Chapter 3

Unsupervised Learning: Customer Segmentation

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

This chapter covers various customer segmentation methods, deals with the concepts of similarity and data standardization, and explains k-means clustering.


In the previous chapter, we saw how to build plots using the built-in function of pandas, and learned how to estimate the mean, median, and other ...

Get Data Science for Marketing Analytics now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.