Customer information system using fuzzy query and cluster analysis

Abstract

Customer information is critical to customer relationship management. The goal of this research is to improve the efficiency of customer relationship management through developing a customer information system. Fuzzy terms with linguistic variables can help specific queries to be more versatile and user-friendly for customer data mining. In this paper, we propose a method integrating cluster analysis with linguistic variables in the context of fuzzy query logistics. Based on the proposed method, this research constructed a customer information system that can offer the user useful information as regards with strategy, decision-making, and better resource allocation methods. Results show the proposed method can decrease total execution time and increase the practicability with the feature of customer information cluster analysis.