Digital Ad Ratings Data Quality Triage via Weighted Scoring
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Solution Overview
Problem
Current methods for determining unique audience size and impression frequency in digital ad ratings are inadequate, as they cannot reliably identify individuals across multiple impressions and lack accurate demographic information, leading to incomplete and inaccurate audience measurement data.
Innovation Solution
The solution involves sharing demographic information between audience measurement entities and database proprietors, allowing for the comparison and aggregation of impression data to generate final weight scores for improved data quality analysis and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional panel member monitoring methods are used to determine audience exposure, then implementation complexity is reduced, but measurement precision and reliability of audience measurement data deteriorate
Solution Approach 1:
The patent combines data from multiple sources including panel member monitoring, census data collection, and database proprietor information into a unified audience measurement system. This integration allows the system to leverage the simplicity of panel monitoring while supplementing it with broader census data and demographic information from database proprietors, thereby improving measurement precision without proportionally increasing implementation complexity
Solution Approach 2:
The patent introduces database proprietors as intermediary entities that provide demographic information and data quality scores. These intermediaries bridge the gap between simple impression counting and complex demographic analysis, enabling the system to obtain accurate audience characteristics without directly implementing complex monitoring infrastructure for all users
2Measurement precision
If census data collection is expanded to improve audience measurement accuracy, then measurement precision improves, but loss of time and processing overhead increase
Solution Approach 1:
The patent implements preliminary action by having database proprietors pre-calculate and store data quality scores, demographic information, and impression data before they are needed for audience measurement. This pre-processing allows the audience measurement entity to quickly retrieve and utilize high-quality data without performing time-consuming calculations in real-time, thus improving measurement precision while minimizing processing time delays
Solution Approach 2:
The patent applies local quality by selectively processing and analyzing only the most relevant and high-quality data points. The system uses data quality scores to identify and prioritize reliable impressions, focusing computational resources on processing high-value data rather than uniformly processing all collected data, thereby improving accuracy while reducing overall processing time
3Reliability
If data quality analysis is performed on all impression data points, then reliability of audience measurement improves, but device complexity and processing requirements increase
Solution Approach 1:
The patent extracts and utilizes data quality scores that are pre-calculated by database proprietors. By taking out this quality assessment function and placing it at the data source rather than implementing it centrally in the audience measurement entity, the system improves reliability through comprehensive data quality analysis while avoiding the complexity of building and maintaining such analysis infrastructure
Solution Approach 2:
The patent implements self-service by enabling database proprietors to automatically generate and provide data quality scores, demographic information, and validated impression data. This allows the data source to serve itself by performing quality assessment and preparation, reducing the burden on the audience measurement entity while improving the reliability of the data received
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture to identify and triage digital ad ratings data quality issues includes processor circuitry to generate an aggregate factor score based on aggregate data from a first impression data point, the first impression data point including the aggregate data and duration data corresponding to a duration of time; determine a duration factor score based on the duration data from the first impression data point; determine a final weight score for the first impression data point using a normalized aggregate factor score and a normalized duration factor score for the first impression data point, the normalized aggregate factor score corresponding to aggregate factor scores of a second impression data point, the normalized duration factor score corresponding to duration factor scores of the second impression data point; and when the final weight score does not satisfy a threshold score.