Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
480396 | European Journal of Operational Research | 2012 | 11 Pages |
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.
► We developed a new method to create customer profiles based on self-organizing maps. ► Enables practitioners to reach previously unknown potentially interested customers. ► A case study confirms that more data leads to a better predictive performance.