Partial Query Ad Matching System for Relevance and Privacy
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Solution Overview
Problem
Current web advertising models, such as banner advertising, inefficiently utilize the Internet's direct marketing potential, often displaying irrelevant ads to users, leading to low click-through rates and failing to reach interested individuals, while also raising privacy concerns through invasive data collection and usage.
Innovation Solution
A computer-implemented system that uses a matching unit to analyze partial query terms input by users and match them with a predefined keyword database, creating lists of relevant keywords and associated listings, which are then used to display targeted advertisements before the user completes their search query, utilizing factors like user, advertiser, product, and rule factors to ensure relevance and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If banner advertising is displayed on web pages, then advertisement exposure is achieved, but click-through rate is low due to irrelevant ads
Solution Approach 1:
The system performs preliminary matching of user search queries with advertisement keywords before the user completes their search. By analyzing partial query terms in real-time and pre-selecting relevant ads based on matched keywords, the system ensures ad relevance is established before the user finishes typing, thereby improving click-through rates while maintaining privacy by not requiring complete search history
Solution Approach 2:
The system introduces a matching unit as an intermediary between the search engine and advertisement delivery system. This matching unit analyzes user queries, matches them with predefined keyword databases, and selectively delivers relevant advertisements. The intermediary function ensures ads are relevant without requiring invasive data collection about user behavior patterns
2Measurement precision
If targeted advertising is implemented through invasive data collection, then ad precision is improved, but user privacy is compromised
Solution Approach 1:
The system applies partial action by analyzing only the partial query term that the user has already typed, rather than requiring complete search history or extensive personal data. This partial analysis is sufficient to match relevant keywords and deliver targeted ads without needing excessive user information, thereby maintaining targeting accuracy while preserving privacy
Solution Approach 2:
The system allows users to self-identify their information needs through their own search queries. By matching ads to the user's explicit search intent rather than inferring from hidden behavioral data, the system achieves targeted advertising through the user's own actions without requiring invasive data collection or monitoring
3Productivity
If advertisements are displayed before query completion, then user engagement is improved, but system complexity increases
Solution Approach 1:
The system segments the advertisement delivery process into distinct components: a predefined keyword database, a matching unit that analyzes partial queries, and a delivery mechanism. This segmentation allows real-time ad display during search without requiring complex integrated systems, as each component performs a specific function independently
Solution Approach 2:
The system changes the parameter of ad delivery timing from traditional post-search display to real-time display during query input. By implementing this parameter change and using predefined keyword databases with automated matching, the system achieves early ad delivery without proportionally increasing complexity, as the matching logic operates on simple keyword comparison rather than complex analysis
4Quantity of substance
If impression-based advertising is used, then advertisement coverage is maximized, but marketing efficiency is reduced
Solution Approach 1:
The system implements feedback by continuously monitoring user search queries and dynamically adjusting ad delivery based on matched keywords. This feedback loop ensures ads are delivered to users actively searching for relevant products or services, maximizing both coverage and efficiency by targeting users who have demonstrated intent through their search behavior
Data Source
AI summary
A computer-implemented system to determine and display advertisements to a remote computer. The system may include one or more servers, a data store, a processor, a controller, a predefined matching keyword database, a product listing advertisement (PLA) database, and a matching unit. The matching unit may receive a partial query term inputted into a search access point. The matching unit may match the partial query term to create a list of matching keywords, perform a keyword relevancy process, create a list of top matched keywords, match the top matched keywords with associated listings, perform an associated listing relevancy process, create a list of top associated listings. The matching unit may send the list of top associated listings to display advertisement elements adjacent the search access point upon receipt of the partial query term and prior to completion of entry of the whole query term.