For Le Tote’s first design collaboration, with model Olivia Culpo, the production process was a delicate balance of mining customer data to make decisions and trusting Culpo’s subjective style.
The collection resulted in items more fashion-forward than Le Tote’s typical selection, while still fitting with the subscription company’s core of affordable workwear: a reversible bomber jacket, a frilled leather skirt and a variety of printed blouses. While the company’s e-commerce site is usually only accessible to its members, Le Tote made this collection available for anyone to shop, as a way to capitalize off the buzzy collaboration.
Five years after it was founded, Le Tote is edging into a brand-building strategy that includes Culpo and other influencers. Its business model earned an early reputation in fashion-tech media as the “Netflix for fashion”: Members pay a flat fee for a monthly shipment of clothing and accessories they can wear for a month and return, or purchase at a special price. In 2016, Le Tote shipped $100 million worth of clothing, and Rakesh Tondon, Le Tote’s CEO and co-founder, said business has grown six times its size over the last three years. So far, the company has raised $53 million in funding.
With a steady membership base, Le Tote is looking to grow and position itself as one of the prominent startups transitioning consumers’ closets to the sharing economy. The space is currently dominated by Rent the Runway, which launched its unlimited everyday clothing rental service in 2016, when it reportedly brought in $121 million in overall revenue. Gwynnie Bee offers a similar business model for plus-size fashion. Other “unlimited-closet-in-the-cloud” startups promising to eliminate the need for shopping altogether include Parcel22 and The Ms.
Le Tote also needs to win over customers from another subset of similarly structured businesses: Stitch Fix (set to become a $1 billion company this year), MM LaFleur, Trunk Club and Dia & Co all ship personalized style boxes to customers for potential purchase based on data and algorithms. They’re for customers who want clothing options delivered at home, without a monthly subscription or needing to come to terms with the idea of renting everyday clothing.
In the race to create the best revolving wardrobe for time-strapped women, Le Tote has built an in-house design team to make affordable items corresponding to customer feedback, which now accounts for 50 percent of its inventory. The other half is provided by brands including Vince Camuto, Nine West and French Collection, which cut prices for Le Tote members in exchange for the vast amounts of feedback and customer insight the company collects on each monthly shipment.
Each data point Le Tote collects is fed to its design team, made up of 12 people. Data collection starts as soon as someone joins the service and is asked about the style of tops, pants and dresses they prefer, and continues as they browse the site and build a “closet” by favoriting items. Tondon said that, for each item added to someone’s online closet, about 80 extra data points are generated in the form of related product traits. (If someone favorites a sleeveless A-line dress in a floral pattern, for instance, there are thousands of other items in the inventory with at least one corresponding attribute.)
After boxes are shipped, Le Tote uses machine learning to digest the written commentary left by members, in response to pointed feedback questions like, “What did you like about the fit?”
“After we collect all of this data, we can go back to our own collections and make tweaks and changes, and design new products immediately, while knowing exactly what demographic each addition will appeal to,” said Tondon. He provided the example of jumpsuits, which are often trending on the site but aren’t purchased regularly because of difficulties in fit. After listening to where those fit problems happen — in the length or size of the bust, for instance — it designed its own jumpsuits, hoping to solve common issues.
Customer data is used similarly by the merchandising team, who reports back to brand partners with very specific ideas of what their members are responding to. In turn, brands can take that feedback into consideration for their own production: French Collection tweaked its sizing model for dresses after learning that Le Tote customers responded better to things sized on the small-to-large scale, rather than numerically.
As a result of this data-driven production and merchandising, Le Tote reports a customer retention rate of 92 percent. And, in an effort to reach outside of the pockets of its current members, the door is open for anyone to shop the new collection with Olivia Culpo.
“People still aren’t used to a service like this,” said Tondon. “There’s an education we need to get through. But now that we have more awareness in the market, we’re thinking more of branding opportunities. We plan to do more collaborations like this in the future.”