For subscription-based businesses, reducing customer churn is a top priority. In this Power BI case study, we will investigate a dataset from an example telecom company called Databel and analyze their churn rates. Analyzing churn doesn’t just mean knowing what the churn rate is: it’s also about figuring out why customers are churning at the rate they are, and how to reduce churn. we will answer these questions by creating measures and calculated columns, while simultaneously creating eye-catching report pages.
Skip to → Customer Churn Power BI Final report
Exploratory Analysis – 1st Part of Our Power BI report
In the first part of the Power BI report we will do some exploratory analysis to check the data by creating new measures and columns.
We will check the following in particular:
- Check Data
- Calculate Churn Rate%
- Investigate Churn Reason
- Digging Deeper into Churn Categories
- Use maps for Churned locations
Investigating Churn Patterns – 2nd Part of The Report
Here we will further investigate why customers are leaving Databel. We will start by:
- Analyzing demographics
- Age groups
- Inspecting groups
- Churn by Contract and Gender
- Unlimited plan
- International calls
- Contract type
Visualizing My Analysis – Final Part of the report
In the last chapter, we’ll create dashboard-style pages and arrange them into stories, so that it is easier to share results with stakeholders. We will start by:
- Creating a cohesive story
- Dashboarding best practices
- Overview page
- More insights