Camping is one of the most popular leisure activities in the U.S.; in fact, American families spend up to 534.9 million days camping in any given year. For one young woman, however, a camping trip meant more than just a rustic getaway; it involved an epiphany that would change the world of online retail as we know it.
After graduating from Stanford and getting her M.B.A. at Harvard, Katrina Lake found herself working at a marketing firm, managing retail client accounts. And while she excelled at her job, Lake realized that if wanted to join the company of her dreams, she would have to create it herself.
Then Lake had an stroke of genius.
While planning a camping trip to a remote area of Northern California, Lake found herself shopping for a tent. But in her search for the perfect tent, she found herself at a loss.
“It was so very frustrating. I went online to research tents. There are thousands of them! I read all the reviews, looked at pricing and attributes and felt I shouldn’t have to become an expert on camping tents to make this purchasing decision. There are other people out there who are experts.”
Meanwhile, Lake had been enlisting in her sister’s help to shop for her; after all, she didn’t have time to shop and her sibling had a better eye for fashion than she did. It was suddenly very easy for Lake to make a connection to her camping dilemma — she needed an expert to help her navigate the world of tent retail.
“That was it,” Lake said. “After all the consulting work I’d been doing in retail, I knew that was the missing piece. I got an epiphany which gave me the spark to Stitch Fix: marrying experts (stylists) with customers who want to buy something.”
Thus Stitch Fix, which can be described as a hybrid of custom retail and Netflix-style algorithms, was born. The services uses data science to match women with the perfect clothing.
Here’s how it works: after filling out a profile and paying a $20 styling fee, the customer receives five articles of clothing, along with a card from a personalized stylist that gives advice on how the pieces should be mixed and matched. From there, the customer decides which pieces they want to keep, and which to return, giving as much feedback as possible in the process.
From there, data scientists get to work, creating an entirely new retail model based on science.
“I felt there was a real opportunity to apply data and technology to the fashion retail business,” Lake told PCMag. “To be honest, walking into Macy’s and buying something today is exactly the same as it has been for decades. I knew there was a better way to innovate, be customer-centric and nicely profitable.”