Marketing Intelligent Systems for consumer behaviour modelling by a descriptive induction approach based on Genetic Fuzzy Systems

Article history: Received 2 March 2007 Received in revised form 26 December 2007 Accepted 12 February 2008 Available online 14 April 2008 In its introduction this paper discusses why marketing professionals do not make satisfactory use of the marketing models posed by academics in their studies. The main body of this research is characterised by the proposal of a brand new and complete methodology for knowledge discovery in databases (KDD), to be applied in marketing causal modelling and with utilities to be used as a marketing management decision support tool. Such methodology is based on Genetic Fuzzy Systems, a specific hybridization of artificial intelligence methods, highly suited to the research problemwe face. The use of KDD methodologies based on intelligent systems like this can be considered as an avant-garde evolution, exponent nowadays of the socalled knowledge-based Marketing Management Support Systems; we name them as Marketing Intelligent Systems. The most important questions to the KDD process–i.e. pre-processing; machine learning and postprocessing–are discussed in depth and solved. After its theoretical presentation, we empirically experiment with it, using a consumer behaviour model of reference. In this part of the paper, we try to offer an overall perspective of how it works. The valuation of its performance and utility is very positive. © 2008 Elsevier Inc. All rights reserved.