How This DTC Fashion Brand Achieved 99 Percent Fit Accuracy

A tool that helps online shoppers find styles that suit them is a kind of fashion holy grail – a tool that promises to reduce costly returns, increase profit margins and provide a better customer experience.

But even in the age of artificial intelligence, fitting in is a tough nut to crack.

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Now, developer of fit technology and direct-to-consumer brand Offer Laws is drawing attention to bold demand — the company says its native AI-powered fit predictions have achieved 99 percent accuracy. Laws of Motion and its founder, chief executive officer Carly Bigi, are riding that result into a new business, with new funding, to bring the technology to other brands.

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

Laws of Motion is not a fashion company that necessarily created its own fitting technology. This was a technology company that needed to test and learn, so it created a clothing brand to act as a real-world laboratory, where it could develop and iterate on its technology.

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

When it comes to data collection, method matters.

As a technology-driven direct-to-consumer brand that offers customized fashion, the company has no inventory, but produces fashions based on predictive fit. Customers fill out a quiz or upload a few selfies to get started and can also input their measurements, if they know them. Offering options is beneficial, as people can choose the method of dressing that is most comfortable for them.

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The Laws of Motion fitting feature starts with a quiz, uploading two selfies or manual entry of measurements.

The company noted that people aged 45 and under prefer the body scan. Those between 45 and 60 flock to the fit quiz, and the 60-plus “know their measurements to, like, an eighth of an inch, which I’m so impressed with,” said Bigi. “So for brands that serve a broad customer demographic, they need to be able to meet a customer where they are, in terms of their comfort and use of technology.”

The AI ​​model takes it from there to predict the size, and then the company adapts the garment. First, that was the Alfa, a classic sheath dress with simple lines. Any adjustments to the technology are based on customer feedback and other information, such as returns.

This process is crucial, and multiplied throughout the customer base and product catalog – which now includes different dresses, pants, blouses, jumpsuits and even bridal – it enables the system to be improved quickly and constantly. “It gave us that precision feedback loop that you wouldn’t have if you were creating the technology in a silo and then licensing it,” she said.

That describes many, if not most, developers and third-party platforms working in suitable technology. The obvious exceptions are Stitch Fix and Amazon and neither of them pin their accuracy to a specific percentage. But the stakes are high. According to Statista, about 16.5 percent of the $1.3 trillion in goods sold online in the US in 2022 were returned.

Because of the situation, the attitude that demands near-perfect accuracy of Laws of Motion is greater. But according to the CEO, she has the receipts – literally. Because the figure comes directly from the clothing brand’s real-world performance and, she said, checking it against the company’s reference data is a validating metric.

It also explains how the brand has pulled off a return rate of under 1 per cent and customer retention of 86 per cent.

“If you answer our quiz or upload some photos, our predicted body measurements for you, the customer, will be within 99 percent of your body’s accuracy,” she said.

Laws of Motion in Motion

As part of the results, Laws of Motion is kicking into high gear.

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

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The company offers a dashboard, so brands can see the impact of appropriate technology on conversion, returns, revenue, average order values ​​and more in real time.

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

What she has achieved so far is amazing, especially for someone without a fashion background. There’s 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 fresh thinking to the problem. That’s pretty clear in everything from her technological approach to her fees.

Basically, Bid Laws, as a platform, only makes profits when their partners make money.

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

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

Now that she’s a new inductee on the Inc. Women Founders list. Magazine, Bigi might feel more at home hitting the venture capital circuit lately. It’s not the first time. She dipped her toe in pre-seed funding — more for networking than fundraising, she said — and pulled in $1.5 million from investors like Jenny Fleiss, co-founder of Rent the Runway and Columbia’s Lang Fund.

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The selfie capture tool through the mobile app.

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

For Sam Yagan, co-founder and managing director of Corazon, Laws of Motion ended the rust of skepticism he had developed over the years about suitable technology.

He may be known as the co-founder of OkCupid or for his time at, but Yagan was the CEO of ShopRunner from 2016 to 2021. sizing challenge.

“I showed up at all the conferences and NRF and Shoptalk and everything, and…there are a gazillion suitable solutions,” he told WWD. “During the four years I spent in the industry. I hate every suitable solution I’ve seen.”

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

“I remember when I was introduced to Carly. I almost didn’t accept the meeting,” he said. “And of course, they had AI, and it was like, ‘Oh, my God, that makes me even slower.'” But her return rate blew me away, and if she could reduce that significantly for other brands too, that would be “crazy,” he said.

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

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