Audience Verification Co-Usage Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current digital audience verification systems inaccurately measure demographics due to co-usage of devices, as they assume the device user is the same person associated with the device, leading to errors in audience statistics.
Innovation Solution
The system generates co-usage-adjusted statistics by comparing error estimates from assumption-based approaches with more reliable demographic data obtained directly or indirectly from users at the time of content exposure, using methods such as surveys or authenticated environment data to correct demographic assignments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If device-to-profile associations are used for audience verification, then the system can operate with simple assumptions about user identity, but the accuracy of demographic statistics deteriorates due to co-usage of devices
Solution Approach 1:
The patent segments the audience verification process into multiple independent components: device identification, profile association, co-usage detection, and demographic assignment. By dividing the verification process into these discrete segments, the system can apply different verification strategies to different segments, improving overall accuracy without requiring complete system redesign.
Solution Approach 2:
The patent introduces an intermediary verification layer that mediates between device identification and profile association. This intermediary component analyzes usage patterns and detects co-usage scenarios, acting as a buffer that prevents direct but inaccurate mapping from device to profile, thereby improving demographic accuracy while maintaining system manageability.
2Ease of operation
If the system assumes the device user is the same person associated with the device, then the audience verification process remains simple, but the demographic statistics become inaccurate
Solution Approach 1:
The patent performs preliminary analysis of usage patterns before making demographic assignments. By pre-detecting co-usage scenarios and establishing correction factors in advance, the system maintains simple real-time verification operations while ensuring accurate demographic statistics through pre-computed adjustments.
Solution Approach 2:
The patent implements feedback mechanisms where demographic accuracy is continuously monitored and used to refine verification assumptions. The system collects data on actual usage patterns, compares them with assumed patterns, and adjusts verification logic accordingly, maintaining operational simplicity while improving accuracy through iterative refinement.
3Measurement precision
If co-usage detection and adjustment mechanisms are implemented, then demographic accuracy improves, but system complexity increases
Solution Approach 1:
The patent applies co-usage detection and adjustment mechanisms selectively to specific scenarios where co-usage is most likely to occur, rather than implementing universal complex verification for all cases. By applying adjustments only where needed (partial action), the system improves demographic accuracy in critical areas while avoiding unnecessary complexity in situations where simple assumptions remain valid.
Data Source
AI summary
Techniques are provided for generating adjustment factors, on a per-demographic-group basis, to compensate for errors in audience verification statistics caused by co-usage of devices. The adjustment factors are based on a comparison of (a) per-group counts produced by applying one audience verification approach to a set of exposures, to (b) per-group counts produced by applying another audience verification approach to the same set of exposures. For example, the first per-group counts may be produced under the assumption that the user to whom content is exposed is the owner of the device, and the second per-group counts may be produced by obtaining demographic information directly or indirectly from a user at the time the user is exposed to the content.