Development of an Intelligent Media Selection Platform for Group Viewing

The client faces challenges in streamlining the decision-making process for solo and group entertainment choices, leading to inefficient selections and reduced quality of shared experiences. Existing solutions lack personalized, group-aware recommendation capabilities, causing frustration and diminished engagement among users seeking quick, tailored entertainment options.

A technology startup focused on creating digital solutions that simplify entertainment choices for families and social groups by leveraging preference-based recommendation engines.

• Create a dynamic platform that offers personalized media recommendations based on user preferences and group dynamics.
• Facilitate seamless input of preferences for up to five users in group settings to determine optimal content choices.
• Implement a matching algorithm that provides a 'Best Match' suggestion based on collective voting and preferences.
• Streamline the media selection process to improve decision speed and enhance user satisfaction.
• Ensure the platform supports both individual and group entertainment scenarios with easy-to-use interfaces.

• User Preference Input Interface: Allow users to specify their favorite genres, actors, or shows/movies filters.
• Group Voting System: Enable up to five users to cast votes and reach consensus for shared entertainment choices.
• Recommendation Engine: Develop an algorithm that analyzes preferences and group votes to suggest suitable media options.
• Content Discovery Guide: Provide an exploratory interface to browse genres, trending titles, and personalized suggestions.
• Swipe-Based Interaction: Incorporate intuitive swipe gestures for quick selection and preference refinement.
• Notification & Sharing: Support social sharing and notifications to inform users of recommendations and decisions.

• Media Content APIs for accessing a broad range of TV shows and movies.
• User profile and authentication systems.
• Notification services for real-time updates.
• Third-party social sharing or voting platforms if applicable.

• System must support at least 100,000 concurrent users with minimal latency.
• Recommendation response time should be under 2 seconds.
• Secure data handling with compliance to privacy standards (e.g., GDPR).
• High availability with 99.9% uptime assurance.
• Scalable architecture supporting future feature expansion.

The platform is expected to significantly reduce media selection time for users, enhancing overall satisfaction and engagement. By enabling personalized and group-aware recommendations, it aims to increase user retention, drive higher content consumption rates, and attract strategic partnerships with entertainment providers, ultimately leading to expanded market reach and revenue growth.