Data Fusion for Audience Measurement Using Behavioral Matching
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Solution Overview
Problem
Current internet audience measurement methods provide an incomplete picture of user behavior, as resource access data alone does not account for user intent, affinity, or offline behavior, and there is a lack of integration with detailed survey data, leading to incomplete audience measurement reports.
Innovation Solution
A system and method that combines panel-based and beacon-based data with survey data to create a comprehensive audience measurement by matching users based on demographic and online behavior data, using data fusion techniques to attribute additional user data to users with only partial data sets, thereby generating more detailed and informative reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If resource access data alone is used for audience measurement, then the measurement system is simple, but the completeness of user behavior representation is insufficient
Solution Approach 1:
The patent combines multiple data sources including panel-based data, beacon-based data, and survey data into a unified audience measurement system. This merging of diverse data types enables comprehensive representation of user behavior while maintaining system manageability through integrated processing
2Measurement precision
If detailed survey data is integrated with resource access data, then the accuracy of audience measurement is improved, but the complexity of data processing increases
Solution Approach 1:
The patent introduces user matching as an intermediary process that connects survey data with resource access data. By matching users across different data sources based on identifying characteristics, the system integrates detailed survey information with behavioral data without requiring direct complex processing of all raw data simultaneously
3Manufacturing precision
If user matching based on demographic and behavior data is performed, then the granularity of audience reports is improved, but the computational requirements increase
Solution Approach 1:
The patent segments the user matching process into distinct stages: first matching panel members with beacon data using demographic criteria, then further refining matches with behavioral data. This segmentation allows granular reporting capabilities while managing computational load by processing matches in hierarchical stages rather than all at once
Data Source
AI summary
A first data set associated with a first group of users is accessed. The first data set includes demographic data, online behavior data, and additional user data associated with the users in the first group. A second data set associated with a second group of users is accessed. The second data set includes demographic data and online behavior data but not additional user data associated with the users in the second group. One or more sets of matched users are determined based on the demographic data and online behavior data included in the first data set and the demographic data and online behavior data included in the second data set. Each set includes a user from the first group matched with a user from the second group. Based on the one or more sets of matched users, an augmented second data set that includes additional user data associated with the users in the second group is generated. One or more reports are generated based on the augmented second data set.