Curating Streaming Content via Subscription Keys
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing multimedia distribution systems struggle to provide personalized, temporally and contextually relevant media program recommendations efficiently, often requiring users to spend excessive time reviewing content options and lacking the ability to recommend content outside the user's current subscription package.
Innovation Solution
A multimedia distribution system that generates personalized media program recommendations by using a recommendation engine to curate content based on a user's subscription level, upgrade paths, and viewing history, presenting recommendations through an interface with ribbons and tiles that indicate accessible and upgradeable content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system presents multiple content options across categories, then the variety of viewing options increases, but the time users spend reviewing content before making viewing decisions increases
Solution Approach 1:
The content interface is segmented into ribbons, each representing a curated collection of content items. This segmentation organizes the vast amount of content into manageable, theme-based groups that are pre-sorted and prioritized, allowing users to navigate content more efficiently without reviewing every individual item across all categories.
Solution Approach 2:
The system performs preliminary actions by pre-curating and pre-sorting content into ribbons based on user preferences, viewing history, and predicted interests. This preliminary organization eliminates the need for users to manually review all content options, as the most relevant content is already arranged and prioritized before the user needs to make viewing decisions.
2Ease of operation
If the system recommends programming from within current subscription packages, then the ease of access improves, but the ability to discover content outside the subscription package is limited
Solution Approach 1:
The recommendation system dynamically adapts its behavior based on user interactions. When users engage with content outside their subscription package, the system updates their profile and adjusts future recommendations to include more external content options. This dynamic adaptation allows the system to maintain ease of access for current subscribers while progressively expanding content discovery capabilities.
Solution Approach 2:
The system introduces an intermediary layer between the user and the full content library. This intermediary is the personalized ribbon interface that curates and presents content selectively. It acts as a mediator that can introduce users to content outside their subscription package while maintaining a smooth, easy interaction model, bridging the gap between current access and expanded discovery.
3Measurement precision
If manual curation by experts is used to generate promotions, then the relevance and accuracy of recommendations improve, but the system complexity and resource requirements increase
Solution Approach 1:
The system performs self-service by automatically generating personalized ribbons based on user viewing history, preferences, and patterns. Instead of requiring manual curation by experts, the system autonomously analyzes user behavior and creates tailored content recommendations, significantly reducing operational complexity while maintaining high recommendation accuracy.
Solution Approach 2:
The system continuously incorporates feedback from user viewing behavior to refine and improve recommendation accuracy. By monitoring what users watch, how long they spend on content, and their interaction patterns, the system automatically adjusts future recommendations. This feedback loop enables the system to improve precision over time without requiring manual recalibration or expert intervention.
Data Source
AI summary
Processes, computing systems, and devices perform operations to generate an interface for selecting streaming content on a client device. The operations include selecting a tile of video content for inclusion in a ribbon, compiling a set of eligibility keys that identify subscription levels with an upgrade path to access the video content of the tile, and compiling a set of lineup keys that identify subscription levels with access to the video content of the tile. A key associated with a user account is matched to the set of eligibility keys or the set of lineup keys to select the ribbon for presentation to the user account. The ribbon is transmitted to the client device in the interface for selecting the streaming content device in response to the user account associated with the key being authenticated on the client device.