Targeting Uplift

List of Symbols.- List of Figures.- List of Tables.- Introduction.- The Traditional Approach: Gross Scoring.- Basic Net Scoring Methods: The Uplift Approach.- Validation of Net Models: Measuring Stability and Discriminatory Power.- Supplementary Methods for Variable Transformation and Selection.- A Simulation Framework for the Validation of Research Hypotheses on Net Scoring.- Software Implementations.- Data Prerequisites.- Practical Issues and Business Cases.- Summary and Outlook.- Appendix.- Other Literature on Net Scoring.- Index.-

René Michel studied mathematics and received his Ph.D. with a focus on statistics from the University of Würzburg, Germany. After working for a consulting company (Altran) for eight years, he is currently a senior analyst and team leader at Deutsche Bank. The core area of his work is data mining in customer relationship management, especially performance measurement for marketing campaigns. He is also a certified SAS trainer and co-author of an introductory book on statistics.

After finishing his PhD at the Department of Mathematics, King's College, London, UK, and his work as a lecturer, Igor Schnakenburg focused on investigating analytical and strategic connections, in particular in the marketing and banking area. He has held various consulting positions and developed prediction models in Germany and abroad. He is an accredited SAS trainer and has taught several courses over the past few years.


Tobias von Martens completed a degree in business informatics at the Technical University Dresden, Germany, where he also received his Ph.D. for a dissertation on revenue management and customer value. He has worked for several years as a senior consultant for analytical customer relationship management, mainly for financial service providers, and has focused his consulting and research on the development of scoring models and customer segmentation.