How does Uplift Modeling work?

Uplift Modeling estimates uplift scores (a.k.a. CATE: Conditional Average Treatment Effect or ITE: Individual Treatment Effect). Uplift score is how much the estimated conversion rate will increase by the campaign.

Suppose you are in charge of a marketing campaign to sell a product, and the estimated conversion rate (probability to buy a product) of a customer is 50 % if targeted and the estimated conversion rate is 40 % if not targeted, then the uplift score of the customer is (50-40) = +10 % points. Likewise, suppose the estimated conversion rate if targeted is 20 % and the estimated conversion rate if not targeted is 80%, the uplift score is (20-80) = -60 % points (negative value).

The range of uplift scores is between -100 and +100 % points (-1 and +1). It is recommended to target customers with high uplift scores and avoid customers with negative uplift scores to optimize the marketing campaign.