Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty

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Data mining (DM) methodology has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the data used by researchers. This study has proposed a new procedure, based on expanded RFM model by including one additional parameter, joining WRFM-based method to K-means algorithm applied in DM with K-optimum according to Davies–Bouldin Index, and then classifying customer product loyalty in under B2B concept. The developed methodology has been implemented for SAPCO Co. in Iran. The result shows a tremendous capability to the firm to assess his customer loyalty in marketing strategy designed by this company in comparing with random selection commonly used by most companies in Iran.

论文关键词:Customer relationship management,Customer loyalty,K-Means algorithm,RFM model

论文评审过程:Available online 24 December 2009.

论文官网地址:https://doi.org/10.1016/j.eswa.2009.12.070