A new SOM-based method for profile generation: Theory and an application in direct marketing

Alex Seret, Thomas Verbraken, Sébastien Versailles and Bart Baesens

European Journal of Operational Research, 2012, vol. 220, issue 1, 199-209

Abstract: The field of direct marketing is constantly searching for new data mining techniques in order to analyze the increasing available amount of data. Self-organizing maps (SOM) have been widely applied and discussed in the literature, since they give the possibility to reduce the complexity of a high dimensional attribute space while providing a powerful visual exploration facility. Combined with clustering techniques and the extraction of the so-called salient dimensions, it is possible for a direct marketer to gain a high level insight about a dataset of prospects. In this paper, a SOM-based profile generator is presented, consisting of a generic method leading to value-adding and business-oriented profiles for targeting individuals with predefined characteristics. Moreover, the proposed method is applied in detail to a concrete case study from the concert industry. The performance of the method is then illustrated and discussed and possible future research tracks are outlined.

Keywords: Data mining; Customer profiling; SOM; Direct marketing (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:220:y:2012:i:1:p:199-209

DOI: 10.1016/j.ejor.2012.01.044

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