Telecom Customer Churn Analytics & Power BI Dashboard

### 🎯 Business Problem & Key Intelligence Metrics
In the telecommunications sector, customer acquisition costs far exceed customer retention expenses. Identifying high-risk churn segments is vital to protecting Recurring Revenue (MRR). The goal of this project was to perform an in-depth exploratory analysis on subscriber telemetry and deliver an executive-level Power BI dashboard highlighting key drivers of churn.

---

### ⚙️ Analytical Methodology & DAX Modeling
* **Data Preparation & ETL:** Cleaned, transformed, and validated subscriber contract data using Python (Pandas) and SQL queries, ensuring data integrity across demographic and financial attributes.
* **Dimensional Modeling & DAX Calculation:** Engineered dynamic DAX measures for core KPIs: Overall Churn Rate (%), Monthly Recurring Revenue at Risk, Average Tenure, and Customer Lifetime Value (LTV).
* **Behavioral Cohort Analysis:** Evaluated the impact of contract types (Month-to-Month vs. Two-Year), payment methods (Electronic Checks vs. Automated Credit), and technical support add-ons on retention.

---

### 📈 Executive Insights & Impact
* **High-Risk Segment Identification:** Revealed that short-tenure subscribers on Month-to-Month contracts paying via Electronic Check accounted for over 50% of total account cancellations.
* **Actionable Retention Strategy:** Provided commercial teams with data-backed recommendations to incentivize annual contracts and automated billing options.