Evaluation of electronic service quality using an integrated fuzzy clustering and principle component analysis approach: an empirical case study

Abstract

This study uses data mining techniques to improve decision making process in various functions of electronic services provided by insurance companies. This study focuses on incentive packages recommended automatically by the system to the most qualified customers. Initially, customers are clustered based on their profiles. The fuzzy clustering techniques are used for this study. Each cluster is formed by customers with common characteristics according to their historical transactions. In each cluster, another data mining technique called principal component analysis is used to rank customers according to some variables which indicate the qualification of customer (customer satisfaction and expectation) to promote the insurance services and initiative packages.