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Basic Net Scoring Methods: The Uplift Approach

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Targeting Uplift

Abstract

Compared to the classical scoring approach, the difficulty with net scoring is that the target variable, i.e. the uplift, is not defined for an individual observation. Rather, the impact of a treatment is measured by a comparison of structurally identical groups of observations which have (target group) or have not (control group) received the treatment. The underlying problem is that an observation cannot be treated and not treated at the same time. Due to this interaction of the response and the treatment variable, gross scoring methods are not directly applicable, yet they present the basis from which to move on. In this chapter, several statistical methods for net scoring are presented. Firstly, a general and formal description of the net scoring problem is provided. Then, a wide variety of statistical methods for uplift modeling are presented and their respective advantages and disadvantages are described. The two final sections deal with appropriate methods for responses or treatments that are not binary, contrary to what is assumed for most parts of the book.

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Notes

  1. 1.

    The notion uplift-uplift comes to mind: It nicely emphasizes the second order nature of net modeling and sticks in mind.

  2. 2.

    The trade-off between stability and significance depends on the problem at hand.

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Authors and Affiliations

  1. Deutsche Bank AG, Frankfurt am Main, Germany

    René Michel & Tobias von Martens

  2. DeTeCon International GmbH, Berlin, Germany

    Igor Schnakenburg

Authors
  1. René Michel
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  2. Igor Schnakenburg
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  3. Tobias von Martens
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Michel, R., Schnakenburg, I., von Martens, T. (2019). Basic Net Scoring Methods: The Uplift Approach. In: Targeting Uplift. Springer, Cham. https://doi.org/10.1007/978-3-030-22625-1_3

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