Cross-Platform Audience Deduplication Using Sequential Odds Ratios
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Solution Overview
Problem
Existing audience measurement systems face challenges in accurately deduplicating audience estimates across multiple computer sources due to duplicate impressions from cross-platform media exposure, leading to inflated reach metrics and inefficient advertising strategies.
Innovation Solution
A scalable approach using a combination of single source direct panel observations, predictive models, census-based observations, and integration techniques to generate logically consistent unique audience totals and probability distributions across various platform combinations, leveraging database proprietors for demographic data and employing alignment circuitry for optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If audience estimates are collected from multiple computer sources, then the comprehensiveness of audience measurement is improved, but duplicate impressions from cross-platform media exposure cause measurement precision to deteriorate
Solution Approach 1:
The patent introduces an intermediary alignment process that mediates between multiple data sources. Alignment circuitry acts as a mediator to harmonize audience estimates from different computer sources by adjusting for duplicate impressions and cross-platform exposure, thereby maintaining measurement precision while preserving comprehensiveness
Solution Approach 2:
The system changes measurement parameters dynamically based on the source and type of data being processed. Different weighting factors and adjustment parameters are applied to audience estimates from different sources, transforming raw counts into adjusted estimates that account for platform-specific duplication patterns
2Adaptability or versatility
If multiple computer sources are used for audience measurement, then the coverage of media ecosystems is improved, but reach metrics become inflated due to duplicate counting
Solution Approach 1:
The alignment process extracts and removes duplicate impressions from the aggregated audience data. By identifying and separating out redundant counting instances across platforms, the system preserves comprehensive coverage while eliminating the inflationary effect of duplicate reach metrics
Solution Approach 2:
The system segments the audience measurement process into distinct components: data collection from multiple sources, alignment and deduplication processing, and final estimation. This segmentation allows each component to be optimized independently, maintaining comprehensive coverage while preventing reach metric inflation through targeted deduplication
3Device complexity
If traditional audience measurement methods are used, then simplicity of the system is maintained, but advertising effectiveness deteriorates due to inefficient strategies
Solution Approach 1:
The alignment circuitry incorporates feedback mechanisms that continuously monitor and adjust audience estimates based on observed duplication patterns. This feedback loop enables the system to automatically optimize advertising allocation without requiring complex manual intervention, thereby improving advertising effectiveness while keeping the system operationally simple
Data Source
AI summary
Disclosed examples access media impression data via one or more wireless communications, the media impression data including panel data obtained from a meter and impression information obtained after an access of media at a computing device; determine an audience deduplication based on the panel data; determine odds ratios for platform combinations based on the audience deduplication; determine posterior distributions for the media based on the odds ratios; perform a sequential odds ratio insertion technique based on the posterior distributions to determine unique audience sizes; align the unique audience sizes based on a constraint; and generate a report including the aligned unique audience sizes.


