IMPROVING VIEWER ENGAGEMENT THROUGH CONTEXT-AWARE ADS IN FREE STREAMING SERVICES

The rapid growth of free streaming services has revolutionized how users consume content, creating new challenges in terms of monetization. Traditional advertisement delivery models, often seen as disruptive, have led to viewer dissatisfaction. This paper presents a context-aware ad delivery system that utilizes advanced machine learning (ML) and reinforcement learning (RL) to optimize viewer engagement by delivering personalized ads based on content type, viewer preferences, and real-time data. By considering both content-related and user-specific contextual factors, the system aims to improve viewer engagement while minimizing ad fatigue. Through extensive experimentation, the results show significant improvements in engagement metrics, such as click-through rates (CTR), compared to static and personalized ad strategies. The findings underscore the effectiveness of context-aware advertising in enhancing user experience and ad performance on free streaming platforms.