In this chapter, we have learned what CLV is and its importance and usage in marketing. Particularly for justifying the cost of customer acquisition, it is crucial to have a good understanding of how much value each new customer is going to bring to the company. We discussed how CLV calculations can help marketers to develop positive ROI marketing strategies. Then, we went through a hypothetical example to show how we can calculate the CLV, using average purchase amount, purchase frequency, and customer lifetime span. We also mentioned another approach of using machine learning and predictive models to estimate the CLV.
During the programming exercises, we have learned how to build regression models that predict the CLV over the course of a 3 month period. In Python, we used the scikit-learn package to build a LinearRegression model. In R, we used the built-in lm function...
