Publications

Uplift modelingTM measures the variation in the difference between a treated group and a control group. Sometimes discussed using different names -- differential response analysis, incremental impact modeling, net modeling, incremental response modeling and "true" response modeling -- Uplift modeling separates "true" responses to campaigns from purchases that would have likely to have happen anyway.

A recently published paper evaluates results from using uplift modeling in three real-world examples. The paper outlines the introduction of quality measures appropriate to assessing the performance of uplift models, for both binary outcomes (purchase, attrition, click, default) and continuous outcomes (spend, response, size or value lost), and discusses some of the challenges faced when building uplift models.

To read the paper, go to http://www.portraitsoftware.com/?a=10399.