SummaryTechnological advancements have contributed to the new corporate culture, where customer relationship management (CRM) is at the center of business concerns. CRM is a widely implemented strategy for managing and fostering long-term profitable relationships with specific customers (Ling and Yen, 2001). Automated data mining tools have made it possible to go beyond analyzes of past events and data mining tools can be used to solve problems that were considered too time consuming in the past, thus providing new opportunities for businesses in relationship management. This report identified that CHAID and neural networks are two of the most commonly used data mining techniques in the CRM domain. However, each of these techniques has advantages and disadvantages that should be considered when deciding their suitability.1. IntroductionNowadays, organizations care more about increasing customer value and realize that customers are more predictable than ever before. As Written and Frank (1999) argue, consumers engage, negotiate, and purchase according to certain patterns etched in transactional and behavioral records. This report will discuss data mining techniques for CRM. Real-world case studies will be analyzed and two types of data mining techniques will be discussed, with emphasis on their relevance to CRM.2. Customer Relationship ManagementAccording to Swift (2001) and Ngai (2005), CRM consists of four dimensions, which can be considered as a closed cycle of customer management system. They share a common goal: to create a deeper understanding of customer behaviors to maximize their value to the business in the long term. Data mining techniques can be...... middle of paper ......telligence, Planning, 23, 582–605.Petrissans, A. (1999). “Customer relationship management: the changing economics of customer relationships”. White paper prepared by Cap Gemini and International Data Corporation. Written, IH and Frank, E. (1999) Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. San Francisco: Morgan Kaufmann Publishers. Swift, R.S. (2001). Accelerate customer relations: use CRM and relational technologies. Upper Saddle River. NJ: Prentice Hall PTR. Thomas, LC, Oliver, RW and Hand, DJ 92005) “A survey of issues in consumer credit modeling research”. Journal of the Operational Research Society, 56, 1006-1015 (September 2005). Turban, E., Aronson, JE, Liang, TP, & Sharda, R. (2007). Decision support and business intelligence systems (Eighth ed.). Pearson Education.