Dynamic Content Ratings via Credential-Based Event Tracking
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Solution Overview
Problem
Content providers face challenges in accurately and efficiently determining viewership habits across various content types and platforms, requiring quicker and more precise methods for content ratings.
Innovation Solution
A method that involves determining events associated with content access, authorizing content streams based on credential information, and analyzing viewership statistics to generate accurate viewership data, including popularity metrics, by using a system that includes content authorizing devices, message brokers, and message processors to track and update viewership quantities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional content rating methods are used, then content ratings can be determined, but the process is slow and lacks efficiency
Solution Approach 1:
The system performs preliminary actions by pre-authorizing content streams and pre-establishing credential verification mechanisms before content delivery. Event tracking is set up in advance, allowing the system to immediately capture and process viewership data as events occur, rather than conducting surveys or analyses after the fact. This preliminary setup enables real-time or near-real-time content rating determination.
Solution Approach 2:
The patent introduces intermediary components including event tracking systems, message brokers, and analytics platforms that mediate between content delivery and rating determination. These intermediaries capture event data during content delivery, buffer and process the information, and generate rating metrics without interrupting the content flow, thereby accelerating the overall process.
2Measurement precision
If comprehensive viewership tracking is implemented, then accurate content ratings are achieved, but system complexity increases
Solution Approach 1:
The system segments the content delivery and rating determination process into distinct modular components: credential verification modules, event tracking modules, data collection modules, and analytics modules. Each segment handles a specific function, allowing independent optimization and reducing overall system complexity while maintaining comprehensive tracking capability.
Solution Approach 2:
The patent implements universal event tracking mechanisms that can monitor multiple types of content delivery events (streaming, downloading, pausing, resuming) across different content types and delivery platforms using a single standardized framework. This multi-functional approach achieves comprehensive viewership tracking without requiring separate complex systems for each event type.
3Productivity
If real-time event tracking is performed, then viewership data is obtained quickly, but data processing complexity increases
Solution Approach 1:
Message brokers and data buffering intermediaries are introduced to handle real-time event data streams. These intermediaries receive, buffer, and pre-process event data from multiple sources, performing initial filtering, aggregation, and validation before passing data to analytics systems. This intermediary layer simplifies the processing burden on downstream systems while maintaining real-time data collection capability.
Solution Approach 2:
The event tracking system implements self-service mechanisms where tracking clients autonomously generate, validate, and transmit their own event data without requiring centralized verification for each event. The system automatically handles data normalization, duplicate detection, and basic analytics, reducing the processing complexity for central systems while maintaining high-speed data collection.
Data Source
AI summary
According to some aspects, methods and systems may include determining that events associated with requests or accessing content items have occurred. The methods and systems may also include authorizing transmission of the content items to the requesting devices based on credential information associated with the requests, and determining a viewership quantity metric associated with the requests.