Reinforcing Crm with Data Mining

With the explosive growth of information available on the World Wide Web, users must increasingly use automated tools to find, extract, filter, and evaluate desired information and resources. Companies are investing significant amounts of time and money on creating, developing, and enhancing individualized customer relationships, a process called customer relationship management, or CRM (Berry & Linoff, 1999; Buttle, 2003; Rud, 2000). Based on a report by the Aberdeen Group, worldwide CRM spending reached $13.7 billion in 2002 and should be close to $20 billion by 2006. Data mining is a powerful technology that can help companies focus on crucial information that may be hiding in their data warehouses (Fayyad, Grinstein, & Wierse, 2001; Wang, 2003). The process involves extracting predictive information from large databases. Data-mining tools can predict future trends and behaviors that enable businesses to make proactive, knowledge-based decisions. By scouring databases for hidden patterns and finding prognostic information that lies outside expectations, these tools can also answer business questions that previously were too time-consuming to tackle. Web mining is the discovery and analysis of useful information by using the World Wide Web. This broad definition encompasses Web content mining, the automated search for resources and retrieval of information from millions of Web sites and online databases, as well as Web usage mining, the discovery and analysis of users’ Web site navigation and online service access patterns (Berry & Linoff, 2002; Marshall, McDonald, Chen, & Chung, 2004). Today, most companies collect and refine massive amounts of data. To increase the value of current information resources, data-mining techniques can be rapidly implemented on existing software and hardware platforms and integrated with new products and systems. If implemented on high-performance client/server or parallel processing computers, data-mining tools can analyze enormous databases to answer customer-centric questions such as, “Which clients have the highest likelihood of responding to my next promotional mailing, and why?” This article provides a basic introduction to data-mining and Web-mining technologies and their applications in CRM. BACKGROUND