Founder Friday: How We Use Data at ThirdLove, with Heidi Zak
As a #ByWomenForWomen company, we love celebrating brands that are led by fellow female founders. Our new series, Founder Friday, is a chance to get to know some of these standout women, including our very own Heidi Zak!
If there’s one thing I’ve learned from starting ThirdLove, it’s that I have to focus on solving a problem for our customer while creating a better customer experience than what currently is offered.
We can’t always solve those problems by just relying on what we think or feel. My gut feeling is important, but it is not always right. So, we use data to inform any decisions we make, from the images we use in marketing campaigns to the colors we offer in new product lines.
When we first started ThirdLove, we put together focus groups with hundreds of women in San Francisco who came to our office, tried on prototype bras, and shared their experiences with us.
From these first focus groups, we were able to develop an algorithm that matched each woman with a size that best fits them. We noticed that a lot of the women in our focus groups were between cup sizes, as the algorithm was getting confused about whether to size up, or size down the cup size. We’d found our problem. So, we created half-cup sizing.
When we asked all the women who had been “in-betweeners” to come back to the office and try our new half-sizes, their reactions were amazing. I got to watch their faces light up because they had finally found a bra that really fit them for the first time in their life. That was the moment the light bulb really turned on, and we realized that if we just listened to the customer and focused on building better products to solve their problem, we’d be successful.
As we’ve grown, we’ve continued to collect data on our customers’ needs and issues through Fit Finder. Over 13 million women have completed the online quiz to date, and that provides us with more than 600 million data points that we continue to use for product development.
It’s really an amazing process when you break it down. A customer tells us about the fit issues she’s having with her current bras in an online quiz that takes about 60 seconds. At the end, we’re able to recommend a size and style for her based on her answers to questions about breast shape, current bra brand, what hook she wears that bra on and more. That information also goes back to our product team, and we are always looking at adding new questions to solve problems we may not have considered in the early days.
We don’t let return data go untapped either. Instead, we use that information to improve future product iterations. We look to see if a certain style, or a certain size in a style, has an above average return rate. For example, when we launched our Classic Strapless bra, we noticed an above average return rate for women who had purchased the bra in smaller cup sizes. We realized there was a design issue for women in a certain size range that needed to be addressed, so we went back and completely redesigned the bra. A few months later, the sizes were back on our site and now getting 5-star reviews!
When you see our data making a direct impact on a customer’s happiness, it really shows that using data isn’t cold or impersonal. It’s the best way to get to know our customers and figure out how we can give them exactly what they want — a perfectly fitting bra.