As part of the PwC Power BI in Data Analytics Virtual Case Experience, I analyzed a customer churn dataset for a telecom client of PwC Switzerland. Through exploratory data analysis, I uncovered insights into the customer churn patterns, which I then visualized in a Power BI dashboard report. The report offered a clear and interactive means to communicate my findings, aiding the client in better comprehending customer behavior and making informed decisions to enhance customer retention.
Recommendations based on the Data:
1. Promote Longer Contract Durations: Encourage customers to opt for extended contract periods, such as one or two-year agreements, as these clients are less prone to churning.
2. Incentivize Contract Extension: Create attractive incentives for customers to transition from month-to-month contracts to longer-term commitments.
3. Tailored Offers for Senior Citizens: Develop customized offers and services tailored to the unique needs and concerns of senior citizens to mitigate churn rates within this demographic.
4. Retention Focus on Female Month-to-Month Customers: Concentrate on retaining female customers on month-to-month contracts, as they exhibit a higher likelihood of churning compared to male customers with similar contract terms.
5. Streamline Payment Options: Provide convenient payment methods and implement automated payment processes to minimize churn stemming from manual payment modes.
6. Mitigate Fiber Optic Internet Churn: Investigate the underlying causes of churn among customers using fiber optic internet to address the notably high churn rate within this specific customer segment.
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