The stylists who are training bots to be stylists
They help clients by learning about them and what they buy
Can’t decide what to wear?
Uniqlo, the Japanese fast-fashion chain, has a solution: A chatbot that gives clothing recommendations based on human input, as well as your purchasing history and … your horoscope.
The technology, which has been years in the making, is just one example of the extremes retailers are going to as they try to build computer algorithms that can intuit the intangibles of fashion.
“Instead of making something that’s purely mechanical — you bought this last month, so you might like this — we’re infusing humanity into the process,” said Rei Inamoto, founder of Inamoto & Co., the firm behind Uniqlo’s technology. “When somebody asks, ‘What should I wear?’ they’re looking for a personalized answer.”
As retailers race to offer customization and convenience, they increasingly turn to stylists and personal shoppers to win over consumers and to help fine-tune algorithms that might give them an edge in the $3-trillion (U.S.) global fashion industry.
Stitch Fix, the online styling-subscription service, has assembled about 3,700 remote stylists — from stay-at-home moms to full-time lawyers who fancy themselves fashionistas — to select clients’ outfits based on a combination of sales data, artificial intelligence and their own taste. (The pay: $15 an hour.)
Meanwhile, tech giant Amazon has hired dozens of fashion designers, photo editors and retail workers in recent years to help shape its proprietary software. The company’s researchers have also developed an algorithm that analyzes images of clothing and then designs similar items, according to an MIT Technology Review report.
“Companies are realizing that you can squeeze even more juice out of the orange if you combine data analytics with the human stylists,” said Wendy Liebmann, chief executive of consulting firm WSL Strategic Retail. “We all know that artificial intelligence is a valuable tool, but it so often misses the nuances.”
Sarah is in her mid-30s, lives in Massachusetts and works in client services.
She’s looking for summer workwear that can transition into the fall.
She likes: Polka dots, floral and lace. She dislikes: Stripes, jackets and black.
Rachel Gee, a preschool teacher-turned-Stitch Fix stylist, knew all of this the moment she glanced at Sarah’s profile.
The company’s algorithms have distilled Sarah’s body measurements and clothing preferences (which she provided when she signed up for the service), as well as three years worth of purchases, into easy-to-read data points. Sarah has long legs and a short torso, and she tends to spend $50 to $100 per item.
Gee scrolled through her client’s Pinterest page, which is full of bohemian styles, embroidered details and geometric prints, then checked her Twitter and Instagram accounts.
“I can see she’s very romantic and edgy, stylewise,” Gee said.
“She’s outdoorsy and has a casual vibe.
“I feel like I know her, like she’s my friend, almost.”
Now, Gee said, she was ready to pick five items to send to her client.
The algorithm’s top suggestion was a pair of distressed denim shorts. Not today, Gee said.
She sent Sarah a pair of shorts the week before, and, plus, Sarah was looking for officewear.
She found an olive green Calvin Klein dress with a subtle floral print.
The computer told her Sarah loves Calvin Klein and predicted a 51 per cent success rate. “We’re more than halfway there,” Gee said.
“That’s a pretty high probability that she’s going to keep that dress.”
She picked four more items: A navy pencil skirt, a magenta Calvin Klein blouse, an offwhite knit blouse and a “fun statement necklace” with stones.
Each item cost between $50 and $100.
“This whole process is like a partnership between me and the data,” said Gee, 29, who lives in San Francisco and now works full time for Stitch Fix.
Stitch Fix now has 3,700 stylists, but five years ago it had just 100.
Executives say they look for workers with a background in fashion, styling, customer service or retail.
“As we learn more about each client over time, both our algorithms and stylists become more accurate,” said Meredith Dunn, the company’s vice-president of styling and client experience.
“Our stylists read and digest feedback from clients and our algorithms ingest that data, too.”
Some in the industry, though, say the model isn’t sustainable.
Working with a personal stylist at Bergdorf Goodman or Saks Fifth Avenue is one thing; relying on machine-learning and stylists in far-off cubicles is another, and it seems like a stretch, said Milton Pedraza, chief executive of the Luxury Institute, a market research firm in New York.
“Algorithms and one-size-fitsall stylists keep costs down, but it doesn’t mean that they’re particularly good matchmakers or can understand tastes and lifestyle,” Pedraza said.
“Having a stylist is about creating a personal relationship, and that just doesn’t happen if someone is styling you from a computer on the other side of the country.”
Andrea Alder was a year out of fashion school when an Amazon recruiter approached her with a top-secret job offer: To train the company’s machines to become arbiters of style.
When her contract ended last summer, she got a job as an editorial stylist for the e-commerce site Zulily. She also works as a personal stylist for private clients. Working at Amazon “made me excited for the future of technology,” she said. “But it also made me realize that I’d rather do more hands-on work.”