In the rapidly evolving telecom landscape, traditional customer satisfaction management methods struggle to keep pace with the dynamic demands of modern users. This project introduces a data-driven customer experience ecosystem that leverages AI and digital twin technologies to transform how CSPs understand, predict, and enhance user satisfaction. By integrating real-time network performance, service delivery, and behavioral analytics, the solution enables CSPs to proactively address issues, optimize resource allocation, and align customer needs with business outcomes. Unlike conventional approaches, this framework shifts from reactive feedback loops to predictive experience design, ensuring that every interaction contributes to measurable business value. CSPs face mounting pressure to deliver seamless, personalized experiences in an era where user expectations are shaped by hyper-connected digital ecosystems. Traditional methods of measuring satisfaction—such as surveys and static KPIs—are limited by: Fragmented data: Network metrics, service feedback, and user behavior remain siloed, preventing holistic root-cause analysis. Delayed responses: Reactive decision-making based on outdated feedback hinders real-time issue resolution (e.g., network latency or service gaps). Misaligned priorities: Satisfaction improvements often lack clear connections to revenue growth, making ROI justification challenging. Solving these challenges will redefine how CSPs operationalize customer experience. As Başar Günyel, Senior Manager of Network Quality at Vodafone Türkiye, states: "Our customers’ happiness and experience are our main-focus areas, and we measure this through complaints, surveys, and other feedback mechanisms. NPS surveys provide valuable insights into customer sentiment, and we leverage various network data sources to correlate this feedback with actual network performance.“