User-Controlled File Interaction for Ad Targeting
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Solution Overview
Problem
Conventional online advertising techniques have low returns on investment, lack user control, and are ineffective in gathering accurate user feedback for targeted advertising, making it difficult to determine user preferences and campaign effectiveness.
Innovation Solution
A user-controlled file interaction system that allows users to interact with advertisements through ratings and vetoes, using a network architecture with an ad server, reporting system, and ratings application to collect and analyze user input, enabling personalized advertisement selection and campaign performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional online advertising techniques are used to present advertisements, then advertisements can be displayed to users, but user control over advertisement presentation is lacking and response rates remain very low
Solution Approach 1:
The patent implements a feedback mechanism where users can rate advertisements and provide input about their preferences. This feedback is then used to adjust future advertisement presentations, creating a closed-loop system that continuously improves based on user responses. The feedback module collects user ratings and uses them to modify advertisement selection algorithms, directly addressing the lack of user control while aiming to improve response rates through personalized content.
Solution Approach 2:
The advertisement presentation system transitions from a static, one-size-fits-all approach to a dynamic, adaptive system. The advertisement selection is no longer fixed but changes based on user feedback, time, context, and individual user profiles. This dynamic adjustment allows the system to respond to user preferences in real-time, enhancing user control while potentially improving engagement and response rates.
2Loss of information
If conventional advertising techniques gather user feedback through data mining, then some information can be collected, but the process is expensive, time-consuming, and lacks accuracy
Solution Approach 1:
The system enables users to directly provide feedback through rating mechanisms and preference inputs without requiring extensive external data mining operations. Users self-report their advertising preferences and experiences, eliminating the need for costly and time-consuming third-party data collection and analysis. This self-service approach improves feedback accuracy by capturing direct user sentiments while significantly reducing the time and resources required for data gathering.
3Measurement precision
If conventional techniques target advertisements using standard methods, then advertisements can be displayed, but targeting effectiveness is poor and returns on investment are low
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing user feedback, ratings, and preference data before selecting and presenting advertisements. This advance preparation allows the system to pre-process user information, build detailed user profiles, and predict user preferences in advance. By doing this preliminary work, the system improves targeting accuracy when advertisements are actually presented, ensuring that the right ads reach the right users at the right time, thereby reducing wasted advertising investment.
Data Source
AI summary
User-controlled file interaction is described, including detecting an interaction with a file presented on a client, the interaction indicating a preference associated with the file, selecting other files for presentation based on the preference, the other files being similar to the element, and presenting the other files on the client.