In the beginning, fashion was simple and need-based. Its aspiration and possession were restricted to the rich and affluent. As the world began to shrink and globalisation took shape, and consumerism rose, fashion also started to evolve. The idea of popular fashion began to trickle down from the top of the society pyramid to the grass-root level, yet it remained simple in execution for a long time. The only providers of personalised fashion were drapers and tailors. The former would provide the textile and fabrics, and the latter would stitch the garments to customers’ taste and requirement. With fashion retail taking a giant leap through mushrooming stores and shopping markets during the 20th century, fashion was to change forever.

Evolution

In early part of the last century which was marked by world wars, economic upheavals and turbulent global politics, numerous fashion players started emerging world over – some perished in the competition over the time while some assumed colossal status and went on to lead the fashion world in the decades to follow. In later part of the last century, in a relatively settled world, the fashion industry became a mighty economic sector employing millions of people and expanding worldwide, transcending geographical boundaries. Navigating many evolutionary phases, the only thing that remained constant in fashion world was the idea of ‘personalisation’, in the form of customised tailoring or made-to-measurement (M2M) as is popularly known today. Steadily, it continued as in the days of the past when tailors used to stitch the garments, now with more professional expertise though. Fashion customers continued to demand what was in vogue or what their favourite or popular celebrities adorned. Simultaneously, the more evolved fashion companies and brands began offering fashion guided by four Ps of marketing – Product, Price, Promotion and Place. The product standardisation became the major differentiator for them. Compelled by huge demand, increased consumption and the pressure to achieve economies of scale, the standardisation of products started reflecting in sizing, styling and fits, leaving shoppers with limited or no say at all. The customer also transformed into ‘consumer’ – a study subject for fashion providers to identify the trends. This consumer was not only ‘consuming’ fashion but began consuming it more frequently and in more abundance. The result was too much variety, and even more was the ‘monotony’ of standardisation. Being in more commanding position, many brands started getting more imposing and to an extent dictating too. This kindled a ‘rebel’ inside fashion consumer who, with the turn of the century, began expressing his strong urge for fashion personalisation – a breakthrough departure from herd mentality. Driven by growing aspiration to stand out and make an individual fashion statement, today’s consumer has evolved into more assertive and expressive of his needs in regard to fashion. This compelled the fashion brands to adapt to the changing consumer behaviour and take fashion personalisation seriously. So, what does fashion personalisation mean in today’s time?

Fashion Personalisation

Literally, the term denotes customisation of fashion suiting the physical, psychological, social, and aspirational needs of the consumer. However, today’s fashion personalisation is not just fitting the clothes to a body type or providing desired style, design, or colour, but also to unravel the drivers and triggers behind individual consumer’s fashion purchasing decision up to micro detail, and to guide and recommend best fashion options matching their requirement. Additionally, there is a deliberate effort in developing a relationship ecosystem that can bring back the consumer for a repeat purchase. In other words, it is to create an individual experiential environment for each and every shopper of fashion merchandise. This makes present-day fashion personalisation a much bigger and engrossing concept, featuring two major components – product customisation and search customisation.

• Product customisation: The fashion consumers of today no longer want to imitate popular celebrity looks while putting together outfits or updating their wardrobes, rather seek individuality. This can only be delivered by creating customised fashion products that cater to the individualised need of different consumers. This continues to happen via manual M2M on one side; as well as, tech-enabled solutions involving Data Analytics, Machine Language (ML), Artificial Intelligence (AI) and Metaverse, on the other side. While there are many M2M players comprising global, regional and emerging brands, the tech-based solutions are open to all those who are willing to embrace new technologies to create personalised fashion choices.

• Search optimisation: Particularly relevant to online shopping, this works in the direction of creating shopping funnels for online shoppers searching to buy fashion items. The algorithms narrow down the searches based on search keywords and shoppers’ past purchases, preferences, item types and their features, and then recommend the most relevant product, and, if needed, with customisation options too. Integrated with all channels of customer touchpoints, the shopping sites or aggregating platforms can reach out to potential shoppers and entice them into shopping. When logged-in and browsing, their clicks indicate search intent and fashion need which is ably picked up by site algorithms to deliver desired results. The search optimisation aims at fashion personalisation for each shopper through right product identification and recommendation. The fashion personalisation can also be packaged with engaging marketing tools, which helps in creating a relationship through offline and online shopping experience.

Need to Personalise

The prime driver of fashion personalisation is the fact that the consumers are growing accustomed to it. They enjoy it when their customer experience is highly personalised, making shopping easier and recreating the personal service they would receive in-store or online even if they have to pay for it. Since personalisation puts customers at the centre of the shopping journey by not letting them wade through hundreds of items they do not care for, customers can find the products they are looking for much faster. According to Epsilon and GBH, 8 out of 10 online customers are more likely to buy from companies that help them find personalised fashion that is perfect for them. Despite the issues of data privacy, a large number of consumers are eager to give away more personal data in exchange for a customer experience that is tailored just for them. This, in turn, gives fashion brands plenty of leeway to cross-sell and up-sell different products.

Key Insights

An Accenture survey of European and North American fashion consumers revealed that 84 per cent consumers are interested in purchasing personalised fashion products, with this share increasing even higher to 94 per cent among high-spending fashion enthusiasts. The survey also found that consumers interested in fashion personalisation on average spend considerably more each year than those who are not (€500/$610 per year vs. €340/$420).

According to another research by Shopify, 44 per cent of customers are okay with brands using their personal information to personalise messaging and improving their product recommendation experience. The share of such customers remaining below half suggests that customers in a large number are still concerned about their privacy. As too much personalisation can be creepy at times, the brands that over-personalise are three times more likely to be abandoned by shoppers, reports a Gartner survey of 2,500 participants. Thus, personalisation demands a perfect balance as exhibited by Australian streetwear retailer Culture Kings that has not customised the shopping experience down to ‘first name’ tags on the website; instead, it has built four global storefronts to sell in different currencies. The strategy has now resulted in more than half of the fashion brand’s revenue coming from its e-commerce business, inspiring more local brands to branch out and offer customised shopping experiences for international customers to remain competitive by including things like geo-targeted domain names, pricing in local currency, and local product shipping with the help of third-party distribution or company-owned warehouses.

M2M Continues to Exist

Traditional M2M has its own fan base around the world, which has only grown with the time. It also serves as an answer to many uncomfortable questions posed at the fashion industry. M2M fashion brands create minimal waste and curb overproduction and overconsumption. Since the segment involves ‘made-to-order’ garments, M2M restricts formation of excess inventory, hence there is no creation of excess waste either. In addition, the longer lead time between ordering and receiving a garment slows down the rate of production, contributing to the cause of fashion sustainability.

Marginalised by ‘standardised’ fashion, the consumers with plus size or unusual and disabled body types are well serviced by M2M. The segment is nevertheless undergoing a major shift. So far, M2M was mostly in the luxury fashion space and used to cater to individual personalisation. However, it is now moving towards mass personalisation as well. The approach involves clothing companies customising clothing to an individual’s body shape and size. Once done rightly, perfectly fitted clothing with millions of customised designs can be made available to the customers.

Use of Technology

So far, personalisation was limited primarily to marketing recommendations for segmented customer based on past purchases or browsing history. With advent of technology like AI and ML, businesses have started using tools that enable them to work with all types of data across channels in real time. The trend is particularly evident among e-commerce platforms which are powered by cloud-based technologies running AI or ML algorithms and accelerating the processing and analysis of Big Data on consumers and their shopping behaviour. The enhanced analytical capabilities equip the fashion brands to provide hyper-personalised, one-to-one experiences akin to salespeople in-store. The hyper-personalisation pushes the fashion brands to reimagine how e-commerce needs to operate. The search-based online shopping is likely to shift to the individualised discovery of products and styles offered in the right size and fit, making all customers to have a curated experience on their own versions of brand websites and marketplaces – from landing page to making payments. Companies are therefore using technologies like Data Analytics, AI, ML, and even Metaverse, to build experiences that drive customer engagement and ultimately loyalty. Let us see how these technologies are aiding fashion personalisation.

Data Analytics

German fashion retailer Zalando uses data analytics to offer the customers millions of tailored ‘Zalando interfaces’. Product displays are automatically tailored to each customer from size to their favourite brands by incorporating preferences into its algorithm. The retailer explores 3D body scanning technology to enhance size and fit selections.

There is a fashion marketplace ‘The Yes’ that has built an extensive product taxonomy while also deploying ML and computer vision to synthesise hundreds of data points for each product. The algorithm then translates shopper preferences into a personalised exploration feed.

There is also a styling service ‘Stitch Fix’ that tailors the products to customers’ tastes and needs and uses a discovery tool called ‘style shuffle’ to help users indicate designers they like. Next, fast-fashion player Shein offers each customer a scrollable feed of products powered by a real-time recommendation algorithm informed by myriad data points across social media and other channels.

A luxury brand also benefits from hyper-personalisation. In luxury stores, the associates can leverage first-party data to provide customers with a unique experience no matter which store they enter, taking in-store clienteling to the next level. As the technologies advance, it is feasible that brands will be able to create digital wardrobes for each customer along with personalised styling recommendations.

Machine Language

Online retailer ASOS has rolled out an in-depth ML system that helps it to understand the relationship between different items in order to match customers with clothes. The system gets data from several sources including product price and description, sales data and the images on the product page. Aided by ML, the system algorithmically identifies various attributes of the product such as its pattern, style and target segment, and then the product recommendation engine combines this data with information on what is in shopper’s basket and saved list. The shoppers can see these recommendations on the product pages, in the app, and in communications from ASOS, and complete an outfit with perfectly matched items.

Aritificial Intelligence

In 2021, H&M invested $40 million in a men’s apparel startup ‘Thread’ which uses AI to offer custom-made fits. Today, the Swedish fashion company serves over a million satisfied customers. There is also an emerging fashion company ‘My Size’ that has opted for advanced technology in self-measuring. The My Size app allows anyone to self-measure simply by using one’s phone in lieu of a tape measure. Its expert algorithm then scans existing apparel sizes so that customers can discover which sizes would perfectly fit them. There are examples of many fashion companies who are leveraging technologies, especially AI, to enhance their fashion personalisation offering.

Visual Search

It all starts from online search wherein many customers struggle with right key words when shopping for fashion. The inappropriate key words usage ends up misdirecting the shoppers to inconsequential or irrelevant results. This makes Visual Search a great solution, as it helps fashion brands in providing the customers with the opportunity to find exactly what they are looking for in a matter of few seconds. The Visual Search becomes even more important in current times when most people get their fashion inspiration from social media platforms – a 2017 survey found that more than 70 per cent of people make fashion, style or beauty-related purchases influenced by social media.

Visual Similarity

Stock out is a big issue in fashion retail. In case of an item running out of stock, the retailer loses sale. Here AI-enabled short-term solution like Visual Showcasing or Similarity (VS) helps. The VS enables offering of alternative products that visually resemble the stock-out item which a customer is looking for. Likely to be confused with Amazon’s Collaborative Filtering (CF) the VS works on a different approach. While Amazon’s CF recommends other products that customers with similar preferences have browsed or purchased, the VS analyses specific attributes from an item that a customer has already liked. The VS is claimed to drive 130 per cent more revenue than Amazon’s CF.

Styling chatbots

The partnership of Dolce & Gabbana with Intelistyle – a fashion styling platform, has equipped its front-line sales team with instant access to AI-styling tools. The D&G teams now take into account customers’ unique features like hair colour, body type and preferences to recommend visually similar products, boosting sales. As a trend, AI chatbots are emerging as better fashion stylists compared to humans. They are replacing human advises as they can more efficiently sort out all the variables such as body type, skin, hair, eye colour or occasion to come up with the best styling advice. No wonders then that eminent brands like Victoria’s Secret, ASOS and Sephora are leveraging the chatbot service and making their customers’ product discovery journey easier. In fact, Victoria’s Secret’s Pink Line (VSPINK) has been using Kik chatbot services since 2016 to help women find their perfect bra by asking for feedback about customer’s measurements or recommending a bra for a particular occasion.

As the chatbot is integrated into a popular messaging platform, new users can access it without having to download or install another mobile app on their phones. Talking of Tommy Hilfiger, the brand also makes product styling recommendations tailored for every event, including glam, street style, classic, casual and sporty, making cross-selling and up-selling easier in the process.

Smart mirrors and fitting

Smart mirrors enable shoppers to get in-store styling advice and view themselves in an outfit without having to visit the fitting room. H&M is among those first companies that have tried smart mirrors with voice and facial recognition features. It further allows the users to take selfies and download them into their phones. On a similar line, virtual fitting is also getting traction. When pandemic kept most clothing stores closed, many brands including Macy’s and Adidas accelerated their adoption of virtual fitting rooms. For those customers who cannot trust the sizing offered online by looking at pictures of clothing, sizing technology makes it easier to find the right size for them while also helping retailers increase conversions and keep returns to a minimum.

Market is witness to Italian fashion retailer YOOX launching an AI-powered virtual styling app YOOXMIRROR in 2018 itself, which today lets the users preview how they look in a full outfit. A digital avatar of the user can be created by taking selfie or uploading a photo, which adorn more than 50,000 digitised clothes, shoes and accessories from the store’s catalogue. The finalised outfit can be shared with friends on social media for a second opinion before making a purchase.

Two Stanford Grads-founded ‘MTailor’ allows users to take their measurements in 15 seconds or less. Once a piece of clothing is spotted by customers, they can use MTailor’s app and their phone’s camera to record a quick video. The app’s 3D Point Cloud technology measures 16 body features and then creates a pattern that the company’s tailors can use to make clothing that fits perfectly.

Complete-the-look

The ‘Complete The Look’ personalisation not only builds fashion brand’s name but also creates valuable opportunities to maximise conversions by cross-selling and upselling more products. Here again AI sorts through an entire catalogue of clothing and accessories and gives a sensible recommendation to customers who are seeking guidance to complete their outfit or style statement. Luxury brand Lane Crawford’s AI-powered customised recommendations find items that look similar to a customer’s first option but with a twist – a different cut or shorter sleeves, for instance. On finalising the garment of choice, the customers can then use brand’s ‘How To Style It’ feature to complete the outfit. The feature showcases different products curated by Lane Crawford’s stylists that are available for purchase on the same site. On The Outnet – a site that sells luxury designer fashion brands, every item features a ‘Wear It With’ section that recommends customers the items that would go perfectly with the product they are about to buy, based on the look photographed.

Marketing

Research shows that existing customers spend more than new customers and the cost of acquiring new customers is relatively higher too. Therefore, to retain customers and attract their repeat purchase, a well-designed and highly personalised e-mail marketing campaign becomes a necessity. Data-driven e-mail campaigns are increasingly curated based on customers’ preferences and past buying behaviour. For many brands the segmented, targeted and personalised e-mails drive more than half of their revenue.

Moreover, as Whatsapp has become a natural platform for consumers to seek and get real-time communication from their favourite brands, Whatsapp marketing is being used effectively to answer product queries, making personalised recommendations or offering last-minute discounts to reduce cart abandonment. It is an excellent tool to acquire and convert new customers as well as reactivate them. Italian fashion retailer Max Mara has also integrated Intelistyle’s AI chatbot experience in Whatsapp to provide customers with a personalised shopping experience on a channel they use daily. Max Mara’s Whatsapp chatbot led to 18x higher customer engagement.

Individualisation

Individualisation of fashion allows brands to curate what shoppers see based on factors like gender, region and browsing and purchasing history. This helps brands not only in adapting to changing consumer preferences but also to predict which items a specific customer might purchase in the future. Such individualised recommendation helps customers find new pieces that might work with their existing outfits or fashion items that stand out on their own. American Ralph Lauren’s Polo Custom Shop does something similar. It allows visitors to create their own custom embroidery pattern with only a few taps on their smartphone or tablet. The customers can make a design in a matter of minutes and have the staff embroider it over their favourite polo shirt, cap or blazer. The service extends to RL sweaters also which customers can design on their own by choosing the colour and colour layout, front and back graphics, and sleeve designs of their liking. Likewise, British online retailer Very has personalised fashion basis a new perspective – the unpredictable English weather. Keeping weather influence on fashion shopping in mind, it launched a campaign that made clothing recommendations based on local weather patterns. When customers visit Very’s website or app, they are instantly presented with products relevant to their local weather conditions, like variety of raincoats if it is raining in their location or summer clothes if they are from a warmer climate.

Membership

Sports brand Nike’s membership programme has garnered a strength of over 140 million members worldwide by delivering personalised experience at every touchpoint. In-store, shoppers benefit from exclusive Member shopping hours, priority checkout and even meet-and-greet with professional athletes; when online, the programme members enjoy benefits of free shipping and returns, personalised deals and the ability to chat with a Nike expert who offers advice on sport and style. Most of the membership is available exclusively through the app, whether the user is in-store or elsewhere. The brand claims that the people shopping on the app spend an average three times as much as people using the website. Nike membership also integrates with the brand’s other offerings, including its running app, Nike Run Club, and smaller membership programmes for specialist interests such as SNKRS.

Phygital experience

British luxury brand Burberry is among those who are experimenting with the future of phygital experience at their stores. In select Burberry stores, shoppers can scan QR codes attached to displayed items and see them in the app. The app encourages the shoppers to explore the store that is designed with keeping social media in mind, accumulate points, and level up a cute avatar as they try interactive experiences and learn about the products. They can spend their points to unlock exclusive items and content, leading to their own journey through the store with the system personalising each touchpoint, based on their past interactions. Burberry plans to roll out the most successful elements across its other stores. Who knows other fashion brands may also follow the suit?

Metaverse

The contribution of metaverse to fashion personalisation is in the form of Non- Fungible Tokens (NFTs) – the unique digital tokens that can be owned by one person, and which are usually paid for in virtual currency like crypto. On January 1, 2022 alone, the spent on NFTs was worth $87.03 million, suggesting a NFT boom in the future. The boom will be characterised with every person having a parallel digital identity as avatars, as well as owning crypto wallets and digital goods. The customer’s imagination will turn brands into stylists as is seen in the case of fitness apparel brand Under Armour which is experimenting with NFTs in retail space. The brand’s Steph Curry collaboration reproduced shoes that the basketball star wore when he broke the NBA record as all-time top three-point shooter. Digital NFTs were released alongside the physical product launch enabling the token owners to virtually wear the shoes in three metaverse: Decentraland, The Sandbox and Gala Games. On other side, Forever 21 partnered with Roblox to create virtual fashion e-commerce stores in its metaverse called ‘Forever 21 Shop city’. Players run the virtual store as if it is their own and purchase merchandise for their avatar through the game. Fashion brands are using Roblox to create immersive experiences for users and reach Gen Z audiences, marking a new beginning.

Fast-fashion retailer ‘Pretty Little Thing’ now showcases products on virtual models. To spark conversation, the news of turning its new ‘avatar in the metaverse’ concept into a competition was posted on its Instagram page.

As the world becomes more and more digitised, more brands will be seen experimenting with NFTs and other virtual reality experiences.

Challenges

Personalising fashion has challenges too. There is still a long road ahead before it can reach its full potential. The first challenge comes from a tech standpoint as the technology involved is ever-evolving and thus always remains far from its final stages. The algorithms, mostly with emerging players, are not 100 per cent automated. Even the established players need to keep improving on existing templates. From the production side, important measures need to be taken to ensure personalisation remains feasible and cost-effective. The brands need to choose small production runs and factories that are aligned towards customised production needs. As the factories that can adapt to personalised production are few, they need to rely on high volume orders to survive. Creating a reliable and user-friendly interface that supports mass personalisation can be equally problematic. In addition, difficulties in navigating choices, measurement errors from the customer itself and the possibility of ending up with an undesirable or unexpected customised design are other problems which fashion companies will have to overcome.