I have actually looked over a dataset from the telecom industry to understand the customer churn trend using Power BI to enable the leadership to take necessary measures according to the requirement. Here are some key highlights:
✨Visualization of the churn rate distribution in terms of states has paved the way to further targeted investigation of the rise of the churn rate in specific locations
✨Churn rate distribution by age has led to the fact that elderly (60+) people are churning more than the younger customers
✨Variation of Churn rate by the contract type revealed that monthly subscribers are more likely to churn than yearly subscribers
✨New customers are more likely to churn compared to the old customers
Please don't hesitate to contact me for more details about the analysis or any feedback.