Propensity predicts how likely a user is to return with subsequent activity. Users exhibiting positive interaction patterns are more likely to return and have higher scores.

There are many reasons why users churn — changing interests, competition from competitors, bad experience, etc. — but from a data perspective, attrition of any kind starts to look similar.

Propensity employs an ensemble of statistical models to identify any patterns it can find for detecting how and when attrition starts to occur. With time, propensity is able to find more patterns in your data and become increasingly accurate in identifying when users start to exhibit those behaviors.