Personalization is one of the most noticeable trends on the Internet in the last ten years. In this article, we will give a brief introduction to what personalization is and how it is used, and also consider what prevents the Internet from becoming completely personalized – and why these are only temporary obstacles.
What is personalization
For those who are not yet familiar with the term, personalization o updated 2024 mobile phone number data n the Internet is when content changes depending on the user interacting with it. Perhaps this is the broadest definition. The most obvious example: search results.
In short, every action we take on the Internet merges into a huything you indicated in your profile into the cauldron. You registered a profile on Drom.ru with this email – you added information about your car. You made a dozen requests in Yandex about science fiction films and literature – now the cauldron knows what you like to read and watch. And you fill the cauldron this way your entire conscious user life. You get a soup named after you.
But that’s not the end of the story. Everyone has a cauldron like this. The contents of some of them are similar to each other. Therefore, it is mathematically possible to derive patterns – and predict what you will like based on what people like you liked. Most people who gave Starship Troopers a 10 also liked The Martian – so if you rated one highly, you will like the other.
Where personalization is used
You encounter personalization based on big data every day. We are talking about personalized recommendations – this is a rather complex internally and simple external mechanism.
Watch a video on YouTube – and the site will offer you se veral similar ones.
Search for a product on the Internet – and you will st uk data aing ads with it on all sites.
Read articles on only one topic – and you will receive a newsletter with thematic articles inside.
And so on.You’ve probably noticed that large online stores reco where do viruses come from on a website? image by vector4stock on freepik mmend suspiciously “non-random” products. For example, a car radio of the very brand you’ve been actively interested in the lasays. This is your “cauldron” working together with personalized recommendation algorithms. Similarly, with large content projects like Kinopoisk or Last.fm, the idea of recommendations is at their core.