With E-Contenta, Matches tailors editorial to certain customer groups depending on their interests and online activity. People being exposed to targeted content look at twice as many pages, have a better conversion rate and better average basket value.

New customers open and view recommended books 2.17 times more often and their conversion rate into paying customers is 1.4 times higher.

High conversion rate into purchases and subscriptions when apps are downloaded. 20% decrease in CAC.

Increased customer life cycle (LTV) by 25%

Out of the videos that have already been viewed by Rutube users, the recommendation algorithm would recommend almost 40%

15% increase in the number of tv card views

Films in the personalized recommendation section are watched 2.5 times more often

The personalized recommendation algorithms work well, as well as similar products, product accessories, sales hits, and Next Best Offers