Abstract
Customer management is one of the important aspects in retail business. It is vital for the retailers to adopt different methodologies by which high valued customers can be identified, in order to perform suitable target marketing effectively. In this paper, a novel model is proposed for classifying retail customers into different categories based on purchasing behavior of customers. A class label for each transaction is determined based upon customer profit value (CPV), and a classifier model is build for predicting different categories of customers. The classifier model is constructed using SPSS tool for market basket data. Finally, the classifier model is verified with test data set, and used for predicting customer category. The extracted information is helpful for planning customer retention and providing personalized customer services by understanding their needs, preferences and behavior.
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Ramaraju, C., Savarimuthu, N. (2011). A Classification Model for Customer Segmentation. In: Abraham, A., Lloret Mauri, J., Buford, J.F., Suzuki, J., Thampi, S.M. (eds) Advances in Computing and Communications. ACC 2011. Communications in Computer and Information Science, vol 190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22709-7_64
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DOI: https://doi.org/10.1007/978-3-642-22709-7_64
Publisher Name: Springer, Berlin, Heidelberg
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