Modeling charity donations using target selection for revenue maximization

This paper presents the results of one application of target selection in direct marketing: the mailing campaigns of a charity organization, where the clients are selected based on the expected amount of donation they are going to make. Target selection is an important data mining problem for which several modeling techniques have been used. Statistical regression, neural networks, decision trees, and clustering are the most utilized techniques. Fuzzy clustering can also be applied to target selection. In this paper, traditional and fuzzy techniques are compared by using cross-validation measures. The four techniques are applied based on recency, frequency and monetary value measures. The application to mailing campaigns of a charity organization, showed that fuzzy modeling obtains results similar to those of other classical target selection techniques.