Hybrid Census User Measurement System
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Solution Overview
Problem
Current media measurement and analytics solutions are limited by their reliance on single data sources, such as panel studies or user surveys, which are costly, subjective, and fail to provide holistic, objective data on Internet ecosystem dynamics, including hardware, content, and user behavior across multiple devices and interfaces.
Innovation Solution
A system that integrates user-centric and network-centric data through a multi-screen framework, using a combination of passive metering, census-level data, and metadata processing to provide comprehensive, scalable, and accurate metrics on device usage, content distribution, and user behavior, enabling strategic decision-making in the digital marketplace.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If panel studies with dedicated devices or software meters are used to measure user behaviors, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts the measurement function from complex dedicated panel devices and implements it through lightweight software meters and embedded tags that can be deployed on existing user devices without requiring specialized hardware infrastructure
Solution Approach 2:
The measurement system is designed to work across multiple device types and platforms (mobile phones, tablets, PCs, smart TVs) using universal software components rather than device-specific measurement tools, enabling broad coverage without proportional increases in system complexity
2Ease of operation
If traditional user surveys or interviews are conducted to understand user behaviors, then ease of operation is improved, but measurement precision deteriorates due to respondent subjectivity
Solution Approach 1:
The patent replaces the mechanical human interview process with automated software meters and embedded tags that objectively record user behaviors through device sensors and application programming interfaces, eliminating respondent subjectivity while maintaining ease of deployment
Solution Approach 2:
The measurement system enables devices and applications to automatically collect and report their own usage data without requiring human intervention or subjective user input, with the software meters autonomously tracking behaviors through device sensors and event logs
3Ease of manufacture
If SDKs and tags are deployed to collect data on participating properties, then ease of manufacture is improved, but measurement precision worsens due to limited coverage
Solution Approach 1:
The patent merges multiple data collection approaches by integrating software meters that run on individual devices with census-level data from network carriers and content distribution platforms, creating a hybrid system that combines the granularity of device-level tracking with the comprehensiveness of population-wide data
4Measurement precision
If a hybrid census and user based measurement methodology is implemented, then measurement precision and scope are improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the measurement system into distinct functional components: software meters for device-level data collection, embedded tags for content-level tracking, and census data aggregation from external sources, allowing each component to be developed and maintained independently while contributing to the overall hybrid measurement framework
Data Source
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AI summary
System (100, 108, 110), such as a number of servers (108), for obtaining and analyzing data on online user behavior and other activity having regard to Internet connectable user devices, optionally mobile devices, the system being configured to collect (404, 408) data from a plurality of data sources, wherein said collected data includes at least individual user-level data acquired from user devices (104, 104a, 104b, 105, 217, 402) and census-level data (107a, 211) indicating behavior and demographic characteristics across the entire population of users, active devices, or measured services, with said user-level data being preferably collected using at least one user research panel (216) of controlled constitution, further preferably from multiple devices of each participant in the user panel, said collected data being indicative of Internet, content, media, application, and/or device usage, organize (406) the obtained user-level and census-level data into a preferably multivalent categorized data set utilizing an ontological metadata schema, determine an electronic deliverable (112, 206, 416) based on an integration of the user-level data and census-level data wherein census-level data is utilized to calibrate user-level data, the deliverable having a dynamically selectable, preferably user-selectable, scope in terms of a number of interest factors regarding used devices or online behaviors, preferably including application usage, application distribution, content usage, content distribution, application monetization, user demographics, device distribution, device characteristics, device usage, and/or time factors.