ABSTRACT
The ideal form of customer service is personal attention, where the needs of each individual are met. Unfortunately, this level of service is more often than not impossible or too costly to achieve. Service providers, therefore, segment their customers into groups with similar characteristics. Cluster analysis is a commonly used technique to segment customers using data, which analyses and divides an unlabeled dataset into groups of observations with similar properties. This chapter shows how to detect patterns and define segments in customer data. The learning objectives for this chapter are:
Understand the principles of customer segmentation
Apply and interpret hierarchical cluster analysis
Apply and interpret k-means clustering
