• Shruti Duge

How Netflix recommends a movie or series personalised for you?

#EverydayTech #ShortStory2 #HowThingsWork



Have you ever wondered how Netflix recommends a movie/series to you? The cursory research on this topic helped me understand these things.


Todd Yellin, Netflix’s vice president of product innovation, talks about how Netflix is like a three-legged stool. The three legs are -

1. Netflix members

2. Taggers who understand the content

3. Machine learning algorithms to synthesize the data


First leg: For Netflix members, various factors are considered to estimate the likelihood of watching a particular title. A few factors are mentioned below:

- Viewing history & user title ratings

Eg: when a user gives a thumbs up to the show (Explicit data) or if a person binge-watched it(Implicit aka behavioral data)

- Information about the titles, such as their genre, categories, actors, release year

- The time of day you watch

- The devices you are watching Netflix on

- How long you watch


Second leg: The data from taggers (inhouse or freelancers), aimed at understanding the content of all shows in the form of tags


Third leg: Machine learning algorithms are used to decipher the most important aspect for users based on this data, predicting future preferences and watching habits.


PS: Yes, my Netflix feed is filled with anime 

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