Currently I'm working on a model that predicts sale based on the activity of a rep. It can be 3 types: mail, phone call, or meeting. These variables are continuous and somewhat cross-correlated, e.g., a rep can send 10 emails, make 1 call and have 3 meetings - and the more calls a rep makes, the less emails he/she sends.
Ultimately I'm trying to understand proportional weight of each activity to create combined activity metrics and say something along the lines: To win a deal with X% probability you need to perform 10 activity "units" where a meeting gives you 5 units, a call 3 units, and an email 1 unit.
It looks that in this case logistic regression should be used to estimate probability of sales from combined activity metric, but how to get best weights for each activity type?