How Laws of Motion’s Fit Tech Hit 99% Accuracy

A tool that can help online shoppers find styles that fit them is kind of a holy grail for fashion — one that promises to cut down on costly returns, boost profit margins and deliver a better experience to customers.

But even in the age of artificial intelligence, fit has been a tough nut to crack.

Now, fit tech developer and direct-to-consumer brand Laws of Motion is attracting attention for a bold claim — the company says its homegrown AI-powered fit predictions have reached 99 percent accuracy. Laws of Motion and its founder, chief executive officer Carla Bigi, are riding that result into a new business, with new funding, to bring the tech to other brands.

A Fashion Brand Built to Support the Tech (Not the Other Way Around)

Laws of Motion is not a fashion company that built its own fitting tech out of necessity. This is a tech company that needed to test and learn, so it created an apparel brand to serve as a real-world lab, where it could develop and iterate on its technology.

This is a distinction with a major difference, right down to the fundamentals — the way it trained its AI models. “We started with 10,000 bodies, which is about a million data points, in 2019,” Bigi told WWD. “And we’ve now amassed just over 2 billion data points of body measurements within our own direct-to-consumer brand.”

When it comes to data collection, the method matters.

As a tech-driven direct-to-consumer brand offering bespoke fashion, the company holds no inventory, but produces fashions based on fit predictions. Customers fill out a quiz or upload a couple of selfies to start and can also input their measurements, if they know them. There’s a benefit to offering options, because people can choose the mode of fitting that feels most comfortable for them.

The company noticed that people ages 45 and younger prefer the body scan. Those between 45 and 60 flock to the fit quiz, while the 60-plus set “know their measurements to, like, an eighth of an inch, which I’m just so impressed by,” Bigi said. “So for brands that are serving a wide demographic of customers, they have to be able to meet a customer where they are, in terms of their comfort and use of the technology.”

The AI model takes it from there to predict the size, and then the company tailors the garment. Initially, that was the Alpha, a classic sheath dress with simple lines. Any adjustments to the tech is based on customer feedback and other information, like returns.

This process is crucial, and multiplied across the customer base and product catalogue — which now includes different dresses, pants, blouses, jumpsuits and even bridal — it allows the system to quickly and constantly improve. “It has allowed us that feedback loop of accuracy that you wouldn’t otherwise have if you were just creating technology in a silo and then licensing it,” she said.

That describes many, if not most, third-party developers and platforms working in fit tech. The obvious exceptions are Stitch Fix and Amazon and neither of them peg their accuracy to a specific percentage. But the stakes are high. According to Statista, about 16.5 percent of the $1.3 trillion of goods sold online in the U.S. in 2022 ended up being returned.

The scenario makes Laws of Motion’s near-perfect accuracy claim seem all the more audacious. But according to the CEO, she has the receipts — literally. Because the figure comes directly from her apparel brand’s real-world performance and, she said, it’s a validated metric checked against the company’s reference data.

It also explains how the brand pulled off a sub-1 percent returns rate and customer retention of 86 percent.

“If you answer our quiz or upload some photos, the predicted body measurements that we have for you, as a customer, is going to be within 99 percent accuracy of the actual body,” she stated.

Laws of Motion Is in Motion

Emboldened by the results, Laws of Motion is kicking into high gear.

The company created a massive range of 1,260 “micro-sizes” and shapes based on its data and demand, from 00 to 40. Then in recent weeks, it just expanded into a new offering to partner with brands as a tech provider — which, again, was always the goal.

The first to sign up is Eddy, the bohemian womenswear brand founded by Megan Eddings Feely, formerly of Ralph Lauren and Tory Burch. Roughly a dozen others are in the process of inking deals, including some well-known contemporary and luxury brands, Bigi said. She couldn’t disclose specific names because the contracts were still out at press time.

What she has accomplished so far is impressive, particularly for someone without a fashion background. Therein lies the twist: Before launching Laws of Motion, Bigi was a Deloitte consultant with an MBA from Columbia Business School. But she saw a need and decided to bring some fresh thinking to the problem. That’s pretty clear in everything from her tech approach to her fees.

Essentially, Laws of Motion, as a platform, only profits when its partners make money.

“The pricing is structured so that we take a percentage of increased revenues from increased conversion for customers who use the technology,” she explained. “We also take a set percentage of savings from decreased returns for customers who use the technology.

“It’s important that we’re able to show in real time the impact that the technology is having, and that’s the first time that’s ever been done with a sizing solution.”

Now a newly minted inductee on Inc. Magazine’s Female Founders list, Bigi might have felt more at home hitting the venture capital circuit recently. It’s not her first time. She dipped a toe in pre-seed funding — more for the networking than fundraising, she said — and pulled in $1.5 million from investors like Jenny Fleiss, Rent the Runway’s cofounder and Columbia’s Lang Fund.

On Wednesday, the company revealed a $5 million Series A fundraising round that pulls in investors like Corazon Capital, Sequoia Capital’s The Scout Program, Leadout Capital and others from the tech and fashion sectors, including Eva Jeanbart-Lorenzotti, Raine Group’s senior consumer adviser and Irving Place Capital’s John Howard, who’s also a board member of Good American, Skims and Frame.

For Sam Yagan, Corazon’s cofounder and managing director, Laws of Motion blasted away the rust of skepticism that he’d developed over years about fit technology.

He may be known as the cofounder of OkCupid or for his stint at match.com, but Yagan was also CEO of ShopRunner from 2016 to 2021. Working with luxury brands and department stores, he saw firsthand how fashion and their tech partners whiffed on the sizing challenge.

“I showed up at all the conferences and NRF and Shoptalk and everything, and…there are a gazillion fit solutions,” he told WWD. “In the course of the four years I spent in the industry. I came to hate every fit solution I saw.”

To Yagan, they instill a false sense of security or accuracy that crumbles the moment the customer gets the look. It’s enough to stoke higher conversions, but that often came with high returns that wiped out the gains.

“I remember when I was introduced to Carly. I almost didn’t take the meeting,” he recounted. “And of course, they had AI, and it was like, ‘Oh, God, that makes me even more nauseous.’” But her return rate wowed him, and if she could drastically slash that down for other brands too, that would be “crazy,” he said.

There’s reason to believe she can, mainly because Bigi believes it — so much that she puts her money where her mouth is. “A lot of these guys want to get paid on conversion increases, because like I said, that’s easy. What’s really hard to deliver is reduced returns….I believe that this sort of performance-based pricing model is truly game-changing.”