In this chapter, we have learned more about customer segmentation. We worked through three simple scenarios of how customer segmentation could help different businesses to form better and more cost-effective marketing strategies. We have discussed how having a good understanding of different customer segments, how customers in different segments behave, and what they need and are interested in can help you target your audience better. We have also learned about the k-means clustering algorithm, which is one of the most frequently used clustering algorithms for customer segmentation. In order to evaluate the quality of clusters, we have shown how we can use the silhouette coefficient.
During programming exercises, we have experimented with how we can build a k-means clustering model in Python and R. In Python, we could use the KMeans module in the scikit-learn package and...