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AI-Powered Customer Churn Reduction and Personalization Platform for Telecom Industry

neoteric.eu

Telecommunications

Information Technology

Key Challenges Identified

The client faced three critical challenges: 1) Ineffective customer retention strategies based on random outreach and reactive discounts, 2) Lack of data-driven insights to identify churn-prone customers or understand churn drivers, and 3) Absence of a systematic approach to personalize offers or measure campaign effectiveness, resulting in high customer churn and operational inefficiencies.

About the Client

One of Poland's largest telecom providers with 1 million+ customers, offering internet, TV, and mobile services

Strategic Project Goals

Develop AI-driven predictive models to identify churn risks with 90%+ accuracy
Create personalized product recommendation engines to enhance customer retention
Implement real-time decision support tools for frontline staff
Achieve 20%+ churn reduction within initial pilot segments
Enable seamless integration with existing CRM and billing systems
Establish feedback loops for continuous model improvement

Core System Capabilities

360-degree customer profile aggregation from multiple data sources
Machine learning models for churn probability scoring
AI-powered product recommendation engine with explainability
Frontline employee dashboard with actionable retention strategies
Automated feedback collection and model retraining pipeline
Segmentation tools for targeted marketing campaigns

Technology Stack Requirements

AWS Lambda

Azure ML

Python

MongoDB

AWS SQS

System Integration Needs

CRM system (e.g., Salesforce)
Billing and subscription management
Customer support ticketing systems
Marketing automation platforms
Legacy telecom infrastructure APIs

Operational Constraints

Real-time prediction processing (<500ms latency)
Horizontal scalability for 1M+ customer records
99.9% system availability SLA
GDPR-compliant data handling
Model explainability and audit trail capabilities

Expected Business Outcomes

The implementation is projected to deliver: 1) 20%+ reduction in customer churn through proactive retention strategies, 2) 2x increase in campaign conversion rates via personalized recommendations, 3) 10x ROI through customer lifetime value preservation, 4) Accelerated digital transformation across departments, and 5) Establishment of data-driven decision-making culture with measurable impact tracking.