“What Size Am I?”: Clothes Horse Takes On Fashion’s Most Awkward Question

The three-year-old startup has developed a front-end interface for helping web shoppers find the perfect fit.


A woman shopping for summer clothes spots a dress on Pinterest and clicks through to the retailer’s product page. She zooms in on the pattern, selects the coral version, and decides the price is within her budget–but then, she hesitates.


For most online shoppers, that moment of hesitation is the result of inconsistent sizing, a problem costing the fashion industry over $3 billion per year.

Enter Clothes Horse, which aims to eliminate the uncertainty that stands between a shopper’s interest and the checkout. The three-year-old startup works with retailers to recommend a size based on a shopper’s measurements and favorite wardrobe staple. This week, Clothes Horses completes the inaugural New York Fashion Tech Lab, an accelerator that pairs fashion tech companies with industry experts.

“There was a fair bit of skepticism when we started that this problem could be solved with a simple front-end [interface],” says CEO and cofounder David Whittemore.

On product pages with the technology installed, users click “What size am I?” and complete the Clothes Horse survey. “Your perfect fit in 20 seconds,” the pop-up proclaims (no mobile integration, as yet). The colors and fonts of the interface vary by retailer, but the survey is cleanly laid out, with accessible language and visual cues that encourage shoppers to finish the steps. On Anthropologie’s website, it took me slightly longer than 20 seconds to enter my height, weight, and bra size, and then select the brand and size of the best-fitting dress in my closet. But Clothes Horse had my information stored and ready when I visited Nicole Miller’s website a few minutes later.

As Whittemore and his team iterated on designing the interface, they made a surprising discovery: Asking the right questions in the right way solved only half of the problem. Just as important, if not more so, was providing shoppers with a fit description as well as with a recommended size.


“We kept hearing about not just which size to get, but how is it going to fit me,” he says. “Now, if it’s a loose skirt, we’re going to say that. We discovered that that’s really what gives the shopper the confidence to move forward.”

A quick glance at the online retail landscape reveals the extent of inconsistent sizing’s impact. Indeed, many of e-commerce’s standard practices and innovative ideas are arguably workarounds for this underlying issue. Free returns? A way to ease the pain of ordering multiple options, with the intention of keeping just one or two. Free second sizes? A must-have feature for Rent the Runway, which promises to help women make a one-time style statement at a specific event. Personal shopping startups like Trunk Club? A way to try a “trunkful” of stylist-selected items and keep only what fits.

Whittemore says that on average Clothes Horse boosts sales by 8% and reduces returns by 9.5%. On product pages with the technology installed, 15% to 20% of shoppers click the survey.

Yet Clothes Horse is no panacea, and the experience may not always be so seamless: When I took the survey on, I happened to have picked a best-fitting dress from Club Monaco, a brand that both Anthropologie and Nicole Miller have approved as comparable. For retailers without overlapping comps, I would have had to complete the survey a second time.

“Anthropologie has a say in which [comps] appear on their site. It’s a delicate question,” says Whittemore, adding that the ever-growing Clothes Horse database includes sizing information for over 600 brands. “Every time a shopper enters information, we’re learning from that and getting smarter.”


And making money. Clothes Horse charges a retailers a flat percentage of the incremental revenue generated by its technology. So far, partners include Blue Fly, Frank & Oak, and J. Lindeberg.

Whittemore is hopeful that relationships established through the New York Fashion Tech Lab program will lead to additional deals with multi-brand customers. Back in 2012, his team participated in DreamIt Ventures’ incubator program; only recently, he argues, have those larger retailers developed enough comfort with technology to experiment. “We’re at an inflection point right now,” he says.

Competitors like Metail, which creates 3-D “virtual” models based on a shoppers’ measurements, are also hoping that retailers are ready to innovate. But for now, the low-key design of Clothes Horse may be a better fit for an industry still stuck in a catalog mindset.

About the author

Senior Writer Ainsley Harris joined Fast Company in 2014. Follow her on Twitter at @ainsleyoc.