An accurate recommendation is a challenge since predictions often miss novelty, are repetitive or become irrelevant to the users. For a large mobile game, it is crucial to enhance the relevance of displayed content. We will present the main challenges and their solution when building a recommender system for millions of players. We discuss the iterative approach to model development, the strategy of competing model testing as well as methods that can diminish the bias of the prediction.