Search Query Statistical Data Compilation for Ad Campaign Optimization
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Solution Overview
Problem
Advertisers face challenges in optimizing their advertising campaigns due to a lack of effective tools for analyzing user search query data, which limits their ability to refine their ad targeting and keyword strategies based on actual user behavior and ad performance metrics.
Innovation Solution
A computer-implemented method and system that compiles and provides search query information, including ad performance data, to advertisers, allowing them to identify successful search queries and modify their keyword lists based on user-selected criteria such as exact, phrase, or broad matches, and receive statistical data for improving ad campaign performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If advertisers manually analyze user search query data without automated tools, then they can understand user behavior patterns, but the process is time-consuming and lacks precision in measuring ad performance metrics
Solution Approach 1:
The patent replaces manual mechanical analysis of search query data with an automated computer-implemented system that collects, processes, and analyzes ad performance metrics. The system automatically matches user search queries with advertiser keywords, tracks impressions and click-throughs, and generates performance reports, eliminating the need for manual data collection and analysis while providing precise measurements of ad campaign effectiveness.
2Quantity of substance
If advertisers use broad keyword matching to increase ad visibility, then ad impressions increase, but ad relevance to specific user queries decreases
Solution Approach 1:
The patent segments keyword matching into three distinct levels: exact match (query must exactly match keyword), phrase match (query must contain the keyword phrase), and broad match (query relates to the keyword conceptually). This segmentation allows advertisers to choose the appropriate match type for each keyword, balancing between obtaining sufficient impressions and maintaining relevant matches. The system tracks performance metrics for each match type separately, enabling precise measurement of how each segmentation level performs.
3Loss of information
If advertisers collect detailed search query data for analysis, then they gain insights into user behavior, but data privacy and user identification risks increase
Solution Approach 1:
The patent extracts and removes personally identifiable information (PII) from collected search query data before analysis and storage. The system anonymizes user identifiers, IP addresses, and other sensitive information while retaining the essential search query text and ad performance metrics needed for analysis. This extraction of harmful identifying elements allows the system to maintain detailed user behavior information for campaign optimization without exposing individual user identities or sensitive personal data.
Data Source
AI summary
Techniques for determining search query information for an advertising campaign and communicating the search query information to a sponsor of the advertising campaign are described. The techniques include receiving, from a sponsor of the advertisement, a request for search query information relating to the advertisement having been presented by a search service, identifying previously executed search queries submitted by users of the search service, wherein search results of the identified search queries have been presented with the advertisement to one or more users of the search service, compiling search query information, the search query information including ad performance data associated with the advertisement for the identified search queries, and providing the sponsor with the compiled search query information. A user interface may be generated to receive user input of selection criteria and provide an interface to search query information.