Ad Engagement Analysis System Using Dwell Time Metrics
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Solution Overview
Problem
Current online systems lack a reliable method to gauge user interest in advertisements, as they do not provide sufficient information on user engagement metrics beyond click-through rates, making it difficult to improve advertisement effectiveness.
Innovation Solution
A system that measures user interaction with ad landing pages using dwell time and bounce rate to provide quality ratings and actionable suggestions for advertisers, focusing on features that can be adjusted to enhance user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional click-through rate metrics are used to measure ad effectiveness, then the measurement process is simple and straightforward, but the ability to gauge genuine user interest and engagement is insufficient
Solution Approach 1:
The patent introduces an intermediary analysis system that acts as a mediator between the advertisement and the user. This system collects and analyzes multiple engagement metrics (dwell time, scroll depth, interaction frequency) to provide a comprehensive assessment of user interest, going beyond simple click-through rates to accurately measure genuine engagement.
Solution Approach 2:
The patent replaces the mechanical simplicity of click-counting with a sophisticated multi-parameter analysis system. Instead of relying on a single binary click event, the system uses multiple measurement dimensions (time-based, interaction-based, engagement-based) to substitute and expand upon the conventional metric, providing richer information about user behavior.
2Loss of information
If no user interaction data is collected beyond clicks, then the system remains simple and data collection is minimal, but no conclusions can be drawn about ad effectiveness or areas for improvement
Solution Approach 1:
The patent implements preliminary data collection mechanisms that automatically capture engagement metrics in the background during user interaction with the advertisement. By pre-configuring tracking of dwell time, scroll behavior, and interaction events, the system gathers comprehensive engagement information without requiring additional user action or manual data collection efforts.
Solution Approach 2:
The system maintains continuous monitoring of user engagement behaviors throughout the entire advertisement interaction period. Rather than relying on discrete, limited events like clicks, the system continuously collects data on all user actions and interactions, ensuring no valuable engagement information is lost during the user's time with the ad.
3Productivity
If advertisers are not provided with actionable feedback, then the system remains simple and advertisers cannot improve their ads, but providing comprehensive feedback would increase system complexity
Solution Approach 1:
The patent implements a feedback mechanism that analyzes collected engagement data and provides actionable recommendations to advertisers. The system identifies specific areas where ads can be improved based on measured user behavior patterns, such as optimizing ad creative elements, adjusting targeting parameters, or modifying landing page content to enhance engagement and conversion rates.
Data Source
AI summary
An online advertising system receives an advertisement from an advertiser. The system analyzes the advertisement, extracts its features and provides to the advertiser a quality rating for the advertisement which depends on a user engagement factor such as the predicted dwell time for the ad, given its features. The system further provides to the advertiser suggestions for improvements to the advertisement, such as a list of actionable guidelines that can improve the expected dwell time of the ad, and likely its conversion rate.