Fuzzified FCM for Mining Sales Data and Establishing Flexible Customer Clusters

RFM model is an important method in customer clustering. Some past studies have proposed fuzzy RFMs model to overcome the shortcomings of traditional RFM models. However, there are some problems unsolved in these approaches. To deal with these problems and to enhance the flexibility in customer clustering, the traditional fuzzy c-means (FCM) method is fuzzified to deal with R, F, and M scores that are expressed in fuzzy values. A fuzzified RFM model is then established by incorporating the fuzzified FCM approach, which is based on the inherent structure of the data itself. The number of customer clusters can be arbitrarily specified in advance, considering the scarcity of marketing resources and the diversification of marketing strategies. Besides, exploring the content of each customer cluster provides the business with many meaningful suggestions that could be usefully employed to establish target marketing programs. An example is adopted to demonstrate the application of the proposed methodology and to make some comparisons.