In this chapter, we discussed predictive analytics and its applications in marketing. We first discussed what predictive analytics is and how it is used in various other industries, such as in the financial and healthcare industries. Then we discussed four common use cases of predictive analytics in marketing—likelihood of engagement, customer lifetime value, recommending the right products and contents, and customer acquisition and retention. There can be numerous other use cases of predictive analytics in marketing, so we recommend you keep up with the latest news on how predictive analytics can be used in marketing industries. We then discussed five different ways to evaluate the performances of predictive models—accuracy, precision, recall, the ROC curve, and the AUC.
In the following chapter, we are going to expand our knowledge of predictive analytics...