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Personalisation report: Meet the fashbots of the future

Personalisation report

From image recognition to chatbots, retailers reveal how AI is revolutionising the way they learn from and interact with shoppers.

Relating to consumers is everything. From the displays at the front of stores to the data-collecting algorithms at the back end of websites and apps, retailers are relentlessly exploring new ways to connect. And the use of artificial-intelligence (AI) technology that recognises speech, images, text and patterns of online behaviour is becoming ever more integral in the quest to capitalise on the changing way we shop.

 AI learns on an ongoing basis and the systems are getting better at predicting what consumers want next, in the process taking automated personalisation to the next level.

“We believe that an AI-driven approach to personalisation is the future of marketing,” says Monetate chief executive Lucinda Duncalfe. “It gives customers what they want, which is an experience that reflects their relationship with the brand. And it gives marketers what they want, which is better performance with less effort.”

Findings from a recent report by consultancy Accenture reinforce this point: 75% of consumers are more likely to buy from a retailer that recognises them by name, recommends options based on past purchases or knows their purchase history. Shoppers also feel that good progress is being made by fashion retailers, it adds. A survey by fashion research unit Sonar found that 64% of UK millennials also believe that, as the technology develops, brands that use AI will soon be able to accurately predict what they want to buy.

This explains why brands such as Childrensalon – the global online retailer of luxury childrenswear – is actively looking to AI and experimenting with consumer photo recognition.

“We have our own social network where customers can upload imagery and create profiles,” explains digital and marketing director Clinton West. “Through this imagery, we are able to identify and understand what brands they are wearing.”

This information is then fed into the company’s main database and from there Childrensalon can use it to assist in the personalisation of each channel for every customer.

“We don’t care what segments people are in,” says West. “We want to tailor our creative and messaging specifically for each individual, so we look at everything we can to ensure we know exactly who every single customer is.”

To do this, Childrensalon uses a combination of its own in-house algorithms and machine learning. It is a potent formula that has led the company’s digital advertising revenue to increase by 76% year on year; the revenue it generates from email to progress by 64% year on year; its conversion rate to increase by 12%; and its clicks-to-purchase to drop from an average of 10 to two. The numbers are testament to Childrensalon’s successful leveraging of the consumer desire for personalisation.

West sees room for further growth using AI: “I believe that all the early adopters will reap the benefits of it in the future. Right now, Childrensalon may not be using it to its full potential, but we are definitely going to be, moving forward. As a technology, it enhances our customers’ experience. For example, given the amount of traffic we have, it’s impossible for us to employ one customer-services representative for every consumer who visits the site. So we could use AI to solve this problem by using it to answer shoppers’ questions and provide the individual with the customer-services experience that people are looking for.”

Retailers are already investing in the technology in a big way. Asos is working on an AI-powered chatbot that gives customers product recommendations, which boss Nick Beighton refers to as “Siri on steroids”. Etsy, the online marketplace for handmade goods, has even acquired an AI start-up, Blackbird Technologies, to personalise its website.

Yoox Net-a-Porter Group (YNAP) is also developing the type of technology that West is referring to. Its AI tech will initially help consumers search through clothing designs. Then, when a customer’s questions become more personal, it will suggest switching to a personal shopper. Once this switch has taken place, the bot will remain on hand to provide support when needed.

Customers can upload imagery and create profiles. Through this imagery, we are able to identify what brands they are wearing

Clinton West, Childrensalon

“You need to blend technology with the human touch, so we see artificial intelligence as interacting and engaging with our customers, and helping our personal shoppers to provide more insight to our customers,” YNAP chief information officer Alex Alexander has revealed.

Fashion etailer Spring is another early adopter. Last year, it introduced a bot-based personal shopping assistant that provided users with recommendations after asking them a series of questions on the Facebook Messenger platform. And the company’s chief product officer, Gannon Hall, assures Drapers that even more exciting innovations are in the pipeline.

He says: “When it comes to the future of personalisation, the possibilities are almost endless, but two of the areas we are experimenting in include ‘computer vision product matching’, where users can scan a product they see in a store or being worn by someone else and instantly get style-matching suggestions from our catalogue. Today’s shopper is increasingly searching for either convenience or curation. Personalisation allows us to provide both through relevant and compelling recommendations, so it’s only going to increase in importance as the retail landscape evolves.”

Key moments: How the history of personalisation has unfolded

1982: Leonard Berry and Jagdish Sheth use the term “relationship marketing” in their research into business marketing. The term later evolves into customer relationship management.

1994: Jeff Bezos launches Amazon. Using the web to sell to individuals, the firm captures the data of each purchase and within five years is working on ways to use this information to recommend products.

2006: Time magazine names “You” as its person of the year for “seizing the reins of the global media” and in recognition of the way user-generated content is changing the commercial world.

2007: Apple’s first iPhone starts a smartphone revolution. With a device in most consumers’ pockets and the creation of retail apps, businesses begin to access new data on customer behaviour.

2012: Uniqlo uses a colour-changing engine and a half-mirror touch-panel to enable customers to view themselves wearing all of the colour choices of an item they have tried on.

2014: Asos enables customers to share their purchases and styles by launching online channel As Seen on Me, in which consumers wearing Asos-bought product feature in an online gallery. 

2016: Amazon launches a prototype grocery shop in its Seattle headquarters. The checkout-free store uses sensors to record the items people pick up, then charges shoppers via an Amazon Prime account.

2017: Net-a-Porter and Mr Porter unveil new services, including a stylist function that syncs with mobile calendars to suggests outfits based on event type, location and weather forecasts.

2017: Farfetch’s “Store of the Future” links online and offline worlds, allowing retailers to connect to customers’ online preferences while they are browsing in store.

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