You will be redirected back to your article in seconds
Skip to main content

Fit:Match Takes Netflix-Style Approach to Pairing Consumers With Clothing

Shoppers looking to forgo the fitting room process as they return to the mall may be in luck, especially if they were already a stickler for sizing. Fit:Match, a platform that performs a 3D body scan designed to capture 150 data points within 10 seconds to determine the optimal apparel fit for shoppers, is bringing a studio experience to three Brookfield malls by fall.

The companies will officially launch the contactless Fit:Match Studio in three shopping centers, beginning with a 778-square-foot space in the Chicago-area Oakbrook Center in mid-August, followed by the Glendale Galleria in suburban Los Angeles and Stonebriar Centre outside Dallas in mid-September. Fit:Match has not yet disclosed which individual retailers are participating.

The technology is designed specifically for the “fit first, style second” apparel shopper, according to Haniff Brown, founder and CEO of Fit:Match. To get “fitched” and receive a Fitch ID, shoppers first answers a list of questions on their mobile phone, providing their name, social media handles and fit preferences. After being scanned by the Fit:Match technology in the studio, the shopper can click a link to start reviewing their personalized assortment of apparel matches.

“We can tell a shopper who is 5’5” how she compares to other shoppers in our database who are also 5’5”,” Brown told Sourcing Journal. “We can identify if they have longer legs than the average shopper or a longer torso, and then identify if wearing a jumpsuit would be an inevitable challenge for them. People often know when they have fit problems, but they don’t understand why. So a big part of our data exchange with the customer is instantly educating them with fit, and supplying them with that data instantaneously so that can start shopping their matches on the spot.”

Related Stories

The Fit:Match algorithm assigns a relevancy score to each user for each apparel item based on numerous factors, including the Fitch ID, data from brands’ tech packs and specifications such as fabric type and stretch. The platform is programmed to generate more accurate results over time as it learns more about the user’s fit and style preferences. The scans are synced with the inventory at each of the company’s retailer partners to show the person items he or she might like based on fit, and hides inventory that the algorithm says doesn’t fit.

“Our vision here is that apparel hasn’t evolved,” Brown said. “When you look at the customer today, they are presented with unique experiences—your Netflix account looks completely different than mine because we have different preferences. We believe apparel should be the same way. When you go to Nike.com your Nike experience should look and feel unique to you. You shouldn’t see products at all that aren’t fits for you. That’s just a big no-no going forward.”

Although Fit:Match seems like a perfect fit for the COVID-19 apparel shopping era, the company actually got its platform off the ground well before the pandemic’s start.

Fit:Match first trialed two pilots in Miami, as well as a popup studio at Brookfield’s Baybrook Mall in Houston last November. While Brookfield had already committed to bring Fit:Match beyond these initial locations, the mall operator was impressed by the metrics that the experience delivered. Brown said participation rates of those who walked into the studio reached 80 percent, with nearly 4,000 shoppers getting “fitched” over a three-month period, without any advertising.

“We showed that to Brookfield and said, ‘We sliced through the data and we’re not seeing it concentrated. We’re seeing it broadly being an appealing concept across sizes, demographics and age groups. We know this concept can travel, and we want to do it at your top locations,’” said Brown. “They were very supportive from the start. They understand that companies that will win over the next decade will leverage sophisticated data.”

Consumer feedback was overwhelmingly positive as well, according to Fit:Match, with the experience generating a Net Promoter Score of 90 percent. The average participant is approximately 26 years old, but so far shoppers as young as 16 and as old as 80 have taken a turn in the scanning studio.

Fit:Match also is talking to “a handful” of retailers to prep for a potential fall launch, which would help the company initiate broader experiences such as having a shopper immediately buy and pick up clothes in the mall.

“We actually tell you which retailer in the mall to pick up something from and the exact SKU to do that,” Brown said. “You literally walk up to that store and its ready and waiting for you to pick up like curbside. That’s what we’re really excited about rolling out. The goal is to offer that service where we could be the first stop in their shopping journey, but also make it very convenient for you to pick up items and casually browse around more seamlessly.”

The technology could be a solution to a major problem for apparel retailers that have been reopening their stores. Overall, 65 percent of women said they would not feel safe trying on clothes in dressing rooms, according to an April survey from First Insight. Fifty-four percent of men said the same.

Tech providers have taken extra steps to alleviate apparel try-on fears amid the pandemic. Checkpoint Systems released Inventory Quarantine (IQ), a Software-as-a-Service solution that allows retailers to assign returned stock to an automated quarantine “holding area” for a number of hours, removing items from visibility to customers both online and in stores.

And solutions providers like Bold Metrics and MySizeID enable consumers to discover their body fit measurements—the first solution uses a quiz and the second offers mobile scanning—which can then be matched with a brand-specific apparel item in their size.