Cross-Device Panel Generator for Audience Measurement
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Solution Overview
Problem
Traditional audience measurement methods rely on registered panel members, limiting the ability to accurately measure cross-device media exposure and device usage, as data collection techniques vary by device type and not all devices are registered, leading to incomplete profiles.
Innovation Solution
The development of a cross-device panel generator that aggregates data from multiple devices by conducting cross-device usage surveys, matching panelists with similar demographics and usage patterns, and imputing missing data from donor panels to create comprehensive profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional panel member tracking is used, then measurement precision for registered devices is maintained, but device coverage and profile completeness deteriorate
Solution Approach 1:
The patent creates virtual copies of panelist profiles by aggregating data from multiple devices and imputing missing information. When a panelist uses unregistered devices, the system generates a virtual profile that replicates their media consumption patterns across all devices, enabling measurement of devices not directly monitored. This allows the system to maintain measurement precision for registered devices while extending coverage to unregistered devices through profile replication.
Solution Approach 2:
The patent introduces an intermediary data aggregation layer that sits between individual device measurements and overall audience metrics. This intermediary layer aggregates data from multiple devices, fills gaps with imputed data, and creates unified panelist profiles. The intermediary process translates fragmented device-level data into comprehensive cross-device insights, resolving the contradiction between measurement precision and device coverage.
2Adaptability or versatility
If data aggregation from multiple devices is implemented, then cross-device profile completeness is improved, but system complexity increases
Solution Approach 1:
The patent segments the data aggregation system into distinct functional modules: device data collection, profile matching, data imputation, and aggregation. Each module handles a specific aspect of the complex task, making the overall system more manageable. The segmentation allows independent optimization of each component and simplifies maintenance while achieving comprehensive cross-device profiling.
Solution Approach 2:
The patent creates a universal data aggregation framework that can handle multiple device types and data sources through a single unified process. The system uses general-purpose algorithms for profile matching and imputation that work across different devices, rather than requiring device-specific processing logic. This multi-functionality reduces operational complexity while maintaining comprehensive coverage.
3Adaptability or versatility
If additional metering software and proxy devices are deployed, then measurement coverage is improved, but network bandwidth and resources are consumed
Solution Approach 1:
The patent creates virtual copies of panelist profiles by aggregating data from multiple devices and imputing missing information. When a panelist uses unregistered devices, the system generates a virtual profile that replicates their media consumption patterns across all devices, enabling measurement of devices not directly monitored. This allows the system to maintain measurement precision for registered devices while extending coverage to unregistered devices through profile replication.
Solution Approach 2:
The system performs self-service by using existing panelist data and public usage statistics to imputing missing information. Instead of requiring active participation from unregistered devices, the system leverages available data from registered devices and general usage patterns to infer behavior on unmonitored devices. This self-service approach extends measurement coverage without requiring additional active resources or network bandwidth.
Data Source
AI summary
Methods and apparatus are disclosed to measure a cross device audience by determining that a first panelist of a first panel is associated with a first device and a second non-paneled device, requesting participation of the first panelist in a second panel associated with the second non-paneled device, and when the first panelist is to participate in the second panel, associating, by executing an instruction with a processor, first panel data corresponding to usage of the first device in the first panel with second panel data corresponding to usage of the second non-paneled device in the second panel to generate a cross device panelist profile for the first panelist.