Netflix is the world's largest online movie rental service with over 10 million subscribers and $1 billion in revenue. It was founded in 1997 and has evolved its recommendation system over time, starting with asking users for ratings and using collaborative filtering to provide personalized recommendations, which now account for 60% of movies selected. The $1 million Netflix Prize helped improve the accuracy of enjoyment predictions through the use of collaborative filtering, time-based corrections, and other models. Netflix continues to evolve its personalization and tailor recommendations with more metadata and implicit data.
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Personalizing Netflix Recommendations
1. Personalizing Netflix
A brief history
Jon Sanders
Recommendation Systems Engineering
Netflix
Los Gatos, CA
jsanders @ netflix.com
http://jobs.netflix.com
2. Fun facts about Netflix
World’s largest online movie rental service #1 in customer satisfaction
Founded 1997 Video rental companies (Consumer Reports)
Online retail (ForeSee)
With more than…
On an average day
10M subscribers, $1B revenue
2M DVDs shipped
100K DVD titles, 50 distribution centers
2M movie ratings received
12K streaming movies & TV episodes
1.5B minutes streamed to 1M Xbox360’s
2B movie ratings
60% of movies selected based on personalized recommendations
Connecting people with movies they’ll love
14. Evolution continues
• Tailor with more metadata, implicit data
• Streaming-specific personalization
• Collaborative Filtering is a component of personalization
• People want to drive, not be led
• Offer discovery, focus and decision support
http://jobs.netflix.com