LONDON, United Kingdom — The rise of online platforms — Amazon, Alibaba, JD.com and Zalando, among others — has put fashion brands in a conundrum. While many have been sceptical about engaging with these online behemoths, for a growing number of fashion brands, these ubiquitous platforms have become a requisite sales channel now that their reach is so vast. This has only intensified as brands become increasingly aware they are no longer just competing with their peers, but also with social networks and streaming services — anything that engages users online — for attention.
Attracted by convenience and choice, more consumers look to online platforms as their first point of search. For instance, Amazon — which retail analysts predict will be one of the first-ever $1 trillion companies by the end of 2018 — is an enormous platform with a number of high-margin business operations, including its own site and third-party marketplace, offering a huge selection of brands in one place, making it an incredibly powerful resource.
“If I go on Amazon now and search for running shoes, I’ll get over 1.3 million recommendations from different brands. Retailers are now able to merchandise an astonishing assortment of products online. They’re able to fill that gap of product knowledge that is completely impossible to provide in a physical store environment — and they can transact consumers in one click,” said Doug Stephens, a retail industry futurist and author of “Reengineering Retail: The Future of Selling in a Post-Digital World.”
Yet Amazon’s colossal offering of products can easily become overwhelming. Too many product options can make decision-making difficult, leading to the possibility of fewer sales. This is where personalisation comes in and explains why it has become the holy grail for online platforms across the planet. Amazon knows what shoppers have bought in the past, are buying now, and are likely to buy in the future — with the insights derived from people’s purchases and searches.
What artificial intelligence (AI) can do is help turn large and diverse data sets into enriched information that can be used to improve the entire supply chain, from design and manufacturing to sales, marketing and customer service. Unrivalled customer data from platforms like Alibaba or Amazon, combined with a suite of powerful tech tools, opens up other powerful new possibilities for fashion brands too.
“Amazon in the US is one of our biggest and fastest-growing customers today. They’re a force and a major customer. Outside of the US, [online retailers like] Tmall, Zalando and Flipkart are big. Brands have to consider what their strategy is with each of these [platforms]. Do they want to play or not?” said Chip Bergh, chief executive of Levi Strauss & Co., for whom these platforms have simply become far too big to ignore.
Levi’s isn’t the only brand to realise the potential of platforms. Calvin Klein was among the first companies to embrace Amazon by selling a selection of products — mainly underwear and denim — through the online retailer. As Amazon has grown, more labels, including Nike and Kate Spade, have overcome concerns about pricing, presentation and the prospect of working with a potential rival.
“Access to consumer data is the holy grail for platform businesses because exclusive ownership of data allows them to exert control over the rest of the ecosystem and makes it attractive for third parties to come on-board the platform,” said Sangeet Paul Choudary, founder and chief executive of C-level advisory firm Platform Thinking Labs and international best-selling author of “Platform Revolution and Platform Scale.”
“It’s important for brands to realise that they can no longer lean on the idea that fashion is something that won’t be consumed by e-commerce. Platforms have the potential to gather tremendous amounts of data and predict what [customers’] wants and needs are going to be,” said Stephens.
This is the key to personalisation. When done right, it can be a major boon for consumer businesses in the era of unlimited choice. Respondents to the BoF-McKinsey Global Fashion Survey identified personalisation as the number one trend in 2018. Another report by McKinsey & Company found that targeted communications, which are relevant and useful, could create lasting customer loyalty and drive revenue growth of 10 to 30 percent. This is understandable given that more than 70 percent of consumers in the US now expect personalisation from online businesses, according to a survey by SEO platform Linkdex.
David Schneider, co-founder and chief executive of European e-commerce giant Zalando, believes that personalisation is even more important for the fashion sector than others. “It is our angle to really create a great consumer experience, be it the offering of unlimited choice [or] being able to personalise [and to] make it really relevant. I think fashion really deserves its very own solutions because... it's quite different from other products. It's quite an emotional product, it's very much trend driven, it's opinionated, it has a lot of social angles to it,” he said.
Personalised enhancements offered by platforms could include generating uncannily precise product search results, smart search engines that draw attention to products consumers might not have realised they wanted, or virtual storefronts that display information tailored to individual shoppers based on their unique characteristics and preferences.
Such developments are subtle but effective, said Sébastien Badault, managing director of France at Alibaba Group and the firm’s global business development leader for the luxury brands category. “That’s the first step. It’s great for brands [that work with Alibaba] because it means we can effectively sell your brand. We are not going to show or push your product to somebody who hasn’t expressed an interest in it, or your brand.”
Alibaba has quietly been testing AI technology, which helped drive the success of this year’s Singles’ Day event, where it sold a record 168.2 billion RMB ($25.3 billion) worth of goods. The new technology — dubbed “FashionAI” — is able to recommend complementary products based on information about a shopper’s previous browsing and purchase habits on its shopping sites, like Tmall and Taobao. The system is also currently installed free of charge at selected stores across China, allowing users to generate outfit matches from hundreds of items, like a personal stylist.
“Over 1,000 brands at this year’s festival converted 100,000 physical locations into ‘smart stores.’ Through this highly interactive platform, merchants [were] able to better engage with their consumers, generating more revenue,” said Meifang Chen, senior manager at Alibaba Group UK. “[Using AI] recommendations can be incredibly accurate and the beauty of this technology is that it gets smarter and smarter. With every user that it interacts with, the capabilities improve,” added Stephens.
Personalisation strategies differ according to the type of platform — and there are many different business models out there. Farfetch, for example, allows luxury fashion boutiques around the world to sell online without maintaining their own costly digital operations. The site almost acts like operating system for retailers and envisions a future where third parties will build their own applications on it, the way developers build their own apps for iOS or Android.
“There is a distinct difference in that Amazon is both a retailer and a marketplace, whereas Alibaba is just a marketplace,” said Alibaba Group’s Badault. “So if you’re Burberry, you will be selling directly to the consumer, but Saks Fifth Avenue is on our platform [and they are] also selling your products.” What this could mean for Burberry is that “a Burberry trench coat could be $300, but Saks [might be] selling it for $250.”
Better Customer Service
Creating a better consumer experience through personalisation can improve customer retention and create a smoother browsing experience, which lets shoppers reach the checkout quickly, spending less time searching for the product they want.
“What these platforms essentially have is a fundamental core loop at their centre. The more data they gather, the more personalised their services become — and that helps to engage consumers even further, allowing them to gather even more data,” said Choudary. This is significant because there is just as much value for platforms to capture what Choudary calls “interest data” as much as “transactional data.”
Access to consumer data is the holy grail for platform businesses because exclusive ownership of data allows them to exert control over the rest of the ecosystem.
“Imagine if [platforms] could leverage Google and Facebook’s big data in addition to their own. That’s essentially what JD.com is doing today. We’re co-operating with the leaders in social media and search [in China], giving us an unprecedented amount of data to create better personalised marketing than anyone in the world,” said Xia Ding, president of JD.com’s fashion division, referring perhaps to the firm’s alliances with WeChat parent company Tencent and Baidu, China’s largest search engine.
Under a deal with the latter, users browsing for product information on Baidu’s mobile search app can now access a dedicated section to buy items directly from JD.com. By encouraging users to stay within the app and make purchases, JD.com is able to garner valuable data on its customers’ preferences.
Personalisation doesn’t only benefit the brands and platforms battling for market share; customers too benefit from sophisticated algorithms. AI, for example, can operate chatbots that mimic consumers’ interaction with a sales associate or a customer-care assistant. While the quality of these services vary, they can make online assistance available outside of business hours. Amazon Echo, a small device with an embedded microphone that connects the user to Amazon’s personal assistant Alexa, is one of the most recent applications of AI by a retailer.
Brands like Tommy Hilfiger, Burberry and Levi’s have also deployed AI-powered chatbots in a bid to improve the relationship with their customers. Tommy Hilfiger’s chatbot was introduced during New York Fashion Week in September 2016 when the brand announced its partnership with model Gigi Hadid. Developed in collaboration with Msg.ai, the chatbot let consumers explore pieces from the brand’s new collection by asking questions that help identify user’s individual tastes and sizes. The goal was to drive traffic to the Tommy Hilfiger website and create a personalised customer experience around their new collection.
Smarter supply chain
Platforms can also use AI technologies to make appropriate business decisions and improve the supply chain, going as far back as packaging or R&D. “This is especially important in the case of industries like fast fashion, where user tastes change very quickly and supply chains are usually slower to react. In such scenarios, having a direct link between the actual data being gathered from users about their tastes and what they’re interested in — and conveying that back up the supply chain — means that designers and developers in the business can come back with the right products, in much shorter lead times,” Choudary explained.
Amazon, which previously applied for a patent for “anticipatory shipping,” uses AI to predict which products will be popular among customers in certain neighbourhoods and cities, and then stores those products in small warehouses nearby. This enables retailers to maximise the profitability of having the right items in stock before the customer orders them, which results in faster fulfilments and leaner inventory operations.
In some cases, AI can help automate tasks, freeing up time and resources for companies to invest further in personalisation. In March 2017, Coca-Cola teamed up with Salesforce and used its AI platform “Einstein” to automatically keep track of items in stock and replenish them when necessary, eliminating the need to manually monitor and reorder inventory. AI automation also removes human error from the equation.
According to 2017 findings by McKinsey & Company, an AI-based approach could also reduce forecasting errors by up to 50 percent, while overall inventory reductions of 20 to 50 percent are feasible. Stitch Fix currently uses AI to improve its clothing designs by analysing images and learning about specific styles of clothing. The subscription company generated $977 million in net revenue in 2017, up from $730 million in 2016, helping it to edge in on the likes of Asos.
“As the feedback loop between customers, platforms and brands becomes faster and more connected, we’re going to see much more agile supply chains [as well as] more alternative supply chains coming up for the first time, where any platform that has access to user data can start connecting directly to contract manufacturers,” said Choudary.
Trade-offs and the future
The trade-off for an increasingly personalised and expeditious service on platforms, however, is customer privacy.
“Privacy is like currency. Like any other currency, consumers are ultimately going to send that currency to brands and retailers they feel they can trust. It’s going to become a basic business attribute that if you want to be successful and you want to have close, loyal relationships with customers, you’re going to have to prove to them that you respect their information and that you will treat it with care,” said Stephens.
“We’re coming to a point where if a customer wants tailored recommendations and customised solutions, they will have to give up some data in order to get to that point,” he added. Indeed, a 2017 report by RichRelevance, a San Francisco-based company that offers personalised shopping experiences for retailers including Macy’s and Barneys New York, found that global consumers are willing to share data in return for better customer experience.
As the feedback loop between customers, platforms and brands becomes faster and more connected, we’re going to see much more agile supply chains.
“The efficiencies that data can provide, from online marketing to the digital user experience to the physical experience, will be a game changer,” said José Neves, founder and chief executive of Farfetch. “The company with more data receptors and more data intelligence will win.”
Choudary believes that brands looking to scale should focus on the depth of data rather than the breadth of data. “Personalisation only becomes powerful when you have depth. If you want to personalise at scale, it’s important to go deep before you start going broad. It might mean focusing on a particular-use case, getting deep data and personalising your services around that case, and then using these services to gather new data.”
“In the long-run, there are a few things that will be really important. One is that companies will move away from focusing purely on transactions to focusing on engaging users, because engagement leads to data and once you have data, you can move users towards new transactions,” Choudary explained.
Looking further ahead, personalisation and AI is impacting the industry in more ways than just boosting supply chain processes and omnichannel. Platforms allow for collaboration, which has become essential for companies that want to survive in the digital world. They can create shared value by joining forces to share consumer insights, allowing for a higher degree of personalisation than a brand could ever realise by itself.
Gillette, for example, offers personalised grooming advice for men on its e-commerce website. Using its latest iOS app, customers can take a picture and try different looks. They can also connect with grooming experts and third-party non-competitive producers of grooming products. Men benefit from the personalised experience while platform participants benefit by interacting with a potential pool of buyers.
“[AI] is helping to change the kinds of expectations that users have. Branding is going to change in a big way. Brands are going to become platforms and they will rely less on traditional branding and more on fostering networks that build up the image of a particular brand,” said Choudary.
For Zalando’s Schneider, ultimately “it’s about learning how to work together and making use of each other’s strengths, which I think results in a better consumer proposition.”