Four years ago, Gilt knew exactly what its customers' tastes and brand preferences were. Today, customers are less brand-oriented, so Gilt relies on predictive analytics to help buyers understand what will sell. But, Gruzbarg cautions, you have to know what you're looking for. "The analytic tools are only as good as the data on which you're elaborating. Understanding what the most relevant information is, that's critical," she says.
What's That You're Wearing? Stylistic Wants to Know
Forget tomorrow. Stylitics wants to know what you're wearing right now.
The newly launched social networking site for the style-savvy encourages its members to create a virtual closet of what they own, what they are wearing and what they are buying. It then shares the information with retail buyers, merchants and product planners so that the right merchandise appears in store windows and promotions can target hot items that will draw customers in. In exchange for sharing their information, Stylitics members can communicate directly with brands they buy and receive personalized style recommendations, special offers and other incentives.
The service, which launched its first beta in August, intends to make its fortune by selling access to member data as a subscription service. Using a dashboard, merchants can slice and dice the data to see what people are wearing and buying in real time, what styles are trending up or down and what other items are in the closets of customers who bought their products. And as the service builds a history, subscribers will be able to download and incorporate trending data for input into their own predictive analytic models, says Stylitics CEO and co-founder Rohan Deuskar.
Stylitics also gives consumers their own fashion intelligence. "We give them the ability to do the same things the brands can do," Deuskar says. For example, they can see what people are wearing in New York this week and what outfits they should pack for a trip there. Success will depend on whether Stylitics can get members to keep a running inventory of their closets, their purchases and what they wear each week. Early test results have been good, Deuskar says. But, he acknowledges, "we will have to do a fantastic job to keep them involved."
-- Robert L. Mitchell
Manya Mayes, director of predictive analytics at Attensity, says text analytics are being used on data provided from social media sites such as Storify, which lets online users create their own visual stories about what outfits they like. "The analytics identify which clothing combinations are put together most often and which ones they are keeping," she says.