4. Evaluating and Choosing the Best Segmentation Approach
Overview
In this chapter, you will continue your journey with customer segmentation. You will improve your approach to customer segmentation by learning and implementing newer techniques for clustering and cluster evaluation. You will learn a principled way of choosing the optimal number of clusters so that you can keep the customer segments statistically robust and actionable for businesses. You will apply evaluation approaches to multiple business problems. You will also learn to apply some other popular approaches to clustering such as mean-shift, k-modes, and k-prototypes. Adding these to your arsenal of segmentation techniques will further sharpen your skills as a data scientist in ...
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