churn

Time-to-event problems (churn, failure, conversion timing) hide a twist that quietly biases plain regression. The signal is naming that twist and reaching for the right framing. Here is the answer.

A high-AUC churn model that changes no behavior is worthless. The strong answer nails the label definition, picks classification vs survival deliberately, and is judged on retention uplift, not accuracy.

Saving a churning account is diagnosis under pressure: find the real reason, fix what you can, and earn back trust with action. Interviewers want a method, not a discount. Here is the move.