Abstract:

Emergence of a newly developed business culture increased the importance of establishing close
relationships with customers so as to increase long term profitability of companies and the concept of Customer Relationship Management (CRM) became incredibly important. To come up with successful CRM strategies, various analyses are drawn on significant amount of data stored in massive databases about customers’ characteristics and their buying behaviors. The aim of this study is to perform customer segmentation and profiling analysis for a company operating in the Fast Moving Consumer Goods (FMCG) market in Turkey by using data mining techniques so as to form a base for effective CRM activities focusing on its valuable customers which will result in increasing long term profitability and customer satisfaction. First, factor analysis is applied to reduce the dimensionality of the customer dataset. This set not only includes the traditional monetary, frequency and recency (RFM) variables but also contains other variables as suggested in the recent marketing literature. Segmentation is carried out by the nonhierarchical k-means clustering algorithm. Finally, customer profiles are obtained based on primarily  variables that are not included in the k-means algorithm.