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2015 | 21 | 24-35
Article title

Life Insurance Customers segmentation using fuzzy clustering

Content
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EN
Abstracts
EN
One of the important issues in service organizations is to identify the customers, understanding their difference and ranking them. Recently, the customer value as a quantitative parameter has been used for segmenting customers. A practical solution for analytical development is using analytical techniques such as dynamic clustering algorithms and programs to explore the dynamics in consumer preferences. The aim of this research is to understand the current customer behavior and suggest a suitable policy for new customers in order to attain the highest benefits and customer satisfaction. To identify such market in life insurance customers, We have used the FKM.pf.niose fuzzy clustering technique for classifying the customers based on their demographic and behavioral data of 1071 people in the period April to October 2014. Results show the optimal number of clusters is 3. These three clusters can be named as: investment, security of life and a combination of both. Some suggestions are presented to improve the performance of the insurance company.
Year
Volume
21
Pages
24-35
Physical description
Contributors
  • Faculty of Management and Accounting, Farabi College, University of Tehran, Tehran, Iran
  • Faculty of Management and Accounting, Farabi College, University of Tehran, Tehran, Iran
  • Faculty of Management and Accounting, Farabi College, University of Tehran, Tehran, Iran
References
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Document Type
article
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bwmeta1.element.psjd-cea7a72b-7f40-46ea-96dc-e2ca71d2939a
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