Personalized Content Channel Generation for Service Providers
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Solution Overview
Problem
Content delivery systems often provide preset packages that may not align with subscribers' viewing or listening habits, resulting in unused content and a lack of current programming, especially when compared to traditional TV services.
Innovation Solution
A customized content selection and delivery system that generates personalized channel packages based on subscriber demographics and content consumption metrics, using scoring and statistical methods to select and deliver relevant content from various providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If preset packages of channels are provided, then service providers can offer comprehensive content coverage, but subscribers cannot access current or relevant programming that matches their preferences
Solution Approach 1:
The system dynamically generates customized channel packages for each subscriber based on their preferences, viewing habits, and demographic information. Instead of static preset packages, the channel lineup is continuously adapted and updated to reflect changing subscriber needs and content availability, enabling real-time personalization at scale.
Solution Approach 2:
The system changes multiple parameters simultaneously including subscriber demographics, content consumption patterns, content availability, and channel scoring weights to generate optimized channel packages. By adjusting these parameters dynamically, the system adapts to different subscriber segments and delivers personalized content lineups without manual intervention.
2Quantity of substance
If comprehensive content packages are offered, then content availability increases, but subscriber engagement decreases due to irrelevant content
Solution Approach 1:
The system extracts and selects only the most relevant channels from the comprehensive content library based on subscriber-specific scoring. Instead of presenting all available content, it takes out and highlights the top-scoring channels that match each subscriber's preferences, making content selection intuitive and engaging while maintaining access to the full library if needed.
Solution Approach 2:
The system segments the comprehensive content library into personalized channel packages for each subscriber based on their preferences and behavior. By dividing the large content volume into tailored segments, subscribers can easily navigate and select from relevant content rather than being overwhelmed by the complete catalog.
3Ease of manufacture
If traditional preset packages are used, then service provider operations are simplified, but content relevance and subscriber satisfaction decrease
Solution Approach 1:
The system performs self-service by automatically generating optimized channel packages without manual intervention. It uses algorithms to score channels, select top performers, and assemble personalized packages based on subscriber data, eliminating the need for manual package creation while ensuring high relevance and subscriber satisfaction.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor subscriber viewing habits, content consumption patterns, and satisfaction metrics. This feedback is used to refine channel scoring, adjust package compositions, and improve personalization over time, thereby maintaining high subscriber satisfaction while simplifying operations through automation.
Data Source
AI summary
A customized content selection and delivery system is operable to create a customized content channel package for a subscriber and customized content channel package to a customer premises over a content delivery network. A multi-level analysis based on measured content consumption metrics is performed to select content provider channels for the customized content channel package.