I'm trying to define a churn prediction model for an online service (betting/gambling). A lot of papers talk about churn analysis/prediction for telco companies where defining a churn user is straightforward: a churn user is a user who cancels his or her contract. I'm wondering how to define a churn user within the context of an industry where users don't cancel any contract/account?I can envision a general approach: if a user who plays every day for a month stops playing for 2 days, this is could be flagged, but a user who only plays once a week and then has no activity for 2 days would not. What's the best approach to encoding this logic algorithmically? Is survival analysis and good approach?
Data driven approach to define a churn user
machine learning;predictive modeling;survival analysis;churn