Chapter 3. Unsupervised Learning: Customer Segmentation
Note
Learning Objectives
By the end of this chapter, you will be able to:
Describe the advantages of using unsupervised learning techniques (clustering) over more traditional segmentation techniques
Perform the preprocessing steps for preparing data for clustering
Use k-means clustering to perform customer segmentation
Determine the properties of groups created using clustering
Note
This chapter covers various customer segmentation methods, deals with the concepts of similarity and data standardization, and explains k-means clustering.
