Evaluation of prediction models for marketing campaigns

Saharon Rosset, Einat Neumann, Uri Eick, Nurit Vatnik, Izhak Idan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

We consider prediction-model evaluation in the context of marketing-campaign planning. In order to evaluate and compare models with specific campaign objectives in mind, we need to concentrate our attention on the appropriate evaluation-criteria. These should portray the model's ability to score accurately and to identify the relevant target population. In this paper we discuss some applicable model-evaluation and selection criteria, their relevance for campaign planning, their robustness under changing population distributions, and their employment when constructing confidence intervals. We illustrate our results with a case study based on our experience from several projects.

Original languageEnglish
Title of host publicationProceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
EditorsF. Provost, R. Srikant, M. Schkolnick, D. Lee
PublisherAssociation for Computing Machinery (ACM)
Pages456-461
Number of pages6
ISBN (Print)158113391X, 9781581133912
DOIs
StatePublished - 2001
EventProceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001) - San Francisco, CA, United States
Duration: 26 Aug 200129 Aug 2001

Publication series

NameProceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Conference

ConferenceProceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001)
Country/TerritoryUnited States
CitySan Francisco, CA
Period26/08/0129/08/01

Keywords

  • Confidence Intervals
  • Marketing Campaigns
  • Model Evaluation
  • Performance Measures

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