Data Science for Marketing Analytics

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.

Introduction

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 ...