Summary

In this chapter, we explored the idea of using unsupervised machine learning to perform customer segmentation. We established how to think about similarity in the customer data feature space and also learned the importance of standardizing data if they are on very different scales. Finally, we learned about k-means clustering, a commonly used, fast, and easily scalable clustering algorithm.

In this chapter, we used predefined values for the number of groups we asked the k-means algorithms to look for. In the next chapter, we will learn about how to choose the number of groups, how to evaluate your groupings, and additional methods for using machine learning to perform customer segmentation.