Churn modeling with probabilistic meta paths-based representation learning

•We devise probabilistic meta paths representation learning for churn prediction.•We propose a random walks sampling method based on the corresponding Markov models.•Experiments on real-life datasets show the benefit of probabilistic meta path RL.•We obtain promising insights on meta path type and predictive outcome interplay.•Our method alleviates RL computational requirements by random walk sampling.