[Corrected 7/28/16 9:59 pm. See below.] Joy Tang knows models—both the algorithmic ones she helped develop while working in high-frequency stock trading for six years, and the human ones who grace magazine pages and strut along runways at fashion shows.
Tang is the co-founder and CEO of Markable, a Madison, WI-based startup whose mobile app helps users find and purchase garments and fashion accessories similar to ones they’ve seen in pictures or in person.
The startup fits into a couple of themes emerging in technology and business: the spread of artificial intelligence-related software to more sectors, and efforts by retailers and brands to find new ways to capture sales through mobile devices.
It’s early, but investors see promise in Markable’s approach. The company has raised more than $1.9 million in equity funding from five investors, according to a regulatory filing that was made public on Wednesday.
Tang says that her company will use some of the money to further develop its software, which she says uses A.I. and deep learning technologies to identify attributes of items in images. The financing will also help support sales and marketing efforts, Tang says.
One participant in the funding round, which Markable is calling “pre-Series A,” is Sheng Fu. He’s the CEO of China-based Cheetah Mobile (NYSE: [[ticker:CMCM]]) and first heard about Markable when the startup appeared on the Chinese television show “I am Unicorn.” The show is similar to “Shark Tank,” a program on the ABC network where entrepreneurs pitch their ideas to investors, sometimes resulting in a deal. Fu is now on Markable’s board of directors, according to the regulatory filing.
After graduating from MIT in 2007, Tang took a job in Chicago, where she worked to fine-tune stock trading algorithms.
She says that in early 2014, she decided to strike out on her own and launch Markable because she saw algorithms and deep learning concepts being used frequently in many different industries, but fashion was not one of them.
“I saw the vacancy in the fashion visual sector,” Tang says. “The concept is out there, but nobody really has made it [work]. At the beginning, it was simply curiosity just to try it and see if it works. Now we know [it does].”
Tang says that Markable’s database, which the company aims to make the world’s largest that’s specific to fashion, comprises some 40 million products from more than 800 brands.
The app can visually recognize things like item type, color, fabric, and sleeve length. It then displays garments that meet those criteria, and allows users to make purchases from within the app. Markable receives a 5 to 25 percent commission on transactions it helps facilitate, says JJ Pagac, the company’s director of marketing and public relations. [An earlier version of this paragraph said that Markable’s minimum commission on purchases is 10 percent. It is actually 5 percent.]
Tang says that since the app became available for iOS devices in May, users have ordered about $16,000 worth of clothing with it. Markable plans to make a version of the app that’s compatible with Android devices in the future, says Alex Suprise, the company’s strategic counsel.
Markable, which was originally based in Chicago but has since moved its legal address to Madison, has about 11 full-time employees, Tang says. She says the plan is for the startup’s technical team to remain in Chicago, while she and several others will continue to work from 100state, a coworking space in downtown Madison. (Tang’s husband is a resident physician at the University of Wisconsin Hospital and Clinics.)
Tang says that the idea isn’t for the app to identify the exact brand of a given piece of clothing. Instead, it could, for instance, be used by a woman who sees someone wearing a high-end item in a publication or on her social media feed, and wants to find a cheaper look-alike.
“We did user experience testing and realized that people are not actually as brand-conscious as they are when they are doing online shopping,” Tang says.
Markable’s users are close to evenly divided between genders, and the app is most popular among people ages 25 to 35, Suprise says.
