From video platforms to social m ia to online stores, how to capture users’ attention is a major issue. The more time users spend browsing content, the more ads they will receive and the more products they will buy. The key is to provide a personaliz experience, attracting users’ attention by recommending content that they are interest in, so that they spend more time on the platform. People’s attention is extremely short – studies have shown that if Netflix fails to recommend a movie that users want to watch within 60 to 90 seconds, users will lose interest and leave Netflix!
How Personaliz Is Netflix’s Recommendation System?
From the video content and arrangement on the homepage, detail information on the videos, to emails and user notifications, Netflix uses different algorithms to provide users with the works they are most interest in and the video information they care about most. Netflix’s homepage classifies recommend videos by theme and category and arranges them into up to 40 rows. As shown in the figure below, each row is a movie theme or category, such as “Blockbuster Movies”, “Family Movies”, “Psychological TV Dramas”, etc.
How personaliz is Netflix’s recommendation system?
Image cr it: Netflix
What film topics should the homepage include? (For rcs database example, would this user be interest in “psychological TV dramas” or “award-winning shows about friendship When a user scrolls down, it means that he is not interest in the theme display on the screen; when he scrolls left, it means that he is interest in the theme display , but not interest in the first few works in the theme.
Which topics should come first?
Which movies should be includ in each theme? How carefully segment your database should the movies be rank ? (For example, in the theme of “blockbuster movies”, should “Aquaman” or “Furious” be rank first?)
All of the above have been carefully calculat by the video recommendation system, the purpose of which is to enable users to find the videos they want to watch in the uk data shortest possible time after logging in. Netflix also has a hidden idea behind arranging the videos by category. In addition to systematically classifying the videos and making it easier for viewers to choose videos, it is also for more effective analysis of user behavior.