The Science Behind the Netflix Algorithms That Decide What You’ll Watch Next1 min read

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Almost everything we do is a recommendation. I was at eBay last week, and they told me that 90 percent of what people buy there comes from search. We’re the opposite. Recommendation is huge, and our search feature is what people do when we’re not able to show them what to watch.

We know what you played, searched for, or rated, as well as the time, date, and device. We even track user interactions such as browsing or scrolling behavior. All that data is fed into several algorithms, each optimized for a different purpose. In a broad sense, most of our algorithms are based on the assumption that similar viewing patterns represent similar user tastes. We can use the behavior of similar users to infer your preferences.

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