Real-Time Audience Data Collection in Content Delivery Networks
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Solution Overview
Problem
Existing content delivery networks lack the ability to rapidly and accurately track user behavior and preferences, and analyze this data in real-time to proactively adjust content and advertisement delivery.
Innovation Solution
A method and apparatus for collecting and analyzing audience data in a content delivery network, involving the receipt of content-related data elements, monitoring user interaction, processing usage data records, and transmitting them to an analysis entity for generating reports used in future content delivery decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prior art systems are used to track user behavior and preferences, then data collection capability is provided, but the ability to rapidly and accurately analyze data in real-time is lacking
Solution Approach 1:
The system performs preliminary data processing and analysis actions continuously as data is generated, rather than waiting for batch processing. Usage data records are processed in real-time as they are created, enabling proactive content delivery adjustments before user requests occur.
Solution Approach 2:
The analysis entity operates continuously to process usage data records in real-time, maintaining constant monitoring and analysis of user behavior. This continuous processing eliminates gaps in data analysis and enables immediate responses to user preferences.
2Reliability
If reactive systems are used to track user activity, then historical data can be analyzed, but real-time proactive adjustment of content delivery is not possible
Solution Approach 1:
The system implements feedback loops where usage data is continuously analyzed and fed back into content delivery decisions. The analysis entity processes real-time data and provides immediate feedback to adjust content delivery proactively, creating a closed-loop system that adapts to user preferences dynamically.
Solution Approach 2:
The content delivery system transitions from static, pre-programmed delivery to dynamic, real-time adjustment based on analyzed user behavior. The system adapts its content delivery strategy dynamically according to real-time usage patterns, enabling proactive responses to changing user preferences.
3Quantity of substance
If comprehensive user behavior tracking is implemented, then detailed audience data is collected, but system complexity increases
Solution Approach 1:
The system segments data collection into discrete usage data records generated by specific events (tune-in, tune-out, channel changes). Each record is processed independently through standardized templates, breaking down the complex data collection process into manageable units that can be handled systematically.
Solution Approach 2:
The analysis entity serves multiple functions: it processes various types of usage data, generates different report formats, and provides both historical analysis and real-time insights. This multi-functional design consolidates what would otherwise require multiple separate systems into a single unified platform.
Data Source
AI summary
Methods and apparatus for collection and processing of data relating to users of a content-delivery network. In one embodiment, the content delivery network is a cable or satellite or HFCu network, and the apparatus includes an architecture for routinely harvesting, parsing, processing, and storing data relating to the activities of the users (e.g., subscribers) of the network. In one variant, at least portions of the data are anonymized to protect subscriber privacy.