Netflix does not disclose all the details of its algorithms, but it is clear from open sources that the basis of its success is user behavior data. The platform tracks what people watch, how much time they spend watching, and even what time of day they turn on TV series. These signals help the system decide what content to offer to a particular viewer.
What exactly does Netflix collect about viewers?
Netflix records:
which movies and series they start watching;
how long they watch a particular title;
the time of day when viewing takes place;
the languages selected;
the devices on which the viewer watches content.
This information forms the basis for personalization. It allows Netflix to tailor the recommendation feed to each user, taking into account their habits and preferences even before they consciously form them.
Source: netflix.com
Netflix never shows everyone the same catalog. Each home page is tailored to a specific viewer. If someone likes documentaries, they will be the first to be offered new documentaries. If they often choose comedies in the evening, the system will suggest these genres at that time. And all this works not based on age or city, but on the user’s actual behavior: what they watch, how much time they spend watching, and even what device they use.
Every click, every episode watched, and even the time of day influence what appears on the screen next. Netflix even tests covers and descriptions of series and films to understand which ones are more likely to attract attention and make you press “Play.” This makes viewing more engaging and increases the likelihood that the user will stay on the platform longer.
What can businesses learn from this?
Netflix shows that even without “reading users’ minds,” it is possible to tailor a product very precisely to their reactions. Tracking what people watch, how they interact with content, and what they choose allows you to create a personalized experience that captivates, retains, and brings users back.
For businesses, this means looking at the actual actions of customers, trying different ways of presenting the product, and responding to real signals rather than assumptions. This approach helps to sell better, build customer loyalty, and keep their attention longer.