Recently news broke that eBay had acquired PhiSix, a startup that develops fit technology for clothing, in an effort to give shoppers another way to discern how an item will look on them when they’re shopping online.
Taking into account a material’s stretch, fabric and sheen, PhiSix generates simulations of clothing on the human form, including a realistic 3D rendering that shows wrinkles and a heat map marking where different sizes will fit more snugly on the body.
For retailers, the potential benefits of adding fit technology onto their e-commerce platform are clear. It could help consumers buy with more confidence – although that has hardly prevented e-commerce from reaching the scale it’s at today – and it could curb monetary losses from returns. Free returns have in many ways come to be expected and are increasingly necessary for retailers to stay competitive. So getting customers to buy fewer sizes and nail it on the first try is a big motivator.
But as eBay Head of Retail Innovation Rob Veres points out, no one technology is a silver bullet at this point. Fit tech startups approach the sizing question in different ways. Clothes Horse, which works with over 30 retailers including Frank & Oak and Nicole Miller, gathers data on the size discrepancies between brands to recommend to users which size to buy.
Like Clothes Horse, the startup True Fit eschews simulations in favor of offering up sizing recommendations powered by machine learning algorithms. Body scanning is another approach to sizing: with a photo taken from the front and side of a person’s body, it can generate hundreds of data points on a person’s sizing.
True Fit came to market in late 2011 and launched with Macy’s and Nordstrom. At this point the startup works with 15 retailers, which co-founder Jessica Murphy estimates will double by the end of the year. True Fit also incorporates shoppers’ clothing preferences into its system, looking at their purchase history to figure out what fit they like best and then augments that data with return history and any information that the user manually inputs during onboarding.
“[Preference] is a huge part of getting it right. Two customers can have the same measurements,” she says. “One likes [clothing] form-fitting, another likes it loose.”
Individualized fit recommendations are particularly useful as compared to to user-generated reviews, Clothes Horse founder Vik Venkatraman argues. Shoppers have learned to be skeptical of those reviews, since they might be coming from people with completely different body types.
“I think that all the major players that don’t have a product… are going to have to pick one up,” Venkatraman says.
As it stands, technology like that employed by Clothes Horse and True Fit may be the most easily digestible to users. Simulations are good, but as Andrea Marron, Nicole Miller’s director of e-commerce and retail, points out, many still give the clothing a rubberized look. When fashion is so much about buying a dream, 3-D renderings aren’t exactly inspiring. A widget that tells users to buy a size up or down intrudes less on that experience.
One company that may have hit the nail on the head is Rent the Runway. The dress rental site serves up user-generated reviews with each look, which include the reviewer’s size and a picture of her wearing the garment. If the shopper already has a profile on the site, Rent the Runway floats to the top reviewers who have a similar body type.
It’s an effective strategy, but it’s not for everyone. Marron says her team considered a similar approach at Nicole Miller , but it was eventually nixed in favor of traditional model photos in order to keep things “aspirational.”
Instead, Nicole Miller uses Clothes Horse and has seen a 15 percent reduction on its return rate since incorporating the service two years ago. Although many fit tech startups also claim improved conversion rates, Marron says she has not seen a significant change on that front.
For PhiSix, the question now is how to present the technology to consumers in a way that’s easily understandable, founder Jonathan Su says. People may not be able to digest a heat map, he says, so the key will be delivering that information in an actionable way. The eBay/PhiSix integration will be launching in the next few months, and given eBay’s resources, we’ll be interested to see what they turn out. It’s clear that they see PhiSix as a long-term investment.
As Veres says: “We’re not going to put something out there to say we did it.”