AR Content Usage Data Analysis for Creator Insights
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems and methods provide limited information to augmented reality content creators about the usage of their content items, including limited interaction data and user characteristics, which hinders their ability to tailor content effectively.
Innovation Solution
The implementation of systems and methods that collect and analyze augmented reality content item usage data, including user profile information and interaction metrics, to provide detailed insights to content creators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If detailed augmented reality content item usage data collection and analysis systems are implemented, then content creators gain deeper insights into user interactions and can tailor content more effectively, but system complexity and data processing requirements increase
Solution Approach 1:
The patent introduces an intermediary analysis system that sits between raw usage data collection and content creator access. This intermediary layer processes, aggregates, and analyzes the data to extract meaningful insights while shielding content creators from the underlying system complexity. The intermediary translates complex usage patterns into actionable recommendations, resolving the contradiction by providing detailed information without exposing system complexity.
Solution Approach 2:
The system implements feedback loops where usage data is continuously collected, analyzed, and returned to content creators as actionable insights. This feedback mechanism enables content creators to refine their content based on actual user interactions, creating a closed-loop system that improves content effectiveness while managing complexity through automated analysis pipelines.
2Measurement precision
If comprehensive user profile information and interaction metrics are collected, then content targeting precision improves, but data processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and segmenting user data during collection, organizing it into structured formats with defined schemas. User profiles are pre-aggregated with key attributes, and interaction metrics are categorized in advance. This preliminary structuring enables faster querying and analysis later, reducing processing time when insights are needed without sacrificing measurement precision.
Solution Approach 2:
The system segments user data into distinct categories and dimensions (demographics, behavior patterns, engagement metrics, etc.), allowing for targeted analysis of specific user characteristics. This segmentation enables efficient processing by focusing computational resources on relevant data subsets rather than analyzing all data uniformly, thus reducing overall processing time while maintaining precision in measured attributes.
Data Source
AI summary
Usage metrics for augmented reality content may be identified and analyzed to determine measures of fitness for respective usage metrics. The measures of fitness may indicate a level of correlation with an outcome specified by an augmented reality content creator and an amount of interaction with an augmented reality content item by users of a client application. Recommendations may be provided to augmented reality content creators indicating modifications to augmented reality content items that have at least a threshold probability of increasing the level of interaction between users of the client application and the augmented reality content item.