Which features of a data set can be used for market campaigning using propensity scores?

Question

A dataset contains so many fields in which there is both relevant and irrelevant field. If we want to do a market campaigning using propensity scoring, which fields of the data set are relevant? How can we find which data field should be selected and which drive to the desired propensity score?

Answer 1

If you take a machine learning approach, the machine learning model would automatically find which features to weigh to predict an outcome.

For example, a decision tree would tell which combination of features are associated with higher propensity scores.