Propensity scores are very useful because they tell you the likelihood of something happening. Confidence values for models reflect confidence in our predictions so a high degree of confidence doesn't help us determine if we're going to have a customer that's going to stay or leave a company, instead it indicates the confidence that we have in our prediction. Sometimes it's helpful to modify the confidence value so that a high confidence value means a prediction that a person is going to leave and a low confidence value indicates that a person is going to stay. Basically, we end up creating a propensity to leave score which would be helpful so that we could make interventions, different marketing efforts, and so on.
Consider this table, for example:
We have two values for Leaving and two values for Staying, each with the confidence...
