Measuring the Impact of Personalized Recommendations

By Kevin Zielnicki, Guy Aridor, Aurélien Bibaut, Allen Tran, Winston Chou, and Nathan Kallus Introduction Personalization is everywhere on the internet. It shapes the products we discover, the stories we read, the music we hear, and the movies and TV shows we watch. At Netflix, personalization has been central to the member experience for decades — from the Netflix Prize to our modern recommender system that helps members navigate a large and constantly changing catalog. But personalization is not only an algorithmic problem, it is also a measurement problem. How do we know how much value pers

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