Virtual Ad Impression Tracking for Multi-User Avatar Engagement
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Solution Overview
Problem
Existing virtual experience platforms face challenges in accurately determining user engagement with digital advertisements, as users may purchase virtual items regardless of advertisement interaction, and simultaneous advertisements for multiple users complicate engagement metrics.
Innovation Solution
Implementing a system to track avatar engagement with digital advertisements by detecting proximity, tracking interactions such as head movements and viewports, and assigning user engagement metrics based on metrics like viewpoint, time spent viewing, and obfuscation of view, while allowing personalized advertisements for each user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If digital advertisements are displayed in virtual experiences, then advertising reach and visibility are improved, but accurate measurement of user engagement becomes difficult
Solution Approach 1:
The system implements feedback by continuously monitoring avatar behavior (proximity, orientation, viewing time) and using this information to adjust and refine engagement metrics. The engagement metric is dynamically calculated based on real-time tracking data, creating a closed-loop measurement system that improves accuracy through continuous validation and adjustment of engagement signals.
Solution Approach 2:
The patent transforms the abstract concept of 'ad engagement' into multiple measurable parameters including avatar proximity to advertisement, orientation angle, viewing duration, and interaction events. By decomposing engagement into these quantifiable parameters, the system can precisely measure and aggregate engagement levels through mathematical calculations of combined parameter values.
2Quantity of substance
If multiple advertisements are served simultaneously to different users, then advertising coverage is improved, but determining individual user engagement becomes complex
Solution Approach 1:
The system segments the advertising measurement system into independent tracking modules, each responsible for monitoring a specific avatar-advertisement interaction pair. By creating separate engagement calculation streams for each user-advertisement combination, the system can simultaneously handle multiple advertisements without cross-contamination of metrics, simplifying the overall complexity through modular independent processing.
Solution Approach 2:
The patent introduces an intermediary engagement metric calculation layer that sits between raw avatar tracking data and final advertising performance reports. This intermediary layer aggregates and normalizes data from multiple simultaneous advertisements, transforming complex multi-source data into standardized engagement metrics that can be easily compared and analyzed across different advertising campaigns.
3Measurement precision
If engagement tracking requires multiple parameters (viewpoint, time, obfuscation), then measurement accuracy is improved, but computational complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing baseline values for engagement parameters such as optimal viewing distances, acceptable orientation ranges, and typical engagement time thresholds. These pre-computed reference values are stored for quick retrieval during real-time tracking, eliminating the need to perform complex calculations from scratch for each measurement and reducing computational overhead while maintaining accuracy.
Data Source
AI summary
Some implementations relate to methods, systems, and computer-readable media for digital advertising within a virtual experience provided at a virtual experience platform. A user's avatar's viewpoint, perspective, time spent viewing, and other attributes are accurately tracked to determine an overall advertising impression. Different advertisements may be displayed to an avatar based on the avatar approaching a digital advertisement element and being within a threshold distance of the digital advertising element. Furthermore, metrics based upon user engagement may be tracked and associated with displayed advertisements.