  As video games attract more and more players, the major challenge for game
studios is to retain them. We present a deep behavioral analysis of churn (game
abandonment) and what we called "purchase churn" (the transition from paying to
non-paying user). A series of churning behavior profiles are identified, which
allows a classification of churners in terms of whether they eventually return
to the game (false churners)--or start purchasing again (false purchase
churners)--and their subsequent behavior. The impact of excluding some or all
of these churners from the training sample is then explored in several churn
and purchase churn prediction models. Our results suggest that discarding
certain combinations of "zombies" (players whose activity is extremely
sporadic) and false churners has a significant positive impact in all models
considered.
