In the narrow sense, data mining is a collection of tools and techniques. It is one of several technologies required to support a customer-centric enterprise. In a broader sense, data mining is an attitude that business actions should be based on learning, that informed decisions are better than uninformed deci sions, and that measuring results is beneficial to the business. Data mining is also a process and a methodology for applying the tools and techniques. For data mining to be effective, the other requirements for analytic CRM must also be in place.
CUSTOMER CENTRIC ENTERPRISE
In order to form a learning relationship with its customers, a firm must be able to: Notice what its customers are doing Remember what it and its customers have done over time Learn from what it has remembered Act on what it has learned to make customers more profitable Although the focus of this book is on the third bullet learning from what has happened in the past—that learning cannot take place in a vacuum. There must be transaction processing systems to capture customer interactions, data warehouses to store historical customer behavior information, data mining to translate history into plans for future action, and a customer relationship strat egy to put those plans into practice.