Executive Overview
A regional telecom provider experienced increasing subscriber churn due to aggressive competition and inconsistent customer engagement strategies. Quation deployed an AI-powered churn prediction model that identified high-risk customers and enabled targeted retention campaigns.
Key Challenges
- High subscriber churn rate
- Limited visibility into customer behavior patterns
- Reactive retention campaigns
- Fragmented CRM and billing data
- Low campaign effectiveness
Quation’s AI-Driven Customer Analytics Solution
Churn Risk Modeling
Machine learning models analyzed usage patterns, payment behavior, service complaints, and plan changes to predict churn probability.
Customer Segmentation
Segmented subscribers into risk categories for targeted engagement strategies.
Personalized Retention Campaigns
AI-driven insights optimized offers and communication timing to maximize response rates.
Performance Tracking Dashboard
Provided marketing teams with real-time churn risk metrics and campaign ROI tracking.
Business Outcomes
- 26% Increase in Customer Retention
- 31% Improvement in Campaign Effectiveness
- 18% Increase in Average Revenue per User (ARPU)
- 22% Reduction in Customer Acquisition Costs
Long-Term Strategic Value
By leveraging advanced AI-powered telecom analytics, the provider transitioned from reactive churn management to predictive customer intelligence.