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How Analytics is Giving Fashion a Makeover

September 24, 2013 | Renee Boucher Ferguson | Data, AI, & Machine Learning

StyleSeek, a new recommendation website, utilizes data and constantly refined algorithms to help fashionistas — or fashion challenged people — discover and chose exactly the right thing to wear, at exactly the right time (think work, weekend, night out). But not everybody agrees data is the right approach. GQ's take on applying analytics to an essentially creative process, one filled with intuition, experience and, of course, an eye for style:

It has to be said that style is and always has been about individuality. This is the main problem that faces the developers of the algorithm — one they are trying to sidestep with"_Style Game, a nine-step profiling quiz that attempts to work out whether you like semi-cutaway collars by flashing up pictures and asking you whether you prefer Daft Punk or Outkast, beach houses or generously appointed New York lofts"_ Style isn’t really that cut and dry.
With about 50,000 actively registered users — and close to 200 retailers on board including the likes of Nordstrom, Macy's and Anthropologie — StyleSeek co-founder and CEO Tyler Spalding doesn't quite agree with GQ's take. The company, which started as a project while Spalding was a student at MIT's Sloan School of Management, employs ten people, half of whom are technologists and the other half content curators or people that actually understand style, "better than I ever will," says Spalding. Conquering the fashion industry is Stylesleek's first step in its mission to transform e-commerce.

Spalding spoke with MIT Sloan Management Review contributing editor Renee Boucher Ferguson about his company's data-driven mission, and its early successes.

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