How BI is helping to predict fashion trends

By , Computerworld |  Business Intelligence, Analytics, business intelligence

At one large retailer that creates its own fashions, designers use the feedback in an iterative loop to evolve fashion items, tuning each for the most enthusiastic consumer response, according to an IT executive who spoke anonymously.

First Insight offers a service that tests how consumers will react to new fashions by engaging them in activities, such as playing games at social media sites. "The application can be used for high-fashion items where there is very little history," says Greg Petro, the company's CEO. First Insight asks users what they think others would pay for test products and gauges their general sentiment about them.

What makes the results different from a focus group is that First Insight determines the "predictive relevancy" of participants' responses by seeding the exercise with products with known outcomes. It examines how their predictions match up with what actually happened with those items, assigns a weighted predictive value to each user, and factors that in when aggregating the results to predict winners and losers for the fashions on which they're building a demand prediction.

Deliverables include not just which products will sell, but suggested price ranges as well. The application is particularly useful for predicting consumer response to high-fashion items that have little or no history to go on, says Petro.

Wild Things LLC, a manufacturer of military and alpine clothing and related gear, was one of First Insight's first customers. CEO Ed Schmults, who is now on the vendor's advisory board, says he first used the service to choose the best style for a corporate logo and is using it to gauge consumer reactions to clothing styles that will launch next year under its newly licensed Smith & Wesson brand.

"Our consumer lines are absolutely driven by fashion. We want to understand customer receptivity to the product, the color, the price point," he says. "This is a very powerful tool for moderating that risk."

Elie Tahari looked at First Insight's technology, and while Aytaman says it was technically "pretty accurate," it went nowhere with store buyers. "Although they liked the idea, they didn't trust it," he says.

Gilt Groupe, which offers members-only flash sales of high-fashion items online, uses a combination of traditional analytic tools from SAS and collective intelligence from a startup company to predict which styles or brands will be winners. Stylitics, a social networking site launched this summer, uses a methodology similar to that of First Insight, but it focuses on the consumer's intentions and what they already have purchased rather than on how they think others would react to a fashion or product line, says Tamara Gruzbarg, senior director of analytics and research at Gilt (see sidebar, below).


Originally published on Computerworld |  Click here to read the original story.
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