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Stage 1: Process & Methodology

• Prepared and cleaned churn data using Excel and Power Query

• Modeled churn metrics and financial impact in Power BI

• Analyzed churn by contract type, tenure, and service usage

• Built dashboards using segmentation and predictive targeting frameworks

Stage 2: Business Questions

• What is the churn rate and financial impact?

• Which customer segments are most vulnerable?

• What services and payment methods contribute to churn?

Stage 3: Objectives

Quantify churn impact, identify vulnerable segments, and develop retention strategies.

Stage 4: Key Insights

• 26.54% churn rate led to $2.86M loss

• Monthly subscribers and short-term customers had highest churn risk

• Fiber Optic users showed high churn due to cost

• Long-term customers generated 89% of revenue

• Electronic Check was the highest-churn payment method

Stage 5: Recommendations

• Incentivize long-term contracts

• Re-evaluate Fiber Optic pricing

• Improve onboarding for new customers

• Launch loyalty programs for high-value customers

• Investigate payment method issues

• Use predictive models to target at-risk customers