Segmentation of life insurance customers based on their profile using fuzzy clustering

Abstract

In the current competitive environment, companies will be able to adjust business strategies, they use market segmentation based on practical ways rather than using traditional approaches or incomplete and impractical mass marketing. In recent years, mining has gained attention and popularity in the business world. The goal of data mining projects is to convert the raw data into useful information. Clustering can also be used to explore differences in attitudes and intentions of the clients. In this study, we used fuzzy clustering on 1071 life insurance customers during March to October 2014. Results show that the optimal number of clusters was 2 which were named as "investment" and "life safety". Some suggestions are presented to improve the performance of the insurance company.