Abstract Customer value refers to the potential interaction of customer and enterprise in the certain periods of time. As companies recognize customer value it can provide customized services for different customers, they can achieve to an effective customer relationship management. This research focuses on Banking Industry and integrates data mining techniques and management issues in order to systematically analyze the customer values. First it applies Fuzzy Analytical Hierarchy Processing (FAHP) in order to weighting variables and then imports DFMT model to the k-means technique, for clustering customers according to the specific criteria. Using proposed scoring model establishes the customer value pyramid and categorizes customers in four spectrums. The customer value pyramid helps to separately determining of each customer value to giving appropriate services to them in proportion with the class value. The statistical population was 285 customers of Tejarat bank branches of Zanjan city in Iran. In the resulted customer pyramid, the first spectrum is the Platinum customer which is composed of two rows of the pyramid called H1 and H2. These two rows in pyramid have the highest value and have the most profitability for the bank. Second spectrum, is called golden customers which has three rows in pyramid called H3, H4, H5. Third spectrums are Silver customers which are laid in H6, H7, H8 rows of spectrum. Forth spectrum, are leaden customers that are H9 and H10 rows of customer pyramid. This spectrum receives and wastes resources of the bank and bank should respect and bear high risks.

Abstract This paper proposes a Fuzzy Multiple Criteria Decision Making (FMCDM) approach for measuring supply chains capability with the main aim of customer satisfaction development. Drawing on the four measurement criterions of a Supply Chain Operations Reference (SCOR) model, this research first summarized the customer satisfaction and performance indexes synthesized from the literature relating to supply chains capability. Then, for screening, the indexes fit for supply chains capability in customer satisfaction development were selected through fuzzy screening. Furthermore, the relative weights of the chosen indexes were calculated by Fuzzy Analytic Hierarchy Process (FAHP). The MCDM analytical tool of TOPSIS was adopted to rank the supply chains performance and improve the gaps with three supply chains as an empirical example. The analysis results highlighted the critical aspects of evaluation criteria as well as the gaps to improve supply chains capability for achieving the aspired/desired level of customer satisfaction development. The results also showed that the proposed FMCDM measuring model using the SCOR framework can be a useful and effective assessment tool.