Why most articles on churn aren’t helpful

No one likes to be left out, neither do businesses. To minimize this, we analyze churn. When I started learning about churn analysis I took to Medium and Kaggle. Having read many of the articles and notebooks out there I came to a few conclusions that motivated me to write this article. Most works are either:

o Too** Technical: **Lots of code, little reasoning. We work with data that is a depiction of reality yet many articles lack communication.

o Too **Theoretical: **Lots of reasons why you should do a churn analysis, perhaps some math, lack of clear examples. Often following the hype.

o Too Specific: Business is practical, most articles dive too deep in the latter two parts to be of significant value to business. Analysts deliver value through actionable insights. How to get such insights in general?

And well, some works are just too dull! So, I’ll be wrapping our analysis in the world of dating. After all, we don’t want Jack to be alone forever :)

As such, this article will take you through the steps on how to conduct a churn analysis, I promise you that there will be code and that I will make it clear. This article is summarized in the Venn diagram below, topped with a dating sauce

#guides-and-tutorials #python #analysis #churn #how-to