Using Selfies to Lower Online Clothing Returns
It’s an Internet Age-old riddle: How do you know if clothing you buy online is going to fit and—more important—flatter you? Christian Wylonis wants to solve it with Fitbay, his Copenhagen-based startup, which matches you online with people of similar size and shape to see how clothing looks in real life. “It’s the missing social network,” says Wylonis, 30, who says his long torso makes it hard for him to find comfortable shirts. “We aim to become the Facebook of clothing.”
The global online market for apparel and footwear is poised to expand to $305 billion in 2018, from $128 billion last year, researcher Euromonitor International estimates. But returns from fickle shoppers are a growing headache for Web retailers. About 30 percent of clothing sold on the Web goes back to retailers, according to Clear Returns, a consultant in Glasgow, Scotland. Germany’s Zalando, Europe’s biggest Internet-only shoe and fashion store, says about half of the items it sells are returned.
At Fitbay, users enter their height, weight, and basic body shape—pear or apple; muscular or oval; long arms or short; etc. Shoppers are matched with others on the site with similar data. They are encouraged to post selfies wearing clothes they like to help their body doubles decide whether items they’re considering will fit.
Each user has a “Discover” page that includes pictures of merchandise from stores and photos of other people on the site wearing clothes they’ve bought that Fitbay’s algorithms predict she’ll like. These recommendations can be fine-tuned by filling out follow-up queries such as what size Gap T-shirt or Forever 21 maxi dress fits best. The company began working on a way to include bust sizes after some women were reluctant to share that information.
Fitbay is the latest in a long line of startups aiming to limit the toll of online-fitting flops. New York fashion technology company Clothes Horse correlates sizes across scores of retailers and makes suggestions based on what you say your favorite garments are. London’s Fits.me creates an avatar based on your measurements, which can show you how a shirt or dress might look on you. Virtusize in Stockholm lets consumers compare prospective purchases with clothes they already own; its system displays an image of a dress that a user is considering buying on top of a dress she already has to see how the two differ in cut. “The long-term vision is that everyone who shops for clothes online will have a Virtusize account,” says Chief Executive Officer Gustaf Tunhammar.
EBay in February acquired PhiSix, which makes 3D graphics of clothing to demonstrate fit. The online marketplace uses the software to show potential buyers an avatar wearing jeans from one of its vendors. EBay won’t say which clothing maker, because it wants to test how popular the feature is without giving the company a boost from curiosity seekers.
Fitbay, which has secured $2.4 million in financing, makes money when customers click through to a website and place an order. Since a trial version went live in February, nearly 100,000 users have signed up. The company says it has 4 million items in its database from more than 1,000 retailers, such as Uniqlo, Ralph Lauren, and J.Crew, offering sartorial solutions for everyone from beanpoles to the big-boned. Fitbay has “an innovative solution to a big problem in a big market,” says Martin Hauge, a general partner at Creandum, a venture capital firm in Stockholm that’s backing Fitbay and was an early investor in music streaming service Spotify. “This could be a winner and a billion-dollar company just like Spotify.”
Wylonis says Fitbay’s advantage is that its solution is based on shape rather than measurements, making it easy to sign up, as there’s no need to bring out the measuring tape. “Whoever solves this is going to be huge,” he says. “And I hope, and believe, it will be us. We’ve finally found a purpose for selfies.”
To continue reading this article you must be a Bloomberg Professional Service Subscriber.
If you believe that you may have received this message in error please let us know.