Nips, tucks, and tech: The next wave of fashion is all about the algorithmic fit
The next wave of online fashion is all about the algorithmic fit.
At least that's what the founders of a handful of new clothing startups are hoping. In the last two years, roughly thirteen such companies have formed under a deceptively simple premise: Custom-sized clothes for the masses.
Some target men's suits, others make bras for women, still others focus on building the perfect t-shirt. But they all have one thing in common: They're trying to democratize tailoring so the world's less wealthy can afford it.
What's compelling about this new business model is what's happening behind the scenes. Data analytics and manufacturing technology have developed to the point where, for the first time ever, it might be possible to achieve the seeming contradiction of customization for the masses.
Roughly $70 million in venture investment has been sunk into this nascent space. See below for an overview of the major players and a breakdown of how many custom fit companies are in each retail sector.
Margins in e-commerce are notoriously slim and this new business model remains untested.
“No one has ever done this before so it’s not like there’s operational models where you can say, ‘Aha! What is the demand, how often will they order that,” says Patrick Chung, venture partner at New Enterprise Associates.
Chung led the firm's investment in a lingerie company called ThirdLove, which offers 30 bra sizes, including half cups, to fit a wider range of women. In one of the weirder technological twists of this genre, ThirdLove customers get their measurements by taking chest selfies. The iPhone app analyzes the pictures to deduce a woman's bra size. It's the sort of technology you'd imagine dreamed up by former tech employees turned fashion execs, and that's exactly what Heidi Zak and Dave Spector, co-founders of ThirdLove, are.
Half cups for the perfect fitting bra sounds like a great idea, but imagine manufacturing that many sizes. What a monstrous undertaking, with money likely disappearing into the ether on every sale.
“We’re not at scale so of course our product margins aren’t going to be as good as Victoria’s Secret," Zak admits. "A lot of it is a volume game.” Over time, the hope is that ThirdLove will collect enough data about its customers that it can optimize its manufacturing.
ThirdLove’s competitor, a lingerie startup called True&Co, takes a different approach. Women fill out a long survey about the shape of their breasts, answering rather intimate questions like ‘What is your shape?” and “How do your breasts rest in your bra?” The answers are fed through an algorithm, allegedly built using millions of data points from other consumers, to determine what bra brand and size are best for one particular woman.
Lingerie has been an obvious first target for custom fit in women’s clothes, because most women stockpile a bra that fits.
In men’s apparel, on the other hand, shirts and suits win the day. Some companies, like Trumaker, actually send “outfitters” to people’s homes to fit them for button down shirts. Others, like Arden Reed, have pop up shops or trucks that consumers can visit to be measured. In the t-shirt department, there’s a range of companies taking the mass sizing approach, using data analysis to create 30 or more sizes of a shirt, that vary based on arm, torso, belly, and chest circumference.
The real challenge in such an endeavor is scaling the manufacturing process. But like any industry, manufacturing has gotten much more efficient in the last decade. There’s new technology for tracking garments and different methods for scanning products. As for predicting supply and demand? Well, the founders and investors say that will come with time.
“If you fast forward in this company [ThirdLove] in another two years, five years, certainly ten years, by that time you have so much data about how sales have gone that the prediction will get better and better and better,” Chung says.
Despite the risks of the unproven "customization for the masses" model, investors have taken the plunge in backing these early companies. They believe, it would seem, that there's money to be made.
After all, custom-fitted clothing solves the number one challenge of apparel e- commerce sales, says Scott Jacobson, managing director at Madrona Venture Group. He’s an investor in suit company Indochino — one of the oldest and biggest custom clothing startups.
“It’s not like the idea of making custom apparel is a new one, but it’s new as it relates to building a new, scalable, online-first type of business,” he says. “The way they mass produce clothes today is the same way they mass produced clothes fifty years ago."
Jacobson points out that apparel is the largest retail category in the world, but because customers don’t want to order something without testing the fit, it’s difficult to convince them to buy through e-commerce. Compared to sectors like books and home appliances, only a small percentage of apparel is sold online. Looking at that gap, he sees opportunity.
“As an investor you look at places where technology can be applied to solve an interesting problem,” Jacobson says. “People want clothes that fit them and look good on them with regardless of body shape.”
Despite their relative diminutive size, these companies haven’t gone completely unnoticed. Victoria’s Secret is already looking over its shoulder, and rolled out its own data quiz for custom sizing a few months ago. It’s nearly identical to True&Co’s.
[illustration by Brad Jonas for Pando]