Buying Shoes? Digital Stylists Use A.I. to Suggest Clothing to Match

The black skirt had multiple personas. The fact that it was made of leather gave it an edgy vibe, but its A-line fit-and-flair cut was more flirty and feminine. “I fell in love with it,” says Michelle Bacharach, co-founder of FindMine. “But as soon as I brought it home, I wondered, ‘how do I wear this?’ ”

That question, along with a realization that she found herself asking it repeatedly over a variety of her purchases—from clothing items to housewares—led her to found FindMine, an e-commerce startup that uses machine learning and artificial intelligence to help shoppers find clothing items that can complete an outfit.

“I’m constantly having to do all this work after the purchase, or I end up not buying things I like because I don’t know how to wear it beyond one outfit,” Bacharach says.

The idea behind FindMine is to give shoppers recommendations—this blouse or pair of shoes would pair well with the black leather skirt—at the point of sale, when a customer could purchase multiple items, Bacharach says. “Once it’s in your closet it’s too late,” she adds.

For brands and retailers, getting these outfit suggestions to shoppers in the store can result in more spending than if a shopper were to buy only one item. For example, the e-commerce website for men’s fashion house John Varvatos, a FindMine customer, displays a dark gray suede jacket cut in a “military racer” style that sells for $798. Beneath it is a “complete this look” section which advises shoppers to pair the jacket with an azure button-down with subtle stripes, tuxedo-style pants, and a pair of chocolate-brown “Brooklyn lug lace” boots—all made by Varvatos.

Other customers include Adidas and American Eagle, which uses Facebook messenger to deliver FindMine’s clothing suggestions to customers, Bacharach says. She estimates that FindMine puts together 11 million outfits each day.

Stylist services make up a growing niche in e-commerce. Some startups such as Fitz focus on human stylists who come into a customer’s home to help analyze what you wear and why, and then reorganize the clothing and accessories that make the cut.

But others have concentrated on using technology to offer these services to a greater number of people more quickly. Stylistics has ClosetSpace , an app that is digitizing that process, giving customers outfit suggestions from their virtual closets and also from retailers’ items that they might want to buy.

Even e-commerce giant Amazon (NASDAQ: [[ticker:AMZN]]) is getting into the game with services like Spark, which is designed to help shoppers find compatible new products—from clothes to home decor to beauty and grooming.

“We all use these tools to help manage our lives: traveling, mobile banking,” says Brooklyn Decker, co-founder of stylist app Finery. “When you look at how women will spend more money on their clothing than on their education, there should be something to manage their clothing.”

Decker, an actress, started Finery last year with

Author: Angela Shah

Angela Shah was formerly the editor of Xconomy Texas. She has written about startups along a wide entrepreneurial spectrum, from Silicon Valley transplants to Austin transforming a once-sleepy university town in the '90s tech boom to 20-something women defying cultural norms as they seek to build vital IT infrastructure in a war-torn Afghanistan. As a foreign correspondent based in Dubai, her work appeared in The New York Times, TIME, Newsweek/Daily Beast and Forbes Asia. Before moving overseas, Shah was a staff writer and columnist with The Dallas Morning News and the Austin American-Statesman. She has a Bachelor's of Journalism from the University of Texas at Austin, and she is a 2007 Knight-Wallace Fellow at the University of Michigan. With the launch of Xconomy Texas, she's returned to her hometown of Houston.