A popular service for reading e-books based on subscription on the iOS, Android, and Windows platforms with a large library estimated at 500 thousand books in 12 languages and 3 million subscribers worldwide.


Stale start: recommendations were offered for new customers that just installed the app, meanwhile nothing was known about them or their tastes in reading


A recommendation model was constructed using public data, DMP and social networks


New customers open and view recommended books 2.17 times more often and their conversion rate into paying customers is 1.4 times higher.
“If recommendation systems are meant to do real business, then what they need to do is go full-throttle with their customer operations and operate like a channel. That’s the way Bookmate operates with E-Contenta.”
Konstantin Savenkov

Interesting Side Note

The Untitled Retail Lab venture company has invested USD 250000 into the E-Contenta personal recommendations service. The transaction took place in December 2015.
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