Decomposition of a term-document matrix representation for faithful customer analysis

The recent rapid growth of the services industry has led to an increase in the number of service quality improvement research studies. However, analyzing service quality and determining the factors influencing consumers' perceptions of service quality are a challenging problem. The objective of this paper was to apply a data mining method to the current problems of Customer Relationship Management (CRM), analyze corporate communications systems and then identify possible data mining applications. We apply simple statistical and machine-learning techniques to study the dynamics of occurrence frequencies of events by scrutinizing user comments and corresponding customer satisfaction scores. Our analysis revealed that in the context of customer support centers, the service experience of customers strongly influences the satisfaction and service quality that the customers experienced. As a result of this study, we have identified a method of capturing the hearts of faithful customers.