Incorporating neighborhood effects in customer relationship management models

Authors:
Philippe Baecke;Dirk Van Den Poel
Affiliations:
Ghent University, Faculty of Economics and Business Administration, Department of Marketing, Ghent, Belgium;Ghent University, Faculty of Economics and Business Administration, Department of Marketing, Ghent, Belgium
Venue:
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Year:
2011

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Abstract

Traditional customer relationship management (CRM) models often ignore the correlation that could exist in the purchasing behavior of neighboring customers. Instead of treating this correlation as nuisance in the error term, a generalized linear autologistic regression can be used to take these neighborhood effects into account and improve the predictive performance of a customer identification model for a Japanese automobile brand. In addition, this study shows that the level on which neighborhoods are composed has an important influence on the extra value that results from the incorporation of spatial autocorrelation.