Telecom Customer Churn Analysis
End-to-end analytics pipeline — SQL Server ETL, Power BI dashboard, and churn driver analysis for a telecom provider with 6,400+ customers.
An end-to-end analytics pipeline identifying key drivers of customer churn for a telecom provider, from raw data ingestion to an interactive Power BI dashboard for management.
Key Findings
| Insight | Detail |
|---|---|
| Overall churn rate | 27% (1,733 of 6,418 customers) |
| Month-to-month churn | 47% vs. 3% for 2-year contracts |
| Fiber-optic churn | 41% vs. 19% for no-Internet plans |
| Geographic concentration | Top 5 states = 60% of total churn |
| Electronic check users | 45% churn rate vs. 15–20% for other payment methods |
| Long-tenure churn | 28% churn rate for customers ≥ 24 months — service fatigue signal |
What I Built
1. Database Setup & ETL
- Created SQL Server database and staging schema
- Imported raw CSVs into staging tables (
Customer_Data,Churn_Staging) - Cleaned and standardized fields (null handling, type conversions)
- Populated production tables (
prod_Churn) via stored procedures
2. Data Transformation & Modeling
- Built reference tables for age groups, tenure bands, and charge brackets
- Unpivoted service indicators for granular analysis
- Defined star schema relationships in Power BI (fact table + dimensions)
- Developed DAX measures: Total Customers, Total Churn, Churn Rate, New Joiners
3. Power BI Dashboard
- Summary KPIs, Demographics, Geography, and Service Usage pages
- Drill-through pages for churn reasons and contract type deep dives
- Dynamic filters and context-sensitive tooltips
Tools
SQL Server Power BI DAX Excel