I call the techniques in this part “special” weapons and tactics because not all companies need to use them. In my opinion, however, all companies fighting churn need a great set of customer metrics. To someone who trained as a data scientist, this may be a surprise because the subjects in this part include what most people think of as the heart of data science: prediction! But I explained back in chapter 1 that churn is different: predicting churn has only a few use cases, whereas there are many more use cases for great customer metrics. Nevertheless, prediction can be an important weapon in your arsenal, with a few wrinkles unique to churn.
If you have never worked on any predictive analytics before, you might find that chapters 8 and 9 have a steep learning curve. That said, these chapters do cover all the basics, and I think anyone who learned the techniques in parts 1 and 2 can master the part 3 techniques as well. But if you have no experience in predictive analytics, you may need to put in a little extra time and use some of the recommended online resources.