Data Mining Applications in Marketing and Customer Relationship Management
Data mining techniques do not exist in a vacuum; they exist in a business context. Although the techniques are interesting in their own right, they are a means to an end. This chapter is about the business context.
The chapter starts with a description of the customer lifecycle and the business processes associated with each stage. Every stage of the customer lifecycle offers opportunities for customer relationship management and data mining, as described throughout the chapter. The customer lifecycle is a central theme because the business processes supported by data mining are organized around that lifecycle.
The business topics addressed in this chapter are presented in roughly ascending order of complexity of the customer relationship. This relationship starts with customers as prospects, moves through the established customer relationship, and ends with retention and winback. In the course of discussing the business applications, the chapter introduces technical material as appropriate, but the details of specific data mining techniques are left for later chapters.
Two Customer Lifecycles
The term customer lifecycle can refer to two different things — the customer's own personal lifecycle, or the lifecycle of the customer relationship. From a data mining point of view, the latter is usually more important.
The Customer's Lifecycle
Customers, whether they are individuals, households, or businesses, ...