2-3 September 2021
Publication Links
IJACSA
Special Issues
Article Details
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Customer Segmentation and Profiling for Life Insurance using K-Modes Clustering and Decision Tree Classifier
Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120950
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 9, 2021.
Abstract: Customer segmentation and profiling has become an important marketing strategy in most businesses as a preparation for better customer services as well as enhancing customer relationship management. This study presents the segmentation and classification technique for insurance industry via data mining approaches: K-Modes Clustering and Decision Tree Classifier. Data from an insurance company were gathered. Decision Tree Algorithm was applied for customer profile classification comparing two methods which are Entropy and Gini. K-Modes Clustering segmentized the customers into three prominent groups which are “Potential High-Value Customers”, “Low Value Customers” and “Disinterested Customers”. Decision Tree with Gini model with 10-fold cross validation was found as the best fit model with average accuracy of 81.30%. This segmentation would help marketing team of insurance company to strategize their marketing plans based on different group of customers by formulating different approaches to maximize customer values. Customers can receive customization of insurance plans which satisfy their necessity as well as better assistance or services from insurance companies.
Keywords: Customer segmentation; customer profiling; decision tree; insurance domain; k-modes clustering
Shuzlina Abdul-Rahman, Nurin Faiqah Kamal Arifin, Mastura Hanafiah and Sofianita Mutalib, “Customer Segmentation and Profiling for Life Insurance using K-Modes Clustering and Decision Tree Classifier” International Journal of Advanced Computer Science and Applications(IJACSA), 12(9), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120950
@article{Abdul-Rahman2021,
title = {Customer Segmentation and Profiling for Life Insurance using K-Modes Clustering and Decision Tree Classifier},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120950},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120950},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {9},
author = {Shuzlina Abdul-Rahman and Nurin Faiqah Kamal Arifin and Mastura Hanafiah and Sofianita Mutalib}
}
