Computing an outfit: Stitch Fix uses algorithms, machine learning to dress its c
Source: Marisa Kendall |
The next time you see a well-dressed individual walking down the street, stop to consider this: that spiffy outfit might not be the result of an impeccable fashion sense — it might be the work of a computer algorithm.
At least, that could be the case if the fashionista is a customer of one of several services that offer fashion delivered on demand, such as San Francisco-based startup Stitch Fix. Using data analysis software and machine learning to match users with personalized clothing choices, Stitch Fix is ushering the fashion industry into the age of Big Data.
For customers who don’t pry too closely into the startup’s inner workings, the service is intended to feel like magic.
“All they’re seeing is they order a box of clothes, and presto — it appears,” said Eric Colson, Stitch Fix’s chief algorithms officer.
Companies in a variety of industries are relying more heavily on data to provide personalized recommendations — think Netflix using algorithms to find movies or TV shows users might like, or Amazon suggesting additional purchases based on what’s in someone’s cart. Stitch Fix, which in September expanded into men’s fashion as part of its ongoing effort to revolutionize the clothing industry, uses that same technology to deliver curated boxes of clothing to customers’ doors.
The first time users try the 5-year-old service, they answer a few dozens questions about their size, style and the body parts they like to flaunt. Stitch Fix takes that data and plugs it into its algorithms, which come up with a list of clothing options. Then a human stylist reviews those choices, selects five items, and ships them. The customer has the option to buy the items or return them, free of charge. If the customer buys nothing, he or she pays a $20 styling fee per box.
Customers can schedule regular deliveries or order one box at a time. When signing up for the service, they choose from a range of clothing price options — including “the cheaper, the better.”
Stitch Fix’s software learns more about each customer every time he or she receives a shipment. The company asks what the customer liked or disliked about each item — using natural language processing to decode their written answers — and applies that data to the next shipment.
“I’ve seen the things that come in my box start to adapt to more what my personal style is,” said Kelly Walker, a music teacher at Willow Glen High School in San Jose who orders a Stitch Fix box every month.
Walker has been using Stitch Fix regularly for about a year and a half, and said she looks forward to receiving her box of goodies every month. She doesn’t think much about the technology that drives the service, mostly because she and her human Stitch Fix stylist exchange personal notes on a regular basis.
During an interview on a recent Friday morning, Walker happened to be wearing a black and white top from Stitch Fix that she loves. But the company doesn’t always get it right.
“One time definitely there was a sweater in there that I was like, ‘umm, this isn’t really my style,'” Walker said. “It was very loose and very baggy.”
Stitch Fix learns a lot about a customer by analyzing what he or she returns, Colson said, especially because many people aren’t good at articulating what they want the first time around.
“They may say they’re preppy, but it turns out they’re more of a classic or casual style,” he said. “People may think they’re a medium, but the medium — that “M” label — has a huge spectrum associated with it.”
In some ways, Stitch Fix is a tech company masquerading as a fashion company. The startup employs 75 data scientists (out of 5,000 total employees). That’s a bigger data science team than Apple, LinkedIn, Twitter, Google or Amazon had, according to a 2015 study by data firm Stitch (which is not affiliated with Stitch Fix).
StitchFix uses 50 different algorithms to conduct its day-to-day business. Aside from the formulas it uses to pick out clothes, it also has algorithms to assign each shopper to one of its 3,000 human stylists. Its tech systems figure out which Stitch Fix warehouse a client’s clothes should come from, determine which styles and how many of each item Stitch Fix should stock and even design some custom pieces. And Stitch Fix can use its data to spot fashion trends. “Cold shoulder” tops — shirts with part of the shoulder or sleeve cut out — are especially hot right now, Colson said.
That high-tech capability likely will be the future of not just fashion, but every industry, said Rishi Garg, a partner with Menlo Park-based venture capital firm Mayfield. As every company becomes a big data company, customers will start to expect those capabilities.
“It’s definitely a trend and something that we’re going to see more of,” Garg said.
Stitch Fix isn’t the only company that provides personalized style delivered. Chicago-based Trunk Club offers a similar service. So does New York-based Bombfell, a fashion delivery service for men that mines users’ Facebook, Twitter and LinkedIn pages for clues about their personal style.
All of those companies also play into the broader delivery craze sweeping the nation, especially targeting millennials who now can opt to have everything from groceries to eyeglasses to birth control arrive at their door. Companies that offer those services recognize something unpleasant about the retail experience — namely that it can be tedious and repetitive, Garg said.
“It reflects a desire to evolve what these retail experiences are like,” he said, “and make them more comfortable.”
While the convenience of on-demand delivery makes services like Stitch Fix increasingly popular, it comes at a cost to traditional brick-and-mortar retail stores. In recent years, traditional retailers like J.C. Penney, Macy’s and Nordstrom have struggled amid growing competition from the likes of Stitch Fix.
The old-line retailers “are taking a hit,” said Marshal Cohen, chief industry analyst of The NPD Group, who specializes in retail. “It has everything to do with the fact that fashion is lacking innovation.”
Some retail stores are fighting back with high-tech solutions of their own, such as Lucky Brand, which installed smart fitting rooms in some locations that suggest clothes for shoppers and help them find items in the correct size.
There’s an inherent sacrifice consumers face when they eschew a store in favor of delivery services, Cohen said.
“We lose the art of shopping,” he said. “We lose the art of personalization.”
Instead of crafting an individual style, shoppers rely on an algorithm or personal shopper to do it for them. And there’s always the risk that the algorithm will get it wrong, leaving the customer with piles of clothes he or she doesn’t want and a hefty delivery fee, Cohen said.
Stitch Fix agrees it’s essential to get the matching right. If it’s off, the company loses a customer and also loses money on shipping the return and on the cost of inventory while the item is out.
“We have to be very confident in our selections,” Colson said. “Because if we get it wrong, we’re going to be paying a lot.”
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