Audience Measurement Server Cross-Platform Data Aggregation
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Solution Overview
Problem
Existing audience measurement systems face challenges in accurately capturing and aggregating content exposure data across different platforms and sources, particularly in complex content delivery networks, due to varying methods of content identification and data collection, which complicates the measurement of overall audience numbers.
Innovation Solution
A system that enables cross-media audience measurement by transmitting lightweight communications or 'pings' from client devices to an audience measurement server, including device identifiers and content information, without requiring client-side agents, allowing for aggregation and filtering of data to provide comprehensive audience measurement while maintaining panel provider confidentiality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If panel members use monitoring software such as browser plug-ins or extensions to transmit content identifiers, then content exposure data can be captured, but device complexity and ease of operation deteriorate due to requiring client-side agents
Solution Approach 1:
The patent extracts the measurement functionality from client-side agents and relocates it to server-side infrastructure. Content publishers insert identification markers directly into content, and the measurement server passively receives and processes exposure data without requiring any client-side monitoring software, thereby eliminating the complexity and operational burden of client agents while maintaining measurement precision
Solution Approach 2:
The measurement server performs multiple functions: it receives content exposure data from multiple content publishers using different identification methods, aggregates data from diverse panels with varying standards, and provides unified audience measurement. This universal approach handles various content formats and publisher systems without requiring specialized client agents for each case
2Adaptability or versatility
If different content publishers use different content identification methods, then content can be delivered across multiple platforms, but measurement precision deteriorates due to difficulty in capturing and aggregating all content exposure
Solution Approach 1:
The measurement server acts as an intermediary between diverse content publishers and the audience measurement system. It receives content exposure data from multiple publishers using different identification methods, normalizes and aggregates this data according to unified standards, and produces accurate cross-platform audience measurements. This intermediary role reconciles the diversity of publisher methods with the need for precise aggregated measurement
Solution Approach 2:
The system transforms content identification data from various publishers into a standardized format. Different content identifiers and exposure metrics from diverse platforms are converted into uniform parameters that can be aggregated and compared, enabling precise measurement across multiple platforms while maintaining adaptability to different content delivery methods
3Productivity
If panel providers identify their panel members to the audience measurement server, then data can be filtered and aggregated by panel, but confidentiality deteriorates as panel membership information is exposed
Solution Approach 1:
The system segments panel identification into two parts: panel providers maintain local identification of their panel members, while the measurement server receives anonymous exposure data. Panel providers can filter and aggregate data for their own panels without exposing membership information to the server, thus maintaining confidentiality while enabling efficient panel-specific data processing through the segmentation of identification functions
Data Source
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AI summary
To provide secure single-source panel audience measurement data while providing confidentiality and security of panel membership, an audience measurement server may capture content identifiers and client identifiers of devices receiving content. A panel provider may generate a probabilistic data structure via a hash of the client identifiers. The audience measurement server may utilize the filter array to extract a subset of measurement data including the data of the panel members, as well as data of some non-panel members as false positives, without being able to distinguish between the members and non-members. The audience measurement server may encrypt the extracted subset of data with each client identifier corresponding to an item of data as a key, and send the encrypted data to the panel provider, thus including both panel and some non-panel data, with the panel provider only able to decrypt data corresponding to its own panel members.