Audience Measurement Entity for Cross-Platform Deduplication
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Solution Overview
Problem
Current methods for tracking digital media viewership, such as server logs and third-party cookies, are prone to over-counting and under-counting errors due to caching and tampering, and face challenges in accurately estimating unique audience sizes across multiple platforms, especially with the restriction on third-party cookies impacting privacy concerns.
Innovation Solution
The system generates public identity arrays through probabilistic bit-flipping of private identity arrays, allowing client devices to send these arrays to database proprietors for aggregation, enabling the audience measurement entity to estimate unique audience sizes without revealing personal identifiable information, and using these aggregated arrays to calculate deduplicated audience cardinality across multiple platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If server logs and third-party cookies are used to track digital media viewership, then viewership information can be obtained, but over-counting and under-counting errors occur due to caching and tampering
Solution Approach 1:
The patent introduces an audience measurement entity as an intermediary between database proprietors and advertisers. This entity aggregates anonymous audience metrics information from multiple database proprietors and provides deduplicated audience size estimates, eliminating the need for direct tracking of individual users across platforms while maintaining measurement accuracy.
Solution Approach 2:
The patent uses aggregated arrays that copy and combine anonymous audience metrics information from multiple database proprietors. These aggregated arrays contain sums of estimated cardinalities and intersections without revealing individual user identities, enabling accurate audience measurement while protecting user privacy and preventing tampering.
2Object-affected harmful factors
If third-party cookies are restricted to protect privacy, then user privacy is protected, but accurate estimation of unique audience sizes across multiple platforms becomes difficult
Solution Approach 1:
The audience measurement entity serves as a trusted intermediary that receives anonymous audience metrics information from database proprietors and performs deduplication across platforms. This intermediary approach enables cross-platform audience measurement without requiring third-party cookies or direct user tracking, thus protecting privacy while maintaining measurement precision.
Solution Approach 2:
The patent replaces the mechanical cookie-based tracking system with a mathematical aggregation system using aggregated arrays. Instead of tracking individual users across platforms via cookies, the system uses sums of estimated cardinalities and intersections from multiple database proprietors to calculate deduplicated audience sizes, eliminating the need for third-party cookies while maintaining accuracy.
3Productivity
If traditional tracking methods are used, then audience metrics can be generated, but duplicate counting across platforms occurs leading to inaccurate results
Solution Approach 1:
The audience measurement entity acts as an intermediary that consolidates audience metrics information from multiple database proprietors and performs deduplication. By using aggregated arrays containing sums of estimated cardinalities and intersections, the system eliminates duplicate counting across platforms while maintaining efficient audience metrics generation.
Solution Approach 2:
The patent moves the measurement from the individual user level to the aggregate population level. Instead of tracking individual users across platforms (one dimension), the system uses aggregated arrays that combine sums of estimated cardinalities and intersections from multiple database proprietors (another dimension), enabling deduplication without identifying individual users.
Data Source
AI summary
A disclosed example includes: at least one memory; instructions; and processor circuitry to execute the instructions to at least: determine a first sum of estimated individual cardinalities of audience members of first and second media platforms; determine a second sum of estimated pairwise cardinalities of ones of the audience members belonging to both the first and second media platforms; and generate lower and upper bound estimates of a deduplicated audience size based on the first and second sums; and send the deduplicated audience size to a computing device via a network communication.