Whle working on a PhD in astrophysics, Chris Moody used supercomputers to simulate how galaxies crash into each other. For his first nonacademic job, he joined Square as a data scientist in 2013. About a year later, he started talking with some data-scientist friends who were employed at a startup called Stitch Fix, an upstart e-commerce service that delivered boxes of women’s fashion, known as “Fixes,” using a mix of algorithmic and human curation.
Moody was mystified. “What on earth are you guys doing at a clothing company?” he recalls asking, admitting that his sartorial taste at the time hewed to “what costs less than ramen?” Their response, though, sent his brain firing. How do you mail customers clothes they’ll love, and that fit them perfectly, without the client ever getting measured or viewing the inventory? Soon he was pushing for a job. “When I was interviewing, I was like, Ooh, this is a place where I’m going to be continuously thinking about this stuff in the shower, going to bed, waking up in the morning.”
He joined in January 2015, and he’s still obsessed. Frustrated that the company only received feedback from customers on the five items mailed in each box, he designed a feature in 2017 called Style Shuffle, which allows customers to rate a set of clothing images each day. A sort of Tinder for clothes, it became available on Stitch Fix’s iOS app in March and has proven to be stickily addictive: It not only trains the company’s algorithm to understand holistically a client’s personal style, but it also draws customers back to the app and interests them in Stitch Fix’s inventory. More than 75% of Stitch Fix’s 2.9 million customers have used it, providing the company with more than a billion ratings. Style Shuffle has vastly improved the company’s ability to personalize its offerings and has boosted Fix requests. “The problems here are extremely interesting,” Moody tells me while wearing a decidedly unfrumpy Nehru-collared shirt.
Stitch Fix is using its data prowess across every aspect of its business to reinvent the $334 billion U.S. apparel industry. For consumers, it’s solving the discovery problem exacerbated by the endless sea of product online, where more than a quarter of clothes are now sold. “Here are all these beautiful things,” says Stitch Fix CEO Katrina Lake, sitting in a fishbowl conference room at her San Francisco headquarters last fall, “but the reality is only a subset of things are right for me.” By soliciting millions of customers’ feedback and precisely measuring every aspect of the clothes it sells, from more than 1,000 brands plus its own in-house labels, Stitch Fix can offer personal styling at scale, widening the market from the very rich to the average consumer, who currently pays the company an average of $55 per item to avoid the headache of shopping.