Abstract

Customer Relationship Management (CRM) plays a crucial role in maintaining and enhancing customer satisfaction and loyalty. To effectively manage customer relationships, organizations require decision support systems that can provide valuable insights and assist in making informed decisions. In this context, Rough Sets-Based Decision Support Systems (RS-DSS) have emerged as a promising approach. RS-DSS utilizes the principles of rough set theory to handle uncertainty and vagueness in customer data, enabling the discovery of hidden patterns and knowledge for effective CRM. This paper provides an overview of the application of RS-DSS in CRM, highlighting its benefits and challenges. The study also discusses various components of RS-DSS, including attribute reduction, rule extraction, and decision-making. Furthermore, the paper presents a case study to illustrate the practical implementation and potential outcomes of RS-DSS in CRM. Overall, RS-DSS holds significant potential in enhancing customer relationship management by leveraging rough set theory for decision support and improving organizational performance.