Natalia Chen
ABSTRACT
At Peloton, we constantly strive to improve the member experience by highlighting personalized content that speaks to each individual user. One area of focus is our landing page, the homescreen, consisting of numerous rows of class recommendations used to captivate our users and guide them through our growing catalog of workouts. In this paper, we discuss a strategy we have used to increase the rate of workouts started from our homescreen through a Thompson sampling approach to row ranking. We also explore a potential improvement with a collaborative filtering method based on user similarity calculated from workout history.
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Digital Library
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- Shoya Yoshida, Shayak Banerjee, Nganba Meetei, Natalia Chen. 2023. Revamping Peloton Homescreen Experience with Personalized Rows. Retrieved 30 May, 2023 from https://www.onepeloton.com/press/articles/revamping-peloton-homescreen-experience-with-personalized-rowsGoogle Scholar
Index Terms
- Leveling Up the Peloton Homescreen: A System and Algorithm for Dynamic Row Ranking
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