Aggregate GUI Activity Analysis for User Engagement Measurement
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Solution Overview
Problem
Existing trading platforms suffer from high latency, inaccurate market insights, lack of personalized support, and insufficient liquidity, impacting efficient and profitable decision-making by traders.
Innovation Solution
A method and system for determining user engagement through graphical user interface interactions by collecting, analyzing, and displaying aggregate user activity data to enhance decision-making and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If trading platforms use existing solutions for market insights, then the platform can operate with current technology, but the accuracy of market insights is compromised due to reliance on trader's own data and history
Solution Approach 1:
The patent introduces an intermediary system that collects and analyzes user interaction data from multiple traders to generate market insights. This intermediary layer aggregates data from diverse user behaviors and interactions, filtering out individual biases and providing objective, aggregated market intelligence that improves accuracy while maintaining adaptability to various trading contexts
2Ease of operation
If trading platforms provide personalized support based on individual trader data, then user experience is improved, but the system complexity increases
Solution Approach 1:
The patent segments user interaction data into distinct categories and dimensions (e.g., navigation patterns, interaction frequency, feature usage). This segmentation allows the system to process and analyze data in manageable portions, generating personalized insights without requiring complex unified analysis. The segmented approach reduces computational complexity while enabling tailored support for individual traders
3Measurement precision
If trading platforms aggregate user interaction data to determine engagement, then market insights accuracy is improved, but data privacy concerns increase
Solution Approach 1:
The patent applies local quality analysis by examining specific localized patterns in user interaction data rather than analyzing entire datasets globally. The system identifies meaningful engagement patterns within specific contexts (e.g., particular feature interactions, time-based patterns) while maintaining data minimization. This localized approach improves engagement measurement accuracy for specific scenarios while reducing the exposure of sensitive personal information, thereby mitigating privacy risks
Data Source
AI summary
Disclosed is a method for determining user engagement based on user interactions. The method comprising collecting via a communication network (304), user-interaction data representative of the user interactions of a plurality of users with a graphical user interface (GUI) (204, 306) executed at a corresponding plurality of user devices (202A-C, 308A-F); analyzing the user-interaction data to determine an aggregate user activity within the GUI; and displaying an indication of the aggregate user activity within the GUI to a given user at a given user device (308F) from amongst the corresponding plurality of user devices, for determining the user engagement.