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Levin cited mint-green dresses, a top seller earlier this decade. “One day it just died,” she said. “It stopped. ‘O.K., everything mint, get out.’ Right after, it looked old. You could feel it.” But retailers adept at using algorithms and big data tend to employ fewer buyers and assign each a wider range of categories, partly because they rely less on intuition. At Le Tote, an online rental and retail service for women’s clothing that does hundreds of millions of dollars in business each year, a six-person team handles buying for all branded apparel — dresses, tops, pants, jackets. Brett Northart, a co-founder, said the company’s algorithms could identify what to add to its stock based on how many customers placed the items on their digital wish lists, along with factors like online ratings and recent purchases. Nathan Cates, a Bombfell buyer, in a T-shirt from among the company’s offerings, with Will Noguchi, a stylist. Bombfell’s algorithms help Mr. Cates make choices about what to buy, but he is obsessive about touching the fabric before acquiring an item and almost always tries it on first.CreditJeenah Moon for The New York Times Bombfell, a box service similar to Stitch Fix catering only to men, relies on a single employee, Nathan Cates, to buy all of its tops and accessories. The company has built algorithmic tools and a vast repository of data to help Mr.

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