Ad Search Engine Tile Interface for Context Analytics
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Solution Overview
Problem
Existing web analytics systems provide limited information about user interaction with online advertisements, failing to accurately track ad views and context, leading to incorrect impression metrics and lack of historical data for advertisers.
Innovation Solution
An ad search engine system that includes a click tag parser, rich media parser, ad copy database, request/query processing module, user interface module, and content preservation module, which collects and stores ad placement and context data, allowing for querying and presenting historical ad placement information and user interaction analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing web analytics systems track ad impressions, then advertisers can measure ad delivery, but the information about user interaction and ad context is very limited
Solution Approach 1:
The system segments ad tracking into multiple independent components: impression tracking, user interaction tracking, and context tracking. Each component captures specific information about ad delivery, user behavior, and webpage context separately, allowing comprehensive data collection without overwhelming complexity in any single system element.
Solution Approach 2:
The patent introduces an intermediary data collection mechanism that captures ad context and user interaction information between the ad server and the user's browser. This intermediary layer preserves detailed information about ad placement, surrounding content, and user actions without requiring complex changes to existing ad delivery infrastructure.
2Measurement precision
If existing systems only confirm ad serving, then implementation is simple, but there is no way to determine actual user viewing or interaction
Solution Approach 1:
The system implements feedback mechanisms that detect actual user interaction with ads through click tags and rich media parsers. These feedback loops provide accurate information about whether users actually viewed or interacted with ads, going beyond simple serving confirmation to measure real user engagement and ad effectiveness.
Solution Approach 2:
The patent replaces simple mechanical ad serving confirmation with sophisticated software-based detection mechanisms including click tag parsing and rich media analysis. These software mechanisms can detect user interactions, ad views, and context information through digital signal processing and data parsing rather than relying on basic server logging.
3Productivity
If ads are served automatically based on factors under publisher control, then ad delivery is efficient, but advertisers cannot determine what ads were presented or access historical data
Solution Approach 1:
The system performs preliminary actions by capturing and storing comprehensive ad context information, user interaction data, and performance metrics at the time of ad delivery. This preliminary data collection preserves historical information about what ads were presented, where they appeared, and how users interacted with them, making this information available for later analysis and optimization.
Solution Approach 2:
The patent implements data recovery mechanisms that capture and preserve ad context and interaction information that would otherwise be lost in the automated ad delivery process. By recovering this historical data through systematic data collection and storage, the system enables advertisers to analyze past performance while maintaining efficient automated ad serving operations.
4Loss of information
If detailed ad context and user interaction data are collected, then advertiser insights are improved, but data storage and processing requirements increase
Solution Approach 1:
The system applies local quality by collecting and storing only the specific ad context and interaction information relevant to each individual ad impression. Rather than uniformly collecting all possible data across all ads, the system focuses data collection on the specific elements actually present and interacted with during each ad delivery event, optimizing the balance between information quality and data volume.
Data Source
AI summary
An ad search engine comprises a click tag parser, a rich media parser, an ad copy database, a request/query processing module, a user interface module and a content preservation module. The ad search engine advantageously receives and stores information about ad placement, context and advertising statistical and metadata in the ad copy database. In response to a query, the request/query processing module searches the ad copy database for advertisements matching the input query. The user interface module receives the results and presents them in a novel user interface composed of an array of tiles where each tiles represents a placement of the advertisement. The present invention also includes a several novel methods including a method for displaying ad search results, a method for generating an ad search result user interface, a method for populating an ad database, a method for ad preservation and a method for generating derived insights.