K-Mean Clustering Method For Analysis Customer Lifetime Value With LRFM Relationship Model In Banking Services
Journal Title: International Research Journal of Applied and Basic Sciences - Year 2012, Vol 3, Issue 11
Abstract
In today’s businesses, achieving customers satisfaction have critical role in organization's goals. On the other hand, all of customers hasn’t equal share in profitability of organization. Therefore, identification key customers will be more sensitive. Calculate the lifetime value assist organizations to rank customers based on their contribution to profitability. The purposeofthispaperisintroduced a model to calculate customer lifetime value (CLV) based on LRFM customer relationship model which consists of four dimensions: relation length (L), recent transaction time (R), buying frequency (F), and monetary (M) in banking services. We proceed with this clustering analysis to classify customers in order to set marketing strategies.Inthisresearch, KMe a n clustering methodas o n e o f t h e main problems in unsupervised learning emphasizes.Achieving this, we used crisp method and implemented them on real data from an Iranian state bank. Validity of clustering process analyzed with R-Squared index. The results show nine cluster patterns between customers. Finally, in terms of this clustering, we proposed customer strategies. Thus, this study considers useful for customer relationship management.
Authors and Affiliations
Mohsen Alvandi| Member of scientific board, Imam Khomeini International University, Iran, Qazvin, Safar Fazli| Member of scientific board, Imam Khomeini International University, Iran, Qazvin, Farzaneh Seifi Abdoli| Department of social science, Imam Khomeini International University, Iran, Qazvin
Keywords
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