Relap.io is an advisory service tool which media can used to recommend readers relevant materials and articles through self-learning algorithms.
Relap.io service was started in the autumn of 2014 and its monthly service generates, as the founder Serghei Shalaev states, 2 billion recommendations and a coverage of 15 million unique users per day. The service uses machine learning algorithms and collaborative filtering to analyze the behavior of users, their geography, device, time spent on the page, and referral sources, in order to offer relevant materials. In the testing period, head of one of the online publications in Russia, AdMe.ru, Paul Radaev, stated that the number of readers, passing on the links in the block of recommendations, has increased by 32%.
The widget was designed to ensure an easy and quick integration on the online platform, which basically comes down to the selection of the unit and its design, followed by installing it on the media platform. Further on, Relaps.io selects the widget algorithms, depending on the specific site, whether it is a news media platform or a topic-wise magazine.
The revenue model with which Relaps.io works is rather innovative. Selling a media tool in time when media is experiencing downscaling and is in search for ways to remains sustainable did not seem like a good business model. Instead, the founder decided to combine the tool with native advertising in order to monetize Relap.io. The media platforms have to agree on sponsored native advertising on the Relap.io block of recommended articles, which represents the revenue model for the tool. And while native advertisement has yet to conquer the Russian media market, the Relap.io founder states that ”this is a new format, which has to prove its viability, and we will need to spend a lot of effort to make it a standard”.