Instant Customer Base Analysis Managerial Heuristics Often “Get It Right”.pdf

Markus Wübben & Florian v. Wangenheim
Instant Customer Base Analysis:
Managerial Heuristics Often “Get It
Right”
Recently, academics have shown interest and enthusiasm in the development and implementation of stochastic
customer base analysis models, such as the Pareto/NBD model and the BG/NBD model. Using the information
these models provide, customer managers should be able to (1) distinguish active customers from inactive
customers, (2) generate transaction forecasts for individual customers and determine future best customers, and
(3) predict the purchase volume of the entire customer base. However, there is also a growing frustration among
academics insofar as these models have not found their way into wide managerial application. To present
arguments in favor of or against the use of these models in practice, the pare the quality of these
models when applied to managerial decision making with the simple heuristics that firms typically use. The authors
find that the simple heuristics perform at least as well as the stochastic models with regard to all managerially
relevant areas, except for predictions regarding future purchases at the overall customer base level. The authors
conclude that in their current state, stochastic customer base analysis models should be implemented in
managerial practice with much care. Furthermore, they identify areas for improvement to make these models
managerially more useful.
Keywords: customer base analysis, heuristics, relationship marketing, direct marketing, customer management
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