The Netflix recommender system: algorithms, business value, and innovation
Recommender 'influences choice for about 80% of hours streamed'; 'We think the combined effect of personalization and recommendations save us more than $1B per year'; churn reduced 'by several percentage points'; effective catalogue size roughly four times that of an unpersonalised ranking at the median play rank, with axis values withheld for competitive reasons.
Recommender 'influences choice for about 80% of hours streamed'; 'We think the combined effect of personalization and recommendations save us more than $1B per year'; churn reduced 'by several percentage points'; effective catalogue size roughly four times that of an unpersonalised ranking at the median play rank, with axis values withheld for competitive reasons.
Written from the full text read 2026-10-12.
What our sources record
Reproduced as it was written when this source was checked, figures and all.
doi:10.1145/2843948. Issue dated December 2015, often cited as 2016. Full text read: recommender 'influences choice for about 80% of hours streamed'; 'We think the combined effect of personalization and recommendations save us more than $1B per year'; churn reduced 'by several percentage points'; effective catalogue size roughly four times that of an unpersonalised ranking at the median play rank, with axis values withheld for competitive reasons.