This thesis focuses on building innovative features that can enhance user experience on today's streaming platforms. Three core functionalities are proposed: a location-based content promotion feature that highlights local films, a synchronized viewing option (watch-party) for a real-time shared streaming experience and a personalized recommendation system based on movie poster analysis adopting a machine learning technique. The chapters delve into the need behind these features and showcases the design and development process using modern web technologies and tools, including OpenAI's CLIP for visual similarity: since the recommendation system goes beyond the meta-data by assessing the visual appeal of posters since it is what the viewer notices first. All of the developed features demonstrate the technical feasibility and how users can be the center of innovations in our digital era. The project is subject to continuous improvement and expansion.