tools like ChatGPT, organizations can create chatbots that better understand customer queries and respond with much greater accuracy and nuance. They can also handle a large volume of queries efficiently and provide more personalized responses over time.

Traditional AI offerings (like some of the not-very-intelligent chatbots you might have interacted with) rely on rules-based systems to provide predetermined responses to questions. And when they come up against a query that they don't recognize or don't follow defined rules, they're stuck. And even when they do give a helpful answer, the language is typically pretty stiff. But a tool like ChatGPT, on the other hand, can understand even complex questions and answer in a more natural, conversational way.

In fact, ChatGPT is so good that UK energy supplier Octopus Energy has built conversational AI into its customer service channels and says that it is now responsible for handling inquiries. The bot reportedly does the work of 250 people and receives higher customer satisfaction ratings than human customer service agents. This is a prime example of how contact centers will increasingly incorporate generative AI chat and voice tools to deal with straightforward, easily repeatable tasks. And, of course, these tools give customers 24/7 access to support, 365 days a year, via multiple channels (such as phone, online chat, and social media messaging).

But answering customer questions isn't the only way generative AI can add value in customer service. Some of the other tasks that generative AI can do or assist with include:

· Giving customers personalized recommendations based on the customer's data and previous interactions further helps to enhance the customer experience.

· Providing conversational search functions for, say, FAQs online. Generative AI can take natural language prompts like "Where's my package?" and either direct the customer to the correct FAQ response or deliver a tailored response. Plus, this can be done in multiple languages.

· Optimizing data to support customer service operations. Generative AI can handle vast amounts of data and turn that information into actionable insights - insights such as "Which are our most common complaints?" It can also track and categorize customer trends.

· Supporting human customer service agents. Generative AI can help human agents be more productive. For example, it can automatically generate responses to common queries, provide summaries of previous complaints and resolutions that agents can use in conversations, and generate product recommendations.

In this way, generative AI can support the work that human agents do and free them up to focus on more complex customer interactions where they can add the most value.

How John Hancock Has Boosted Its Customer Service With Conversational AI Tools

We've already seen how one company has improved its customer service function with generative AI. Now, let's turn to another example. John Hancock, the US arm of global financial services provider Manulife, has been supporting customers for more than 160 years. But this doesn't stop the life insurance company from embracing the latest technology.

The company has partnered with Microsoft to implement conversational AI tools, including Azure Bot Service, to provide support for common customer queries and issues. Like many companies, at the start of the COVID-19 pandemic, John Hancock contact centers saw a spike in calls, meaning the company needed new ways to help customers access the answers they needed. So they turned to Microsoft to help set up chatbot assistants that could handle general inquiries - thus reducing the total number of message center and phone inquiries and freeing up contact center employees.

In other words, this allows human contact center workers to focus their efforts on more complex cases - those calls that really require their expertise, as opposed to generic queries like "How do I reset my password?" As a result, team members enjoy a better work experience and more manageable workloads - while customers enjoy reduced wait times and a better service experience. As Tracy Kelly, AVP of contact center and LTC operations, puts it, "The call reduction due to chatbot innovation equates to impressive cost savings we've been able to reinvest in our customer contact centers..."

Plus, as an added bonus, the customer service team is being upskilled in valuable AI skills, thereby helping to future-proof their jobs.

It's no wonder customer service has become CEOs' number one generative AI priority, according to the IBM Institute for Business Value, with 85 percent of execs saying generative AI will be interacting directly with their customers within the next two years. Those companies that ignore the generative AI trend clearly risk being left behind.

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Uncover the innovative ways AI is transforming creativity, product development, and logistical processes in the fashion business.

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Case Study: Zara’s Use of AI to Stay Competitive in Fast Fashion

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Case Study: Zara’s Use of AI to Stay Competitive in Fast Fashion

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Data-Driven Personalization in 2025: Unlocking the Future

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Data-Driven Personalization in 2025: Unlocking the Future

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Welcome to the world of data-driven personalization, where marketing transforms into an art powered by cutting-edge science! Imagine a future where every interaction with a brand feels uniquely tailored to your needs, your interests, and even your mood. That’s the promise of personalization, and 2025 is shaping up to be the year it truly delivers.

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Welcome to the world of data-driven personalization, where marketing transforms into an art powered by cutting-edge science! Imagine a future where every interaction with a brand feels uniquely tailored to your needs, your interests, and even your mood. That's the promise of personalization, and 2025 is shaping up to be the year it truly delivers.

What is Data-Driven Personalization?

At its core, data-driven personalization is the art of using customer data analysis to craft experiences that resonate deeply with individuals. It's about moving beyond generic campaigns to create meaningful connections. Whether you're shopping online, streaming your favorite shows, or even scrolling through emails, data-powered marketing ensures each interaction feels hyper-personalized and relevant.

A great example is Spotify's "Discover Weekly" playlist, which uses algorithms powered by advanced analytics to analyze your listening history, similar users' behaviors, and trending music. This results in a curated playlist that feels as if it was made just for you-a prime example of predictive personalization.

The Evolution of Personalization in Marketing

Personalization has transformed significantly over the last decade. Initially, it was limited to adding a client name to an email greeting. Today, the integration of tailored customer data and AI-driven insights has elevated it to predictive recommendations that seem almost psychic.

This shift was driven by buyer demand. According to a 2024 survey by Salesforce , 76% of consumers expect companies to understand their needs and expectations. Brands like Netflix and Amazon set the standard by leveraging data marketing to offer highly specific recommendations. Netflix's algorithms analyze billions of data points daily, including viewing history, preferences, and even the time of day you watch content, to suggest what you'll likely enjoy next.

For marketers, this evolution is not optional. As businesses across sectors adopt hyper-personalized strategies, the bar for customer experiences continues to rise.

Key Trends Shaping 2025

The personalization landscape is evolving rapidly. Here are four trends defining the future:

1. Hyper-Personalization at Scale

Businesses are no longer restricted to offering tailored experiences to a few high-value customers. With the help of advanced analytics and AI, companies can now deliver hyper-personalized interactions to millions simultaneously. For example, Sephora uses customer data analysis from its loyalty program to recommend products, services, and beauty routines tailored to individual preferences and purchase history.

2. Integration of Technographic Data

Beyond demographics, understanding the technology customers use provides deeper insights into their behavior. For instance, a B2B software company might tailor its marketing efforts based on whether prospects use competitors' platforms or specific operating systems. This type of tailored client data allows for highly relevant offers and messaging.

3. Behavioral Insights as Strategy Gold

Companies are delving into not just "what" customers buy, but "why" and "how." Behavioral data reveals patterns like shopping habits, time spent on pages, or response to promotions. For example, Walmart uses real-time purchase data and predictive personalization to adjust inventory and recommend products online that align with local buying trends.

4. Transparency and Trust

As more brands leverage customer data, privacy concerns have come to the forefront. Businesses that prioritize transparent data policies and give users control over their data are earning shopper loyalty. Apple's App Tracking Transparency (ATT) framework is a leading example, giving users clear control over how their data is used.

Benefits of Data-Driven Personalization

Investing in data marketing isn't just about driving sales-it's about fostering long-term relationships. Here's what businesses stand to gain:

Enhanced Customer Experiences Personalization makes every interaction seamless and enjoyable. A 2024 McKinsey report found that 78% of consumers are more likely to purchase from brands that offer personalized experiences.

Increased Customer Loyalty When brands "get it right," clients feel understood and valued. Starbucks' Rewards app exemplifies this by using customer data analysis to deliver personalized offers based on buying habits, location, and even time of day.

Higher Conversion Rates Personalization simplifies decisions by providing exactly what the buyer needs. Predictive personalization can increase click-through rates on recommendations by up to 20%, according to a data analysis.

More Efficient Marketing Spend With advanced analytics, marketers can identify the most effective strategies, reducing wasted effort and resources. Targeting high-intent audiences ensures campaigns yield maximum ROI.

Tools Driving Personalization in 2025

Here are the essential tools businesses are using to unlock the potential of hyper-personalized experiences:

Customer Data Platforms (CDPs)

CDPs consolidate tailored customer data from multiple channels-such as web analytics, sales, and client support-into a unified view. This comprehensive profile is the backbone of effective personalization strategies.

AI sifts through vast datasets to uncover patterns, predict trends, and offer actionable insights. For example, Unilever uses AI to analyze customer feedback in real-time, enabling the company to adjust marketing strategies instantly.

Interactive Content Platforms

Tools like Typeform and Outgrow empower users to engage with brands through personalized quizzes, product configurators, and surveys. This provides value to the user and enriches customer data analysis.

Marketing Automation Systems

Platforms like HubSpot and Marketo automate personalized email campaigns and retargeting ads. By using predictive personalization, these systems ensure content aligns with customer preferences and timing.

Bringing It All Together

The real challenge isn't gathering customer data - it's using it effectively. Successful brands integrate tools like CDPs, AI, and behavioral analytics into cohesive strategies. This holistic approach enables them to deliver hyper-personalized experiences that leave lasting impressions.

Picture this: You're browsing for a new winter coat online. Not only does the retailer suggest options in your preferred styles, but it also considers your local climate, upcoming travel plans, and budget. It even offers recommendations for matching boots and accessories.

This is the power of predictive personalization combined with data marketing. And it's not limited to retail. In healthcare, patient portals use customer data analysis to remind individuals of routine checkups, recommend wellness plans, and provide tailored advice.

As 2025 unfolds, the possibilities for hyper-personalized experiences are endless. Businesses that embrace this shift will not only meet customer expectations but redefine them, setting new benchmarks for what personalization can achieve.

The tools are here, the data is abundant, and the future of marketing is waiting. Are you ready to make 2025 the year of transformative, data-driven personalization?

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Data-Driven Personalization in 2025: Unlocking the Future

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Welcome to the world of data-driven personalization, where marketing transforms into an art powered by cutting-edge science! Imagine a future where every interaction with a brand feels uniquely tailored to your needs, your interests, and even your mood. That's the promise of personalization, and 202

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How Smart Wearables Are Shaping Our Future

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How Smart Wearables Are Shaping Our Future

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Serial Entrepreneur. Digital Award Winner, Mentor, Board Advisor, Founder and CEO of LookStyler, a global marketplace for fashion tourism.
Welcome to a new world where anything you wear can become a utility item. In this regard, we have seen some innovative products across the markets in areas like health, entertainment, gaming and fitness. Especially in the world of fashion, items like watches, bracelets and rings are now designed to track health as well as enable other benefits.
Wearable Technology Usage
For example, Ourarecently partnered with Gucciin order to connect fashion wearables to wellness and to track things like sleep and heart rate. Levi's and Jacquard by Google have created a jacket that has touch and gesture interactivity woven into the sleeve. Ray-Ban Stories is a collaboration project of Ray-Ban and Meta featuring smart glasses that allow you to capture everything around you by photo or video.

What we are seeing is the lines between sectors like fashion, retail, health, wellness and even fintech blurring. Smartwatches have been around for a while but can now also be used for payments. Particularly in the post-pandemic world, we have witnessed an accelerated adoption of health tech. Beauty, fashion, luxury and utility are now all becoming part of one blended universe.
History
Wearable technology encompasses any kind of electronic device that is designed to serve a purpose on a user's body. Such technology can be integrated into smart rings, glasses, clothing, earphones, medical wearables, smart helmets and biosensors.

Wearable technology functions by integrating microprocessors, batteries and internet connectivity to the product so the collected data can be synced to other electronics. While most wearables are worn on one's body, some can function remotely. The purpose is the same. These devices monitor data in real time. Some of the most sophisticated examples of wearable technology I have seen include AI hearing aids and smart glasses.
The Future
According to TechTarget, "The origins of wearable technology date back to the 13th century when eyeglasses were first invented," but it took centuries for this technology to really flourish. In the 1960s, Edward Thorpe and Claude Shannon were the pioneers who commercialized smart wearables by creating a tiny computer that could fit into a shoe or around the waist. In the 1970s, wearables entered the fashion world as Pulsar released its first calculator wristwatch. According to Insider, unlike Casio calculator watches that later helped popularize these wearable technologies, Pulsar watches were 18-karat gold and were sold at high-end jewelry stores like Tiffany's.

In the last decade, we have seen a massive shift in wearables, especially with the push of large companies like Google and Apple products. AR and VR headsets are now becoming a big part of the gaming world, especially with the rise of the metaverse.

The future of smart wearable technology is mostly linked with interconnectivity among devices and the ability to sync data between wearables and mobile phones. Energy harvesting is another big domain, and it pertains to converting body heat, movement or solar energy into power. Innovative companies like Epeasare working on ambient energy harvesting, processing and sensing solutions in order to make wireless devices that do not need to be actively charged. Another innovation that Facebook is working on is non-invasive sensors that will allow hands-free typing using your brain activity.
In The Metaverse
Other breakthrough innovations relate to haptic technology, which can create an experience by applying forces, vibrations or motions to control virtual objects. Engineers are working on recreating realistic touch sensations while engaging human-computer interactions.
Fiction Or Reality
Haptic devices can be grouped into three main types: graspable, wearable and touchable. Graspable gadgets are used by professionals like doctors to operate remotely or by engineers to repair space satellites from Earth. Wearable haptic devices can also communicate through vibration. This can be integrated into clothing for giving direction and helping someone walk, hear and see in the virtual world. Touchable interfaces pertain to smartphone screens and can allow the users to feel various textures remotely. This is something that is especially promising for online shopping and virtual travel.

Facebook's rebrand to Meta in late 2021 made the metaverse a household name. I believe the new 4-D immersive universe is about to profoundly transform our digital lives. This is important for all entrepreneurs and brands, as it will have a major impact on how clients act and interact with our products and businesses. AR, VR and XR devices will offer a possibility to engage in a completely new shopping experience. If you cannot leave your house for some reason, you can now just simply wear a device that can connect you to the other side of the world.

In 2018, Steven Spielberg released the movie Ready Player One based on Ernest Cline's bestseller of the same name. It depicts a future where people use avatars to escape to a virtual entertainment universe called OASIS. I believe many of the science fiction elements depicted in this story will soon be here, and companies need to gradually adopt Web3 trends to keep up. Of course, there will be a transitional phase with hurdles related to the development of the infrastructure as well as cost implications, so be prepared for this.

Overall, we are moving fast from the first prototypes invented 50 years ago to a world where an XR or haptic device may become a part of your everyday life. Generations Z and Alpha already spend much of their time in the virtual world. I think the time has come for all companies to join them there and continue working on sophisticating the hybrid and the physical user experience. Fashion companies of the future will thus sell both virtual as well as physical items.

It seems OASIS is suddenly much more real than we ever thought possible. I believe that entrepreneurs who learn to adapt their businesses rapidly and combine smart wearables with successful metaverse applications will be the winners of tomorrow.

Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?

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How Smart Wearables Are Shaping Our Future

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I believe that entrepreneurs who learn to adapt their businesses rapidly and combine smart wearables with successful metaverse applications will be the winners of tomorrow.

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It’s time to build your business for an AI world. We help you discover AI’s potential at the intersection of strategy and technology, and embed AI in all you do. Let’s turn AI’s promise into performance.

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How we can help

It's time to build your business for an AI world. We help you discover AI's potential at the intersection of strategy and technology, and embed AI in all you do. Let's turn AI's promise into performance.

For as long as artificial intelligence has helped businesses streamline how work gets done, we've been at the forefront-whether it's defining AI frameworks for financial services clients, helping telcos establish responsible AI strategy, or embedding AI in our own digital tools .

While fast-moving AI adopters can establish a competitive advantage, they first must overcome inherent challenges-from building the right tech stack and managing the safe use of data, to training employees and ensuring output quality and proper tracking.

We combine business strategy and technical expertise to help you rethink your goals with AI in mind, then build the most high-value use cases from proof of concept to production. Our integrated team of industry and AI consultants, AI product managers and engineers, and key partners work together to propose strategies based on value, feasibility, risk, and differentiation-then deliver the solution's tech stack, operating model, and talent strategy. Crucially, we ready your organization for AI adoption by strengthening internal capabilities, training your team, and implementing change management to ensure a smooth transition.

With our fingers on the pulse of the evolving AI landscape, we understand the technology's untapped potential and its risks-and how to manage both responsibly. Our technical expertise and experience collaborating closely with early movers can help you kickstart your journey and achieve sustained success.

AI Consulting Services

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Across industries, we're helping clients strategically consider and implement use cases to improve efficiency, customer retention, and time-to-market.

Customer service chatbots, wealth advisor intelligent assistants, and personalized marketing content generation

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Contact center and chatbots, e-commerce content generation and analytics, and store ops intelligent assistants

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Our AI Experience & Impact

The Coca-Cola Company

The first company to engage with our OpenAI alliance, The Coca-Cola Company used a buzzworthy campaign to spark a two-way dialogue with consumers. "Create Real Magic" combined ChatGPT and DALL-E into a first-of-its kind platform that offered a canvas for AI-fueled experimentation.

Digital creatives were invited to tap into iconic assets from the The Coca-Cola Company's archives to generate original artwork to be displayed in New York's Time Square and London's Piccadilly Circus. By blending customer activation, stakeholder engagement, and public relations, the campaign elevated the company's world-class brands, marketing, and consumer experiences-and kickstarted its journey with generative AI.

Carrefour

French multinational retailer Carrefour has improved its customer and employee experience with three innovative tech solutions based on ChatGPT technology. Its natural-language, GPT-4-enabled chatbot, Hopla, drives a seamless e-commerce experience on carrefour.fr. Connected to the site's search engine, the advice robot retrieves customer-specific preferences, offering them smart guidance on food selection based on budget, quantities, dietary restrictions, and more.

In its journey toward becoming a "Digital Retail Company," Carrefour is also exploring other customer-facing generative AI use cases as well as internal applications. It's using the technology to enrich more than 2,000 product sheets and to streamline everyday tasks in internal purchasing processes.

InsuranceCo

When a leading insurance company recognized that consumer needs and buying habits were continually shifting, it began to strategically re-think how analytics could reshape its customer experience. Harnessing the power of artificial intelligence, we helped the company apply machine-learning algorithms against its data to continually refine predictions about which product a customer was likely to buy next. To support that analysis, we created a comprehensive data lake, integrating 20 databases into a system that contained a rich 10-year history of client and external data. After seeing promising results, InsuranceCo locked in the internal capabilities needed to scale its new analytics expertise across the organization.

Results:

25% potential boost in revenue

10x improvement in marketing performance

The first company to engage with our OpenAI alliance, The Coca-Cola Company used a buzzworthy campaign to spark a two-way dialogue with consumers. "Create Real Magic" combined ChatGPT and DALL-E into a first-of-its kind platform that offered a canvas for AI-fueled experimentation.

Digital creatives were invited to tap into iconic assets from the The Coca-Cola Company's archives to generate original artwork to be displayed in New York's Time Square and London's Piccadilly Circus. By blending customer activation, stakeholder engagement, and public relations, the campaign elevated the company's world-class brands, marketing, and consumer experiences-and kickstarted its journey with generative AI.

French multinational retailer Carrefour has improved its customer and employee experience with three innovative tech solutions based on ChatGPT technology. Its natural-language, GPT-4-enabled chatbot, Hopla, drives a seamless e-commerce experience on carrefour.fr. Connected to the site's search engine, the advice robot retrieves customer-specific preferences, offering them smart guidance on food selection based on budget, quantities, dietary restrictions, and more.

In its journey toward becoming a "Digital Retail Company," Carrefour is also exploring other customer-facing generative AI use cases as well as internal applications. It's using the technology to enrich more than 2,000 product sheets and to streamline everyday tasks in internal purchasing processes.

When a leading insurance company recognized that consumer needs and buying habits were continually shifting, it began to strategically re-think how analytics could reshape its customer experience. Harnessing the power of artificial intelligence, we helped the company apply machine-learning algorithms against its data to continually refine predictions about which product a customer was likely to buy next. To support that analysis, we created a comprehensive data lake, integrating 20 databases into a system that contained a rich 10-year history of client and external data. After seeing promising results, InsuranceCo locked in the internal capabilities needed to scale its new analytics expertise across the organization.

Results:

25% potential boost in revenue

10x improvement in marketing performance

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It’s time to build your business for an AI world. We help you discover AI’s potential at the intersection of strategy and technology, and embed AI in all you do. Let’s turn AI’s promise into performance.

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Generative AI: Unlocking the future of fashion

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Generative AI: Unlocking the future of fashion

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While still nascent, generative AI has the potential to help fashion businesses become more productive, get to market faster, and serve customers better. The time to explore the technology is now.

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As this season's fashion weeks wrap up in London, Milan, New York, and Paris, brands are working to produce and sell the designs they've just showcased on runways-and they're starting next season's collections. In the future, it's entirely possible that those designs will blend the prowess of a creative director with the power of generative artificial intelligence (AI), helping to bring clothes and accessories to market faster, selling them more efficiently, and improving the customer experience.

By now, you've likely heard of OpenAI's ChatGPT, the AI chatbot that became an overnight sensation and sparked a digital race to build and release competitors. ChatGPT is only one consumer-friendly example of generative AI, a technology comprising algorithms that can be used to create new content, including audio, code, images, text, simulations, and videos. Rather than simply identifying and classifying information, generative AI creates new information by leveraging foundation models, which are deep learning models that can handle multiple complex tasks at the same time. Examples include GPT-3.5 and DALL-E. (For more on generative AI and machine learning, see " What is generative AI?" and " Generative AI is here: How tools like ChatGPT could change your business.")

While the fashion industry has experimented with basic AI and other frontier technologies-the metaverse, nonfungible tokens (NFTs), digital IDs, and augmented or virtual reality come to mind-it has so far had little experience with generative AI. True, this nascent technology became broadly available only recently and is still rife with worrisome kinks and bugs, but all indications are that it could improve at lightning speed and become a game changer in many aspects of business. In the next three to five years, generative AI could add $150 billion, conservatively, and up to $275 billion to the apparel, fashion, and luxury sectors' operating profits, according to McKinsey analysis. From codesigning to speeding content development processes, generative AI creates new space for creativity. It can input all forms of "unstructured" data-raw text, images, and video-and output new forms of media, ranging from fully-written scripts to 3-D designs and realistic virtual models for video campaigns.

These are still early days, but some clear use cases for generative AI in fashion have already emerged. (Many of these use cases also apply to the adjacent beauty and luxury sectors.) Within product innovation, marketing, and sales and customer experience in particular, the technology can have significant outcomes and may be more feasible to implement in the short term compared with other areas in the fashion value chain. In this article, we outline some of the most promising use cases and offer steps executives can take to get started, as well as risks to keep in mind when doing so.

In our view, generative AI is not just automation-it's about augmentation and acceleration. That means giving fashion professionals and creatives the technological tools to do certain tasks dramatically faster, freeing them up to spend more of their time doing things that only humans can do. It also means creating systems to serve customers better. Here's where to begin.

Understanding the use cases

Generative AI has the potential to affect the entire fashion ecosystem. Fashion companies can use the technology to help create better-selling designs, reduce marketing costs, hyperpersonalize customer communications, and speed up processes. It may also reshape supply chain and logistics, store operations, and organization and support functions (see sidebar, "Generative AI use cases in fashion").

Product development and innovation

Instead of relying on trend reports and market analysis alone to inform designs for next season's collection, both mass-market fashion retailers and luxury brands' creative directors can use generative AI to analyze in real time various types of unstructured data. Generative AI can, for example, quickly aggregate and perform sentiment analysis from videos on social media or model trends from multiple sources of consumer data.

Creative directors and their teams could input sketches and desired details-such as fabrics, color palettes, and patterns-into a platform powered by generative AI that automatically creates an array of designs, thus allowing designers to play with an enormous variety of styles and looks. A team might then design new items based on these outputs, putting a fashion house's signature touch on each of the looks. This opens the door to creating innovative, limited-edition product drops that may also be collaborations between two brands. Products such as eyeglasses could be designed for individuals by using facial-recognition technology powered by generative AI to scan facial topography and adjust for a customer's size and style preferences.

This scenario became reality in December 2022, when a group of Hong Kong-based fashion designers from the Laboratory for Artificial Intelligence in Design (AiDLab) held a fashion show featuring generative-AI-supported designs. Using tools from tech companies such as Cala, Designovel, and Fashable, fashion designers are already tapping into the power of generative AI to spark new ideas, try myriad design variations without having to produce expensive samples, and vastly accelerate their processes. (For beauty businesses, generative AI also provides an opportunity for brands to identify new product formulations, potentially helping to reduce lab testing costs.)

Marketing

Marketing executives and agencies can use generative AI to brainstorm campaign strategies, product campaign content, and even virtual avatars for every marketing channel-and do it fast.

Striking marketing gold can often be a numbers game. Consider TikTok: there's no single winning formula for going viral on the platform. Instead, the more you produce, the higher your chances are of becoming a trending topic and boosting brand awareness and sales. Prompting a generative-AI-powered video platform to create short-form videos for TikTok or other social-media platforms can help save time and costs associated with pumping out social-media content. Generative AI can recognize patterns and trends in viral content and create new content that also follows specifications from the marketer.

These exercises can help in-house marketing teams manage their workloads while reducing their reliance on outsourcing work to creative agencies. Marketers will want to be careful with this approach, however: trying to reach consumers by replicating what other brands have done can counteract the unique identity and value proposition that a brand spends years building.

Generative AI could also be applied to personalized customer communications. Companies that excel at personalization increase revenues by 40 percent compared with companies that don't leverage personalization, according to McKinsey research.

Several start-ups-CopyAI, Jasper AI, and Writesonic, to name just a few-are helping pioneer personalized marketing at scale through generative AI. Using these tools, a marketer's daily tasks might start to look like this: they could choose the type of content they want to create, whether it's an email, a long-form blog post, or something else; add a prompt describing what they are looking for; and include the targeted audience and other parameters, such as tone, that help create marketing communications that are in line with the brand. The AI tool then offers several options from which the marketer can choose.

These tools are most helpful when applied to lower-funnel marketing channels (those that are mostly used to encourage sales conversions) as opposed to more prestigious brand-building communications. Marketers are still required to prompt and edit the work.

Sales and consumer experience

Today's generative-AI-powered chats, which use stronger natural-language processing to better understand and interact with humans, are already a measurable improvement over existing AI chats. That said, there isn't (yet) a foolproof generative-AI chatbot for businesses-current chatbots and other text-generating tools still occasionally make errors that could cause serious customer service disasters. Eventually, though, this technology could help customer support agents outsource complex inquiries-for example, using chatbots to help provide personalized responses in numerous languages.

Today, there are services that assign a generative AI "representative" to a brand to handle customer service queries across email, chat, text, and a brand's own platforms. These services help to reduce customer service wait times and improve response times.

Generative-AI agents can also serve luxury brands, particularly when it comes to "clienteling," a retail strategy whereby sales associates develop long-term relationships with a brand's highest-spending customers to encourage purchases and improve brand loyalty. (High-end brands can hit a sales conversion rate of 60 to 70 percent in luxury boutiques, through appointment-only shopping, for example.) That process has remained somewhat analog and manual, relying on brands' sales associates to reach out to customers through a variety of messaging platforms or texts, and is limited to only when those associates are working. Generative-AI-powered tools can keep the conversation going or make styling recommendations after a shopper leaves the store, coach sales associates on how to engage with customers, personalize communications for specific customers, and analyze consumer profiles and online real-time interaction.

In July 2022, apparel retailer Stitch Fix said it was experimenting with GPT-3 and DALL-E 2, the text-to-image AI generator, to boost sales and improve customer satisfaction with better styling services. These generative models are being tested to help stylists quickly and accurately interpret reams of customer feedback and curate products that customers would be likelier to purchase. For example, the AI tool could analyze all of a customer's feedback, which could include hundreds of text comments, email requests, product ratings, and online posts. If a customer regularly comments on, say, the "great fit" and "fun color" of a certain style of pants, DALL-E could generate images of similar pants that the customer would likely want to purchase. The stylist could then find similar items in Stitch Fix's inventory and recommend them to that customer.

Virtual try-ons are yet another example of how generative AI can improve sales and consumer experience. Paris-based Veesual enables virtual try-on integration for e-commerce fashion brands, meaning customers can choose their model and pick clothes to try on.

How to get started

As exciting as generative-AI technology might be, companies will still want to tread cautiously before entrusting any of their core tasks entirely to generative AI. But neglecting to explore the possibilities that this technology offers could be just as risky, given the pace at which it is evolving and the explosive growth of the user base. Executives can start thinking now about how their businesses could use generative AI. There are a few steps leaders can take to begin.

Make value your North Star

Fashion leaders should outline where generative AI can offer the greatest value to their business. Start by noting which areas-creative design, merchandising, runway campaigns, or clienteling-could benefit the most from generative AI. Leaders can then prioritize the generative AI use cases they should pursue based on the level of impact the use cases may have on their business. Some measures of impact include improving customer satisfaction scores and reducing customer service wait times.

Once the value is identified, use cases should also be prioritized according to how feasible they are to implement; determining how seamlessly generative AI can be used will depend on things like a team's technical skills. Afterward, teams should build a short-term road map to test and validate these use cases. At the same time, they can also consider what long-term goals might include, such as how to build a generative-design platform that can be updated and used by designers for every season.

It may be tempting to have a bit of fun with generative AI, but harnessing its power will take extra diligence. Fashion executives must be intentional in building tools that can deliver value rather than experiment with existing tools indiscriminately.

Know risks and plan to mitigate them

In a previous article, we listed some of the risks of using generative AI. One is that the legal parameters around generative AI's use are still being ironed out. Designers are sometimes criticized for creating derivative works and copycat designs. Determining who owns the intellectual property and creative rights to AI-generated works, which could be based on multimodal data sources such as other designers' past collections, will be decided on a case-by-case basis until there is a strong legal precedent. (Although it doesn't involve generative AI, the high-profile battle between Hermès and artist Mason Rothschild surrounding MetaBirkin NFTs, in which a judge ruled that the NFTs infringed on Hermès's trademark, shows how fashion brands can become embroiled in legal conundrums when new technologies emerge.)

Another risk is bias and fairness in generative-AI systems, particularly around biased data sets, which may present reputational challenges for brands that rely on the technology. For example, if an image-generating tool produces an advertising campaign with inappropriate or offensive images that are then shared globally, a brand's reputation could be hurt. And pointing fingers at the company AI in an attempt at damage control may do little to calm consumer ire.

There is also the risk that employees who use generative AI are not fully aware of its shortcomings and may fail to check for errors introduced by the technology. In this case, businesses must regularly train employees and provide them with the resources they need to understand how to use the technology.

While risks are unavoidable, executives can mitigate their potential impact by establishing a process to address risk, ethics, and quality assurance.

Upskill your current workforce

Generative-AI tools could add value to a host of different areas of a business, so it will be important to educate and train employees-including designers, marketers, sales associates, and customer service representatives-on the use of the technology.

Some businesses have already introduced AI-focused training. Levi Strauss, for one, launched a machine learning boot camp in 2021 to train nontech employees on how to use machine learning in the company's design process. Employees who complete the program create new AI tools that are relevant to their work. One of Levi's goals with the program is to increase the diversity of employees who have tech knowledge so that the company can uncover problems that employees who come from traditional technology backgrounds might otherwise miss. The program also helps teams with different specializations-such as design teams and engineering teams-communicate better and find common ground. Furthermore, Levi's has found that the program helps improves employee retention.

With an AI-savvy workforce, collaboration will take on a new meaning. Leaders should consider: How do we define responsibilities and operate collectively between technical and nontechnical roles? Design and software engineering teams can set up weekly leadership meetings to strategize quarterly road maps and working sessions among teams. Design leads can share their needs for certain insights and tools (a tool that generates design variations from a sketch, perhaps), while engineering teams deliver those tools.

Partner with the right tech support

Fashion businesses will no doubt have to invest in their workforce when it comes to leveraging generative AI, but they won't have to build out applications or foundation models themselves. Instead, fashion leaders can partner with generative-AI businesses and experts to move quickly. A fashion executive might partner with a business (such as Microsoft or OpenAI) that provides new technology or a partner that provides support capabilities (such as cloud computing or APIs).

While the potential use cases for generative AI are coming to light quickly, the future of this technology in the apparel and luxury industries is still being stitched together. But experimenting with new tools today means opening infinite possibilities tomorrow.

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Generative AI: Unlocking the future of fashion

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While still nascent, generative AI has the potential to help fashion businesses become more productive, get to market faster, and serve customers better.

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Building Trust In AI: Overcoming Bias, Privacy And Transparency Challenges

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Building Trust In AI: Overcoming Bias, Privacy And Transparency Challenges

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Artificial intelligence (AI) has the power to revolutionize industries, boost efficiency and drive innovation. Its influence spans areas like healthcare diagnostics, financial advice and personalized marketing.

However, with this potential come serious ethical challenges. As AI becomes more integrated into society, leaders must address key concerns around bias, data privacy and transparency. Neglecting these issues risks public mistrust, legal consequences and unintended societal impacts.

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Building Trust In AI: How To Overcome Ethical Challenges

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As AI becomes more integrated into society, leaders must address key concerns around bias, data privacy and transparency.

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Very Important People: Status and Beauty in the Global Party Circuit

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Very Important People: Status and Beauty in the Global Party Circuit

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A sociologist and former fashion model takes readers inside the elite global party circuit of "models and bottles" to reveal how beautiful young women are used to boost the status of men

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A sociologist and former fashion model takes readers inside the elite global party circuit of “models and bottles” to reveal how beautiful young women are used to boost the status of men

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Circularity, carbon, community and pre-competitive collaboration, the four C’s of sustainability, dominated this year’s Global Fashion Summit in Copenhagen. The resounding message? Urgently needed progress is reliant on the industry working together to achieve it.

“To go faster, the entire industry has to be mobilised behind sustainability targets,” says Francois Souchet, global head of sustainability and impact at New York consulting and communications agency BPCM, who attended the summit with 900 members of the fashion industry across Kering, the United Nations, Burberry and Nike. If it wasn’t already clear that sustainability is incredibly complex, this summit proved it, he says.

This year’s theme was “alliances for a new era” but high-level pacts and promises can only go so far, says Fashion Innovation Agency’s Moin Roberts-Islam. “Bold, visionary statements give the industry a North Star, but they often don’t change the situation on the ground. Real progress will come from brands collaborating with their competitors and meeting solutions providers, sharing successful case studies for others to learn from and replicate.” To this end, many criticised a lack of diversity, and particularly speakers from within the supply chain, at the forum.

The fashion industry does have several alliances at play, but they are disjointed and mostly voluntary. The Fashion Pact, which includes over 75 groups and companies, with brands from Gucci to Chanel, has promised to stop global warming, restore biodiversity and protect the oceans, but is not legally binding. Similarly, the UN Fashion Industry Charter for Climate Action has levels of membership, with some signatories committed to its clauses and others for whom implementing change in their own supply chain is not a condition of entry.

Select attendees were given a masterclass on the new GFA Monitor report, and how to take action from it.
Photo: Courtesy of Global Fashion Summit: Copenhagen Edition

There were some positives: universal standards and shared industry values were core to the GFA Monitor, a new report to guide fashion brands towards a net positive industry by the event organiser, Global Fashion Agenda (GFA). GFA also unveiled the Global Circular Fashion Forum, a global initiative to scale the recycling of post-industrial textile waste in textile manufacturing countries. Supply chain transparency and traceability platform TrusTrace released an open-source traceability playbook in collaboration with campaigning organisation Fashion Revolution and Amsterdam-based change agency Fashion for Good, whose partners include Kering and PVH.

But there is work to do. Hotly discussed topics were decarbonising the supply chain, sustainability in the metaverse and garment worker rights. Challenges that persist include a lack of funding for significant change and representation from the communities on the frontlines of fashion’s impact.

Several major fashion brands took the opportunity to introduce new business models; a common thread was the concept of “timeless design” that is no longer seasonal as a sustainability solution. Ralph Lauren’s new circularity strategy, announced exclusively on Vogue Business, positions seasonless items designed with longevity in mind as a key driver of rental, resale and repair services. At Kering-owned cult favourite Bottega Veneta, CEO Leo Rongone says timeless designs like its intrecciato handbags are core to its founding values. The brand will be re-releasing handbags from previous collections at their original full price, which Rongone says reflects their “enduring value”.

Global Fashion Agenda CEO Federica Marchionni giving the opening address.
Photo: Courtesy of Global Fashion Summit: Copenhagen Edition

The overall mood was a sense of unity after a turbulent pandemic period — this marked the first in-person event in two years. Whether that will move the needle remains to be seen, and participants agreed that more diverse voices are still needed at the table. “We all turned inward during the pandemic,” says Allbirds head of sustainability Hana Kajimura. “It has been great to see the big picture again, and get a pulse on where the rest of the industry is.”

Collaboration took centre stage

A bombshell came from Liz Ricketts, founder of The Or Foundation, a non-profit based between the US and Ghana, which advocates for environmental justice and awareness around the impact of thrown-away fashion burdening Kantamanto market in Accra, Ghana, such as the crushing physical impact on women carrying bales of clothes, and the 40 per cent that remain unsellable, often diverted to Ghana’s shores and landfills. The Or Foundation will receive $5 million annually for three years from fast fashion retailer Shein — recently reported to be worth $100 billion — as part of the brand’s Extended Producer Responsibility Fund.

“We have been calling on brands to pay the bill that is due to the communities who have been managing their waste, and this is a significant step toward accountability,” says Ricketts. “What we see as truly revolutionary is Shein’s acknowledgement that their clothing may be ending up here in Kantamanto, a simple fact that no other major fashion brand has been willing to state as yet.”

The Or Foundation co-founder Liz Ricketts sharing the news of Shein’s $15 million grant.
Photo: Courtesy of Global Fashion Summit: Copenhagen Edition

The audience response was mixed, with critics pointing out that this is pocket change for a company the size of Shein, and it isn’t sufficient to donate without changing the business model creating waste in the first place. “You can’t run a permanent programme on $15 million, especially over three years,” says Joanne Brasch, special project manager at the California Product Stewardship Council.

Sustainable fashion writer and advocate Sophie Benson summed up the complexity neatly. “The Or Foundation’s agreement with Shein does not represent an endorsement of the brand’s practices,” she says. “We should not be celebrating Shein for doing the absolute bare minimum in mitigating its impact and it doesn’t excuse the waste it creates or the harm it causes. But the money will prove vital in supporting and furthering The Or Foundation’s work, and those who are not on the ground doing that work have no place criticising them for accepting the money.”

Adam Whinston, Shein’s global head of ESG, said via email that the partnership is about transparency. “Through this agreement we acknowledge that some of our clothing may be ending up in Kantamanto, and other markets like it. This acknowledgement is a first step toward our goal of industry-wide reckoning.”

Funding climate action was another running theme. The Apparel Impact Institute announced a $250 million Fashion Climate Fund, backed by H&M and Lululemon. The fund is aimed at decarbonisation, and will finance initiatives throughout the supply chain, from transitioning to renewable energy to scaling next-generation materials.

Others made individual commitments, in the hope of inspiring more brands to follow in their footsteps. Copenhagen-based Ganni, whose founders hosted select attendees for a dinner in their home on Tuesday night, brought three next-gen ‘fabrics of the future' – Mylo, Stem and Circulose – to market, with limited-edition releases aimed at supporting material innovators to scale.

Ganni founder Nicolaj Reffstrup on the action stage, sharing the brand’s journey from carbon offsetting to carbon insetting.
Photo: Courtesy of Global Fashion Summit: Copenhagen Edition

British brand Mulberry said it will work with Eon to embed all products with digital IDs by 2025, starting with pre-owned items bought back for its Mulberry Exchange programme, and extending to new products in the next year or two. Mulberry is the first member of the Sustainable Markets Initiative Fashion Task Force to follow through on its commitment to embed digital product IDs, and CEO Thierry Andretta says he hopes the move will encourage other members to move faster. “Authentication is important to customers,” he explains. “This is the future.”

Diverse voices bring more fruitful discussions

Among attendees, there was a general consensus that diversity and authenticity should be at the heart of conversations about change. Many commented on the lack of conflict between panellists on stage, remarking that collaboration often involves difficult conversations. “We strive to hear from many voices, and we always promise to be more global, driving more impact,” says GFA CEO Federica Marchionni, who joined in 2021 from Secoo International.

“This year’s summit saw a huge increase in diverse voices from all over the world, with different lived experiences who hold power in fashion coming together to learn,” says designer and educator Rahemur Rahman. “I wish the garment workers, leather tanners and farmers — the people our decisions affect — had more presence.”

A panel called ‘Subverting Fashion’s Historical Exclusion’, with In Futurum co-founder Moussa Mchangama, Better Buying Institute co-founder Dr Marsha Dickson, and Buzigahill founder Bobby Kolade.
Photo: Courtesy of Global Fashion Summit: Copenhagen Edition

Nina Stevenson, head of education at London College of Fashion’s Centre for Sustainable Fashion, agreed. “Fashion is still on a business-as-usual trajectory. If the solutions work continues to be driven by those in the Global North, without listening and learning from those personally affected by our actions, then it will be in vain.”

Still, others acknowledged the progress made since its foundation in 2009. Marchionni notes the diversity of attendees was limited by Covid-19 travel restrictions and challenges. To help counter this, GFA is planning to expand its reach, with a new summit in South-East Asia soon to be announced. “We want more representation across the value chain,” she explains.

The real measure of the summit’s impact will be in the months to come, Marchionni continues. GFA is planning to survey attendees several times in the next year to understand what has changed as a result of the summit, and the connections formed there. “It’s good to take a pledge and make a commitment, but you need discipline in the follow-through.”

Comments, questions or feedback? Email us at feedback@voguebusiness.com.

More from this author:

Bottega Veneta to re-release archival pieces, build lifetime repairs

Ganni launches zero-waste trousers and mushroom wallets as next-gen materials reach shop floor

The open-source playbook backed by Adidas that could transform traceability

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Key takeaways from the Global Fashion Summit: More diversity, more collaboration

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Last week, fashion leaders gathered in Copenhagen for the annual Global Fashion Summit. There were collaborations and commitments, but voices on-stage lacked diversity.

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Power in numbers: How independent designers are getting resourceful in a tough market

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Power in numbers: How independent designers are getting resourceful in a tough market

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Jonathan Cohen and Sarah Leff got together a group of 14 designers for a three-day New York pop-up, in a bid to engage consumers amid tariff chaos. Here, community is key.

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Oldham is also optimistic about the connection the pop-up will foster on the designer side. "We're all kind of in the same world, which is nice to build community through this sale with like-minded designers," he says. "It's a good group of a lot of people who I'm friends with and others who I've admired from afar."

The Collective is the first major effort from independent designers to push for sales - and connection - amid tough times. Other brands, though, have embarked on similar physical initiatives to reach clients at this moment. Lingua Franca, for instance, is planning to host more trunk shows to get products directly to consumers. Realisation Par, which paused shipping to the US on 23 April (all of the brand's silk garments are made in China), is hosting a Los Angeles pop-up from 22 to 30 June as a way to reach US consumers without shipping garments into the country. (The pop-up was announced before the China tariffs were paused for 90 days.)

Oldham, for his part, had hoped to organise a sample sale with fellow New York designers, as he told Vogue Business in April. "Jonathan and Sarah beat me to it," he jokes. He's glad that the pair were able to leverage their network built over the course of their 14-year brand journey, making the pre-packaged deal an easy yes.

It's the right time for a new model, Cohen and Leff agree. Cohen recalls advice he gave students on a recent Parsons School of Design panel: "I told the kids that, aside from being innovative in design, you have to be innovative in business. That's almost more exciting right now - these new systems, rather than a new silhouette." These new systems, from methods of production to communication with clients, are what's missing in fashion right now, Cohen says. "It's really important to be constantly thinking of new systems to get your clothing on people."

"Aside from being innovative in design, you have to be innovative in business."

It's a conversation that comes up a lot amongst designers of this next generation, Ripley says of her peers. "There's a real sense of wanting to have ownership over our sales," she says. "For many of us, at least in our case, we were able to build the brand thanks to the support of our wholesale partners. But making the shift from wholesale to DTC takes time, infrastructure, and funding which aren't always present."

Initiatives like this offer a way in. The pop-up may not be a new concept, but rallying a brand's community to enable designers to keep 100 per cent of profits generated at said pop-up is a significant milestone. Can it be replicated beyond this brief moment?

Cohen and Leff are optimistic. "Obviously we need to tackle this first weekend and see how everyone's sales are," Leff says. But they're keen to expand beyond New York. "There's always the possibility of doing LA and other states," Cohen says. "People are excited when designers come to places like Nashville."

Comments, questions or feedback? Email us at feedback@voguebusiness.com.
More from this author: No naked dressing, no big gowns: What Cannes's new rules mean for stylists The US-China trade agreement brings relief and whiplash for brands Australian Fashion Week cheat sheet: Resort 2026

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Power in numbers: How independent designers are getting resourceful in a tough market

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Jonathan Cohen and Sarah Leff got together a group of 14 designers for a three-day New York pop-up, in a bid to engage consumers amid tariff chaos. Here, community is key.

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The BFC Announces London Fashion Week Festival Line-up

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The BFC Announces London Fashion Week Festival Line-up

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The BFC Announces London Fashion Week Festival Line-up

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The British Fashion Council (BFC) is delighted to release the line-up of this year’s London Fashion Week Festival with a schedule of industry talks, designer catwalks and immersive wellbeing experiences.

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TikTok What's Next 2024: In Action Trend Report

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TikTok What's Next 2024: In Action Trend Report

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Brat, bodysuits and bag charms: The year in TikTok

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Brat, bodysuits and bag charms: The year in TikTok

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The micro-trend cycle picked up speed in 2024. Here are some highlights from the Vogue Business TikTok Trend Tracker.

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4 key takeaways from London Fashion Week AW25

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4 key takeaways from London Fashion Week AW25

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AW25 was a quieter season but designers showed up in new ways, proving that resilience and creativity will always reign at LFW.

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In Santa Fe, Native Fashion Week Was a Celebration of Community

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In Santa Fe, Native Fashion Week Was a Celebration of Community

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Amid a backslide in the industry’s commitment to body and age diversity, at Australian fashion week some designers are taking a different approach to casting