To model, or not to model: Forecasting for customer prioritization
Simple heuristics are usually deemed to be inferior to more complicated models. Although recent studies have demonstrated the usefulness of some forecasting heuristics, the questions of why and when a heuristic would work remain unaddressed. This study aims to answer such “why” and “when” questions by looking empirically at the specific context of forecasting for customer prioritization. Based on widely-applied probabilistic models, a series of simulations reveal that: (1) we are not usually able to identify the future top-X% of customers in a customer base accurately, even if we know the exact data generation process; (2) a simple heuristic can perform as well as a probabilistic model even if the model maps the data generation process exactly; (3) the relative performances of the model and the heuristics can be explained by several easily-obtainable descriptive statistics. The heuristic works because the minimal information it relies upon is relatively robust and relevant in a random world.
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- David C. Schmittlein & Albert C. Bemmaor & Donald G. Morrison, 1985. "Technical Note—Why Does the NBD Model Work? Robustness in Representing Product Purchases, Brand Purchases and Imperfectly Recorded Purchases," Marketing Science, INFORMS, vol. 4(3), pages 255-266.
- Fischhoff, Baruch, 1994. "What forecasts (seem to) mean," International Journal of Forecasting, Elsevier, vol. 10(3), pages 387-403, November.
- David C. Schmittlein & Robert A. Peterson, 1994. "Customer Base Analysis: An Industrial Purchase Process Application," Marketing Science, INFORMS, vol. 13(1), pages 41-67.
- Goldstein, Daniel G. & Gigerenzer, Gerd, 2009. "Fast and frugal forecasting," International Journal of Forecasting, Elsevier, vol. 25(4), pages 760-772, October.
- Makridakis, Spyros, 1986. "The art and science of forecasting An assessment and future directions," International Journal of Forecasting, Elsevier, vol. 2(1), pages 15-39.
- David C. Schmittlein & Donald G. Morrison & Richard Colombo, 1987. "Counting Your Customers: Who-Are They and What Will They Do Next?," Management Science, INFORMS, vol. 33(1), pages 1-24, January.
- Makoto Abe, 2009. "“Counting Your Customers” One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 28(3), pages 541-553, 05-06.
- Sharad Borle & Siddharth S. Singh & Dipak C. Jain, 2008. "Customer Lifetime Value Measurement," Management Science, INFORMS, vol. 54(1), pages 100-112, January.
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