Company: Trunk Club

Worked on our “First Use” team to design and test a “curated outfits” feature based on machine learning to increase the rate of users receiving a “trunk” of clothes.


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Problem

Trunk Club was a digital styling service that paired users with stylists to help them pick out outfits and clothes to send to them in a “trunk”. As a designer on the “First Use” team, we were responsible for the a new user’s experience from sign-up through trying on the first trunk of clothes.

Our main KPI was what we called the "taker rate", or the percentage of new users who would "take" home a trunk of clothes to try on. We were starting to learn from past research that there was a good segment of new customers that would drop off because they didn’t have enough time to talk with their stylist, which was normally required in order to see any clothes. We started to think how might we allow customers to see clothes faster?


Discovery

Of the past discovery research we had done with customers around their first experiences with Trunk Club, there were a few themes that came up: