Recommendation Quality and the Concentration of Consumption: Experimental Evidence from Netflix

Guy Aridor, Winston Chou, Nathan Kallus, Antoine Scheid, Allen Tran and Kevin Zielnicki

No 12981, CESifo Working Paper Series from CESifo

Abstract: We study an experiment with 8.5 million users on Netflix's recommender system to measure how improvements in recommendation technology affect the set of products that get consumed. Improvements increase total consumption and users' reliance on recommendations while diffusing recommendations and consumption away from the most popular products ("superstars") toward a larger number of moderately popular products ("middle-tail"), with minimal effects on the most niche products ("long-tail"). Our results challenge the notion that recommender systems polarize consumption — raising the consumption shares of the head and tail at the expense of the middle — and suggest that the returns to investing in middle-tail products grow as algorithms improve and platforms scale.

Keywords: personalization; recommendation systems; field experiment (search for similar items in EconPapers)
JEL-codes: C93 D82 D83 (search for similar items in EconPapers)
Date: 2026
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