Enhancing Telecom Customer Experience Through AI Driven Personalization - A Comprehensive Framework

Abstract

This paper presents a comprehensive framework for implementing a Customer Experience Enhancement Agent in the telecom industry, focusing on the use of autonomous AI agents. The objective is to investigate how AI can transform customer interactions and deliver personalized services. The framework includes components, such as data analysis, tailored recommendations, and dynamic adjustments. Beginning with a comprehensive analysis of customer data, including usage patterns, preferences, and interaction history, the framework forms the foundation for understanding customer behavior. Algorithms developed to offer personalized service suggestions, like optimal data plans, new features, and other relevant recommendations tailored to individual profiles. The use of collaborative filtering, content-based filtering, and hybrid models ensures that recommendations are accurate and relevant. Additionally, the framework implements methods for continuously refining recommendations as customer behavior evolves using real-time data analytics and machine learning techniques. This approach addresses challenges, such as data volume, velocity, veracity, privacy concerns, and algorithm biases. By continuously adapting to changing customer behaviors, the proposed framework aims to enhance customer satisfaction and loyalty, thereby driving the growth and competitiveness of telecom providers.