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Summary:

In order to remedy the pain of shopping for bras online, Michelle Lam of True & Co. says her company relies heavily on aggregated data.

Clothes are fickle. While it’s a hassle to go to a store and try on dozens of different garments to find the right fit, it’s nearly impossible to guess what will fit when shopping online. Onstage at Roadmap 2013, Michelle Lam, co-Founder and CEO of lingerie shop True&Co., talked about how her team has turned to data to not only ease a customer’s shopping experience, but to dictate how garments are produced in the future.

“We’re creating an ongoing dialogue with the customer to collect data without friction,” Lam explained.

Tackling the difficult topic of sizing bras online — a confounding problem in the real world, as research shows that up to 80 percent of women are wearing the wrong size bra — Lam said that her company starts collecting data from the customer by asking uncomfortable questions in a personable way.

“We talk about things that benefit the customer and a way to collect data that is incredibly friendly. We’ve exchanged an intrusive experience that’s very uncomfortable and turned it into a Cosmo quiz.”

The data is then filtered to categorize the women into one of 6,000 body types, which is then matched to create a body-specific store just from those answers. True & Co. continues to collect data as the customer shops, noting not only more personal facts (for example, whether or not a woman is married) but also aggregating what a customer clicks on and packs into a try-on box.

“To date, we’ve successfully fit eight in ten cases with the quiz alone,” Lam adds.

But Lam said that the company has been able to utilize that data for more than just increased personalization. Recently, the company launched an intimates line that is reflective of the feedback that customers have given the company. With that data, True & Co. took specific fits and design cues to create a custom line of bras based on the most popular feedback.

“We have a perfect loop of body type, implicit/explicit preferences, and then their feedback to figure out a sweet spot for each body type,” Lam explained. “We’ve then fed those sweet spots into a mass manufacturing process.”

Check out the rest of our Roadmap 2013 live coverage here, and a video embed of the session follows below:


A transcription of the video follows on the next page

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  1. Just a really good example of how to approach smart data capture and clever data analysis with the end goal in mind – improving the shopping experience. There seems to me to be still too many companies out there that take the reverse approach. They start with the data and see what can be unearthed from it. They should, like True & Co., start with the objective they want to achieve and understand specifically what data they need to achieve that objective.

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