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

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• 作者：Alex Seret^a ; ^{alex.seret@econ.kuleuven.be} ; Thomas Verbraken^a ; ^{thomas.verbraken@econ.kuleuven.be} ; Sé ; bastien Versailles^a ; ^{sebastien.versailles@gmail.com} ; Bart Baesens^a ; ^b ; ^c ; ^{bart.baesens@econ.kuleuven}
• 关键词：Data mining ; Customer profiling ; SOM ; Direct marketing
• 刊名：European Journal of Operational Research
• 出版年：2012
• 期刊代码：58_03772217
• 类别：et
• 出版时间：1 July, 2012
• 卷：220
• 期：1
• 页码：199-209
• 文件大小：552 K

摘要

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.