Targeted Advertising via Thumbnail Response Matching
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Solution Overview
Problem
Existing targeted advertising methods, such as behavioral and contextual advertising, require understanding and analyzing user content in real-time, which is time-consuming and costly, often failing to provide highly relevant advertisements.
Innovation Solution
Displaying advertising content to users based on their responses to questions provided upon selecting thumbnails, with the option to receive and generate statistical information from previous users' responses to provide targeted content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If behavioral or contextual advertising methods are used to analyze user content in real-time, then advertising relevance to user interests can be improved, but time consumption and costs increase significantly
Solution Approach 1:
The system pre-generates multiple candidate advertisements and their associated metadata (keywords, categories, tags) before user interaction. When a user selects a thumbnail, the system quickly matches the user's selection against the pre-prepared advertisement database using simple keyword comparison rather than real-time content analysis, thereby reducing time consumption while maintaining advertising relevance.
Solution Approach 2:
Instead of analyzing the actual content of each thumbnail in real-time, the system creates simplified copies or representations of the content in the form of pre-extracted keywords, tags, and metadata. These copies enable fast comparison and matching with advertisement databases without requiring complex real-time content understanding, thus reducing time consumption while preserving advertising relevance.
2Measurement precision
If behavioral or contextual advertising methods are used to analyze user content in real-time, then advertising relevance to user interests can be improved, but costs increase significantly
Solution Approach 1:
The system performs content analysis and generates advertisement matching rules in advance, storing the results in a database. This preliminary processing shifts the computational burden from real-time operations to offline batch processing, significantly reducing the costs associated with real-time content analysis while maintaining high advertising relevance through pre-computed matches.
Solution Approach 2:
The system uses simple, lightweight matching algorithms and data structures (such as keyword lists and tag arrays) instead of complex AI models for real-time advertisement selection. These simple matching mechanisms are computationally inexpensive and can be quickly executed, reducing the costs of real-time advertising delivery while maintaining sufficient relevance through effective keyword and tag matching.
3Measurement precision
If content understanding and analysis are performed in real-time, then advertising relevance can be improved, but system complexity increases
Solution Approach 1:
The system divides the advertising delivery process into distinct segments: (1) offline content analysis and keyword extraction from thumbnails, (2) pre-generation of advertisement candidates with their metadata, and (3) simple real-time matching based on user selection. This segmentation transforms a complex real-time content analysis task into simpler, more manageable components, reducing system complexity while maintaining advertising relevance.
Solution Approach 2:
The system introduces an intermediary layer of pre-extracted keywords, tags, and metadata that mediates between the user's thumbnail selection and the advertisement database. Instead of directly analyzing thumbnail content in real-time, the system uses these intermediary data structures to facilitate fast matching, thereby reducing system complexity while preserving advertising relevance through effective intermediate representation.
Data Source
AI summary
Methods and computer-readable media for presenting a user with advertising content, such as an advertisement or coupon, based on the user's responses to one or more questions are provided. A user may view a web page that includes one or more thumbnails, where each thumbnail represents a media, such as a video clip, an audio clip, or an image. Once a user selects a thumbnail, by hovering a cursor over the thumbnail, for example, a question may appear over the thumbnail. The user may respond to the question, and based on the response, may be provided with some form of relevant advertising content. Subsequent questions may be presented to the user if the user selects more than one thumbnail in a session, and thus the user may be provided with highly relevant advertising content that is based on responses to more than one question.