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Dynamic segmentation and ranking approach of customers and identifying their behavioral mobility using data mining techniques in Kargaran Welfare Bank
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Mohamd Paridari1   , Hassan Saberi 2, Zeinol abedin Amini3 , Ehsan Amini4 |
1- PhD Student in Business Administration, Department of Management, Faculty of Humanities, Saveh Branch, Islamic Azad University of Saveh, Iran
2- Assistant Professor of Business Management, Faculty of Humanities, Saveh Branch, Saveh Islamic Azad University, Iran (Corresponding Author) , saberi20hassan@yahoo.com
3- Assistant Professor of Public Management, Faculty of Humanities, Saveh Branch, Saveh Islamic Azad University, Iran
4- Assistant Professor of Industrial Management, Department of Management, Faculty of Humanities, Saveh Branch, Saveh Islamic Azad University, Iran |
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Abstract: (651 Views) |
Nowadays, identifying, determining the value and segmentation of customers is essential for a bank. Dynamic classification of workers' welfare bank customers and identification of their behavioral mobility between different departments in a specific period of time using data techniques Kaveh. In this regard, transaction data of customers of this bank was considered as a statistical community. In six time periods and on a monthly basis with the aim of segmentation and dynamic ranking of customers by K MEAN algorithms and self-organized neural networks SOM was performed. Based on the results of this study, customers were divided into three main sections and their dynamics were studied. Marketing is provided.
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Article number: 8 |
| Keywords: Dynamic Customer Segmentation, Customer Lifetime Value, Data Mining, K-means, SOM, Bank |
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Full-Text [PDF 1348 kb]
(278 Downloads)
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Article type: Research |
Subject:
Special
Received: 2022/06/24 | Accepted: 2022/08/18 | Published: 2022/12/1
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