Business
Mining Data From Fashion
"There is a graveyard full of similar companies that did not get pricing, seeding and subsidizing decisions right."
Would you trust a computer to design your wardrobe? The co-founders of Stylitics, a start-up that combines fashion with the burgeoning field of analytics, hope the answer is yes.
But the company’s strategy is as much about attracting corporate clients as it is about building a community of fashionistas. Stylitics employs an analytics platform to track and gain insights from users’ clothing choices and purchase behaviors. Customers are given incentives, such as reward cards, to log what they wear each day; meanwhile, Stylitics uses that information to help retailers track trends. “This proprietary tool is the first of its kind to surface real-time trends and behavioral analysis, helping our clients to make smarter business decisions and stay current in an increasingly fragmented marketplace,” says Rohan Deuskar, who founded Stylitics with Zach Davis.
In return for staying active on Stylitics, members get information about trends and style recommendations from experts. They can also be tapped for targeted marketing campaigns. “Members get rewards and discounts based on participation,” Deuskar notes. “This could range from silk scarves … to gift cards to experiences like sitting down for lunch with their favorite designer.”
According to Deuskar, once user participation crosses a certain threshold, the data the community produces will become of use for businesses, which have traditionally had to rely on fragmented and often out-of-date market research from customer surveys or polls.
“Stylitics can generate rich data on what one’s customers are wearing and generate interesting insights from that data,” notes Kartik Hosanagar, a Wharton professor of operations and information management. “For example, with what brands is my brand often co-worn? Or what percentage of my customer’s wardrobe is occupied by my brand? Ultimately, this kind of business intelligence can drive decisions on marketing and promotions.”
His comments are echoed by S. Ramesh Kumar, a professor of marketing at the Indian Institute of Management in Bangalore. “Capturing real-time data on consumers, especially in areas like fashion and entertainment, which are subject to dynamic shifts, is a useful piece of research,” he states. “Brands today need to offer variety, coordinate with supply chain issues and offer cutting-edge offerings. But the utility of such real-time data will be further enhanced through technology so that the data can be used to customize offerings. A traditional tool like ethnography is likely to have more uses through its online version — netnography— in the days to come.” In the Stylitics model, members are a cost center — the product rather than the customer. Revenue will be generated from fashion companies who will pay for the insights Stylitics aims to provide.
According to Deuskar, the company raised a seed round of funding in August through angel investors. “Our focus is now on delivering a great product, building our member base, and building our client list. Our expectation is that we’ll have demonstrated traction by early next year, and anticipate raising a Series A round towards the middle of 2012,” he says. “We recognize that we have a long way to go.”
A Different Model
The Stylitics model is not new. There are dozens of Internet-based data-mining companies. There are also several companies, particularly in India, using games and other freebie-offering diversions to promote brands. Those firms include Contests2win, BrandandMe and Hungama. But data mining and incentives-based branding campaigns have not been successfully married as yet. “We may use similar approaches like rewards and promotions,” Deuskar notes. “But I think we’re fundamentally a different kind of business.”
Hosanagar says that the Stylitics concept is not about universal brand promotion or employing a one-size-fits-all approach, which could be the kiss of death in the fashion industry. “It’s about knowing which products are likely to sell out soon and which ones will not sell out this season, so that [retailers] can make better decisions about markdowns. It’s about identifying emerging trends so [retailers] can bring the right designs to market.” Ultimately, he adds, “Stylitics can help fashion brands get better visibility into their customers’ tastes and preferences. This will allow them to make better management decisions, from designing the next season’s products to identifying the right prices at the store.”
But Stylitics is facing plenty of competition from established companies trying to turn user analytics into profits. “The way to think about this is whether they can be threatened or enveloped by players such as Facebook, who have the installed base, and can let people start [updating their status with] what they are wearing in addition to who they are,” notes Ravi Bapna, board of overseers professor of information and decision sciences at the University of Minnesota and executive director of the Srini Raju Centre for IT and the Networked Economy at the Indian School of Business in Hyderabad.
There is also the question of critical mass. There is obviously a point below which Stylitics will be unable to deliver statistically relevant numbers. “It’s a classic two-sided market-seeding problem,” says Bapna. “There is a graveyard full of similar companies that did not get pricing, seeding and subsidizing decisions right.”
Designed to Fit
But Hosanagar suggests that Stylitics does not need millions of users on its platform to be useful to firms. “Think of it like a panel. If the panel is well designed, a small panel of a few hundred users can generate tremendous insights,” he says. “If Stylitics can get even 200,000 active users, that will suffice. The key, though, is that these users are engaged and interact with the Stylitics platform daily so that it is possible to get the kind of analytics that [the company] hopes to offer.” Adds Deuskar: “We believe that we can build the sample sizes both demographically and regionally to make this valuable, although we may need to proactively fill in gaps over time.”
What people wear, how they portray themselves and how they are perceived is a fundamental and primal expression of their identity, Bapna adds. “Anything that furthers the matching of people’s preferences … with their provisioning by suppliers … has the potential to create value.” He sees the emergence of Stylitics and similar companies as part of a broader trend toward analytics-driven business models that will “reduce the frictions of our day-to-day existence. The really interesting question is whether the use of such analytics-driven recommendation engines can provide us with an expanded view of what people’s true preferences are over time. Will people become more self-expressive or diverse in their dressing style? Or will they retreat into the proverbial echo chamber? We don’t have a good understanding of how these technologies influence … our underlying tastes and preferences.”