2001 · 38 citations · 6 references
Marketing AnalyticsDigital MarketingConsumer ResearchBusiness AnalyticsMarketing-campaign PlanningManagementDecision TheoryStatisticsElection ForecastingQuantitative ManagementPrediction ModellingPublic PolicyMarketing CampaignsPredictive AnalyticsPredictive ModelingPrediction-model EvaluationModel ComparisonCandidate SelectionMarketingAdvertisingCampaign PlanningInteractive MarketingStatistical Inference
Prediction‑model evaluation is considered in the context of marketing‑campaign planning. The study aims to evaluate and compare models by focusing on campaign‑specific evaluation criteria, discussing their relevance, robustness to population shifts, and use in constructing confidence intervals. The authors propose criteria that assess a model’s scoring accuracy and its ability to identify the relevant target population. Results are illustrated with a case study drawn from several projects.
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.
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Proceedings of the 24th international conference on Machine learning
2007 · 11.7K citations
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