chapter five
5 Understanding churn and behavior with metrics
If you need to use statistics to understand your experiment, then you ought to have done a better experiment
-Ernest Rutherford, Nobel Prize in Chemistry 1908 : Known as "The Father of Nuclear Physics" for his discovery of radioactive decay.
This chapter covers
- ● Showing how churn relates to metrics using cohort analysis
- ● Summarizing the range of customer behaviors with dataset statistics
- ● Converting metrics from their normal scale into scores and analyzing cohorts using scores
- ● Removing invalid observations from a cohort analysis
- ● Defining customer segments based on metrics and churn
It’s time to do what you came here for: understand why your customers are churning and what keeps them engaged. Although it took a while, the dataset you learned to create in the previous chapters is the foundation for what comes next. You may be expecting that now I'm going to dive into some serious statistics or machine learning to do the analysis. Instead, I want to call your attention to the quote at the top of the page, which is my favorite saying by a scientist.