Key Takeaways and Summary on Creating a Tableau Story

In this module, we performed an end-to-end case study of customer churn analysis.

Here is a quick summary of what you learned in this session:

• We started this session by creating multiple dashboards on the different services and their relation with contract, total charges (LTVs), monthly charges, tenure, and churn.
• Next, we created some plots to understand the contract and the payment patterns.
• Further, we created another dashboard to understand only the LTV.
• Finally, we created a Tableau story with all the dashboards created so far.

This brings us to the end of the case study. But before concluding this case study, we will watch the forthcoming video to understand what should be the key takeaways from the case study. Let us go ahead and watch the video.

So, here are the key takeaways from this case study:

1. Using SQL with Python is a great idea if you have to build complicated business logics and also want to have a single interface to run queries and perform analysis.
2. It is important to understand the business objectives and context prior to starting any type of analysis.
3. Concerning churn, we saw that the most important variables related to it include contract, monthly charges, and some services (internet, phone, and multiple lines).
4. People who stay with a company longer normally lead to higher LTVs, and enforcing 2- or 1-year contracts can help with this.
5. We can and must categorize people as having high and low LTVs.