Alie is a recommendation engine for online gaming platforms that use on-site behavioral targeting for suggesting games. It studies the user profiles and other aspects like - games played/purchased, total playtime, ratings, reviews, interactions, and suggests games based on the similarities. Alie can also help you keep the players engaged with suggestions like “new arrivals”, “most played”, “most purchased”, etc.
Alie offers a variety of algorithms that you can implement as per your requirement and hook them at the right places on your platform. Alie offers Algorithms like - Most Played, Most Purchased, Other user’s choice, End-user interaction, etc.
Alie analyzes your user’s choices and games they are playing frequently. You can use Alie for showing your most recent games in the same genre as recommendations. You can use nomenclature like - “newly launched”, “just arrived” or “New game suggestion for you”
More the time people will spend playing games on your platform more likely they will make in-app purchases. Though it also depends on how the games are designed and whether have strategies to drive in-app purchases. But certainly, the relevant gaming recommendations will urge people to play the recommended games.
Behavioral data is the most important data which Recommendation Engines can use for suggesting games to your users. The online gaming industry has access to detailed data about how players interact with the games. Alie can use this data to discover underlying patterns and create users profiles and groups to recommend the games.
There are various ways with which you can engage the gamers on your platform. Recommendations are one of the ways with which gamers tend to stay longer on your platform. Better the recommendations more will be the time spent by gamers.