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₹139,000+ in revenue was at risk — and the business did not know it yet.
I recently completed a Customer Churn Risk & Retention Analysis in Power BI, examining 7,043 telecom customers to identify who was most likely to leave and why.
Key findings from the analysis:
· 26.5% overall churn rate across the customer base · Month-to-month contract holders showed the highest churn likelihood · The first 12 months were identified as the highest-risk period for customer loss · High monthly charges emerged as a consistent predictor of churn behaviour
The dashboard was built to move beyond vanity metrics and surface the segments that actually matter — enabling targeted retention campaigns before revenue walks out the door.
Churn is not just a product problem. It is a data problem. When you can see which customers are at risk, which contracts are underperforming, and which price points are driving exits — you can build a retention strategy that is specific, not generic.
If your business is losing customers and needs clarity on why, I can help you build the analytics foundation to address it.
#PowerBI #ChurnAnalysis #CustomerRetention #DataAnalytics #BusinessIntelligence #TelecomAnalytics
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The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started