Hybrid Cloud CRM Architectures for Telecom Network Intelligence: A Scalable, AI-Driven Framework for Real-Time Decision-Making

Abstract

Telecommunications providers are increasingly challenged by the exponential growth in network data and customer interactions, as well as the complexity of the partner ecosystem. Traditional Customer Relationship Management (CRM) systems are not designed to ingest, correlate, and act upon real-time network intelligence. This paper proposes a novel Hybrid Cloud CRM Architecture that integrates public cloud CRM platforms, private data lakes, and edge computing with an AI-driven intelligence layer. The proposed framework introduces a Network-Aware CRM Intelligence Layer (NACIL) that correlates telecom network KPIs with customer behavior and partner performance metrics. The architecture enables real-time decision-making, predictive analytics, and automated operational workflows. Experimental evaluation across telecom use cases demonstrates improvements of 28% in churn prediction accuracy, 35% reduction in incident resolution time, and 22% increase in partner-driven revenue efficiency. The proposed model positions CRM systems as intelligent, network-aware platforms that transform telecom operations from reactive to predictive.