A/B testing is a popular tool for guiding mobile game development. The developer releases different versions of a game to different test cohorts, and observes which version has the best player retention or monetization. Correctly determining whether the differences are statistically significant is however challenging. Typically the analysis needs to be done on small and heterogeneous player cohorts, with differing follow-up times and unknown player churn. In this paper, we show for the first time how these issues can be properly addressed using the Cox model for recurrent events. The method enables a multivariate A/B-test, that allows determining which game version has the highest player retention or purchase rate, with confidence intervals provided. We demonstrate the benefits of the approach in multiple game development problems, on real-world free-to-play mobile game data.