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Information Journal Paper

Title

The Impact of E-CRM on Customer Loyalty Using Data Mining Techniques

Pages

  175-205

Abstract

 With the expansion of the Internet, various tools have been used to communicate with customers in organizations, and organizations use different E-CRM methods to create competitive advantages. Since Customer Loyalty is critical to achieving competitive advantage and profitability for organizations, one of the goals of organizations in using E-CRM is to maintain and increase Customer Loyalty. Therefore, considering the importance of the impact of various E-CRM services on customers’ loyalty, the purpose of this study is to investigate the impact of E-CRM on the loyalty of Bank Mellat customers using Data Mining techniques. The data required for this research were extracted from Bank Mellat databases. Data Mining techniques include clustering with K-means algorithm and neural networks (using error-relay algorithm) and LRFM model through programming in MATLAB and Excel software were used to analyze the data. The results showed that with increasing use of E-CRM services, customers’ loyalty increases. The relationship between E-CRM, the components of LRFM model, and loyalty is a nonlinear and the change in loyalty as E-CRM changes is not a constant. The increase in loyalty is a function of LRFM components, the amount of E-CRM and weights obtained in the neural network.

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    APA: Copy

    RANGRIZ, HASAN, & Bayrami Shahrivar, Zahra. (2019). The Impact of E-CRM on Customer Loyalty Using Data Mining Techniques. JOURNAL OF BUSINESS INTELLIGENCE MANAGEMENT STUDIES, 7(27 ), 175-205. SID. https://sid.ir/paper/268151/en

    Vancouver: Copy

    RANGRIZ HASAN, Bayrami Shahrivar Zahra. The Impact of E-CRM on Customer Loyalty Using Data Mining Techniques. JOURNAL OF BUSINESS INTELLIGENCE MANAGEMENT STUDIES[Internet]. 2019;7(27 ):175-205. Available from: https://sid.ir/paper/268151/en

    IEEE: Copy

    HASAN RANGRIZ, and Zahra Bayrami Shahrivar, “The Impact of E-CRM on Customer Loyalty Using Data Mining Techniques,” JOURNAL OF BUSINESS INTELLIGENCE MANAGEMENT STUDIES, vol. 7, no. 27 , pp. 175–205, 2019, [Online]. Available: https://sid.ir/paper/268151/en

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