Markus Wübben & Florian v. Wangenheim
Executive Summary
Imagine that a marketing executive at a large direct marketing company needs to (1) identify customers who are likely to defect or stay and (2) identify potential future best customers. This information is crucial in computing customer lifetime value and retaining and maintaining relationships with the best customers, and it assists in preparing a win-back campaign for lost customer or customers who are likely to defect. The company may have built up a customer database with detailed information about each customer’s purchase behavior, but despite the richness of the available data, very simple managerial heuristics are used to address these issues. However, the marketing science literature offers sophisticated statistical models that are supposed to be able to determine customer activity levels and predict future purchases. As a committed member of the marketing team, this aforementioned marketing executive might ask whether these sophisticated models can help solve problems better than the traditional, simple managerial heuristics.
This article empirically evaluates the performance of the simple managerial heuristics and the sophisticated statistical models on three different data sets from three companies operating in noncontractual settings. Surprisingly, the evaluation shows that on the individual customer level, the predictions made by the sophisticated stochastic models do not outperform the simple managerial heuristics. The authors identify reasons that simple managerial heuristics tend to work well and how marketing science can achieve a greater impact in marketing practice when performance measures are used that are managerially meaningful.
Biography
Markus Wübben is a doctoral candidate in the TUM Business School at Technische Universität München, Munich. His research interests are customer management and customer base analysis.
Florian v. Wangenheim is Professor of Services and Technology Marketing in the TUM Business School at Technische Universität München, Munich. His research appears in the Journal of the Academy of Marketing Science, MSI Research Report Series, Journal of Business Research, Journal of Service Research, European Journal of Marketing, International Marketing Review, and Journal of Relationship Marketing, among others. His research interests are in customer management, technology-mediated services management, and solution marketing.
Journal of Marketing, Vol. 72, No. 3, May 2008
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