Corpus ID: 22535399

Using control groups to target on predicted lift: Building and assessing uplift model

@inproceedings{Radcliffe2007UsingCG,
  title={Using control groups to target on predicted lift: Building and assessing uplift model},
  author={N. Radcliffe},
  year={2007}
}
  • N. Radcliffe
  • Published 2007
  • Engineering
  • Various authors have independently proposed modelling the difference between the behaviour of a treated and a control population and using this as the basis for targeting direct marketing activity. We call such models Uplift Models. This paper reviews the motivation for such an approach and compares the various methodologies put forward. We present results from using uplift modelling in three real-world examples. We also introduce quality measures appropriate to assessing the performance of… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 13 REFERENCES
    Bagging predictors
    11,878
    Open Access
    Marketing Data Mining
    3
    Open Access
    Programs for Machine Learning. Part I
    5,086
    Open Access
    Classification and Regression Trees
    27,197
    Open Access
    Induction of Decision Trees
    12,639
    Open Access
    A proportional hazards approach to campaign list selection
    • 2005