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Targeting Uplift

An Introduction to Net Scores

  • René Michel
  • Igor Schnakenburg
  • Tobias von Martens
Book

Table of contents

  1. Front Matter
    Pages i-xxxii
  2. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 1-6
  3. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 7-43
  4. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 45-99
  5. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 101-120
  6. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 121-136
  7. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 137-146
  8. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 147-189
  9. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 191-239
  10. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 241-319
  11. René Michel, Igor Schnakenburg, Tobias von Martens
    Pages 321-325
  12. Back Matter
    Pages 327-351

About this book

Introduction

This book explores all relevant aspects of net scoring, also known as uplift modeling: a data mining approach used to analyze and predict the effects of a given treatment on a desired target variable for an individual observation. After discussing modern net score modeling methods, data preparation, and the assessment of uplift models, the book investigates software implementations and real-world scenarios. Focusing on the application of theoretical results and on practical issues of uplift modeling, it also includes a dedicated chapter on software solutions in SAS, R, Spectrum Miner, and KNIME, which compares the respective tools. This book also presents the applications of net scoring in various contexts, e.g. medical treatment, with a special emphasis on direct marketing and corresponding business cases. The target audience primarily includes data scientists, especially researchers and practitioners in predictive modeling and scoring, mainly, but not exclusively, in the marketing context. 

Keywords

net scoring uplift modelling incremental response personalized treatment learning campaign management enhanced scoring scoring algorithm applications of net scoring in markerting software implementation of net scoring algorithms gross scoring predictive modelling

Authors and affiliations

  • René Michel
    • 1
  • Igor Schnakenburg
    • 2
  • Tobias von Martens
    • 3
  1. 1.Deutsche Bank AGFrankfurt am MainGermany
  2. 2.DeTeCon International GmbHBerlinGermany
  3. 3.Deutsche Bank AGFrankfurt am MainGermany

Bibliographic information

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