The longer a user stays on a platform

Why is personalization important?

Capturing user attention is an important goal for video, social m ia, and e-commerce platforms. , the more ads they see and the more likely they are to buy a product. Personalization plays a key role in this by recommending content that matches a user’s interests, thereby keeping them on the platform longer. This is not an easy task, as human attention spans are short. Studies show that the average Netflix user loses interest after 60 to 90 seconds of viewing. In other words, if Netflix can’t get a user to click in such a short time, he or she is likely to leave for another platform.

How personaliz is Netflix’s recommendation system?

Netflix uses various algorithms to recommend videos and provides relevant information through its home page, video detail tabs, emails, and user notifications. On the home page, there are up to 40 rows of recommend videos, which are group according to common themes or categories. As shown below, each row has a specific theme or category, such as TV series starring women, TV series worth watching, Western TV series, etc.

What topics or categories should

 

be includ on the homepage? (For example, are users interest in psychological TV series or award-winning friendship dramas?)

How to sort the topics?

Which videos should be includ in each topic? How should  vnpay database the videos be rank ? (For example, should Aquaman or Fast & Furious be 1 in the Blockbuster category?)

Special data

Netflix answers these questions

through meticulous calculations by its recommendation betting big when creating a start-up or algorithm, which aims to recommend videos that users want to watch. Organizing videos by topic/category is also a strategic move by Netflix. It not only makes it easier for users to choose  uk data videos, but also allows Netflix to analyze user behavior and interests by looking at the user’s scrolling actions. When a user scrolls down, it means that he/she is not interest in the topic display on the screen; when a user scrolls to the left, it means that he/she is interest in the topic but not in the top-rank shows.

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