URL Tagging for Accurate Audience Measurement
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Solution Overview
Problem
Current audience measurement methods face challenges in accurately tracking internet media usage due to issues like over-counting and under-counting, tampering with server logs, and limitations in using third-party cookies, which affect the reliability of audience demographics and targeted advertising.
Innovation Solution
The proposed solution involves using a system that collects and processes URL information from user browsing behavior to assign features to users, leveraging cloud storage and natural language processing to generate dynamic rules for tagging users, and building look-a-like models to improve audience measurement and targeted advertising without relying heavily on third-party cookies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If server logs are used for audience measurement, then data collection is straightforward, but accuracy deteriorates due to over-counting, under-counting, and tampering
Solution Approach 1:
The patent introduces URL tagging as an intermediary mechanism between server logs and audience measurement. By tagging URLs with unique identifiers and tracking their propagation through web requests, the system creates a reliable chain of evidence that prevents tampering and accurate counting, while maintaining ease of implementation through standard web protocols
Solution Approach 2:
The patent creates copies of URL identifiers embedded in web requests and responses. These copied identifiers travel through the web request chain, allowing multiple servers to independently verify the same user session without relying on centralized log management, thereby preventing tampering and over-counting
2Adaptability or versatility
If third-party cookies are used for tracking, then user behavior can be tracked across sites, but reliability deteriorates due to cookie limitations and privacy restrictions
Solution Approach 1:
Instead of tracking users through cookies stored on client devices, the patent inverts the approach by embedding tracking identifiers in server-controlled URLs. The tracking information flows from server to server through web requests, making it server-reliant rather than client-reliant, thereby eliminating cookie-related reliability issues while maintaining cross-site tracking capability
Solution Approach 2:
The patent replaces the mechanical cookie-based tracking system with a URL-based tracking system. By substituting the cookie mechanism with URL parameter propagation, the system eliminates dependencies on browser cookie storage, privacy settings, and third-party cookie restrictions, thereby improving reliability
3Measurement precision
If detailed URL information is collected for feature tagging, then user demographics accuracy improves, but computational resources increase
Solution Approach 1:
The patent extracts only the essential URL components needed for feature tagging, such as domain names, path segments, and query parameters, while discarding redundant information. By selectively extracting relevant features from URLs, the system maintains high demographic accuracy while minimizing computational processing requirements
Data Source
AI summary
Methods, apparatus, systems, and articles of manufacture are disclosed to extract information from uniform resource locators (URLs). An example system includes at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to collect first uniform resource locator (URL) information from a server of an Internet-based media publisher, the first URL information corresponding to first media accessed by first users, determine first URL components in the first URL information, and determine feature-to-user assignment rules based on the first URL components.