User Frustration Detection for Mobile Device Experience Optimization
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Solution Overview
Problem
Current methods for evaluating user experience on mobile devices are often network-based and delayed, failing to promptly address user frustration, which can lead to non-productive actions and suboptimal device performance.
Innovation Solution
A system and method that detect user frustration events, associate them with device events, and transmit event packages to provide immediate feedback, allowing for improved user experience evaluation and service optimization by identifying and addressing causes of frustration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If network-based evaluation methods are used, then system resources are reduced, but user feedback is delayed and response time increases
Solution Approach 1:
The device performs preliminary actions by detecting user frustration events and associating them with device events before transmitting the event package. This allows the system to prepare feedback data in advance at the device level, reducing the overall feedback delay without requiring complex continuous monitoring infrastructure.
Solution Approach 2:
The device serves itself by autonomously detecting frustration events, determining associated device events, and forming event packages for transmission. This self-service capability eliminates the need for continuous network-based monitoring, reducing feedback delay while keeping device complexity manageable through targeted rather than continuous processing.
2Measurement precision
If continuous monitoring of user experience is implemented, then user feedback quality improves, but device energy consumption increases
Solution Approach 1:
Instead of continuous monitoring, the system applies partial action by detecting only specific frustration events that meet certain criteria. This selective approach maintains measurement precision for critical user experience issues while significantly reducing device energy consumption compared to continuous monitoring of all user interactions.
Solution Approach 2:
The system uses feedback by transmitting event packages that contain both user frustration event indicators and associated device event indicators. This feedback mechanism provides accurate user experience evaluation by linking frustration events to specific device operations, enabling precise measurement without requiring continuous energy-intensive monitoring.
3Measurement precision
If detailed event packages are transmitted, then feedback accuracy improves, but network bandwidth consumption increases
Solution Approach 1:
The event package is segmented into distinct components: user frustration event indicators and associated device event indicators. This segmentation allows the system to transmit only the necessary detailed information for accurate feedback without including redundant data, thereby improving feedback accuracy while controlling network bandwidth consumption.
Solution Approach 2:
The system applies parameter changes by selectively including specific event indicators in the event package based on the detected frustration event type and associated device events. This approach optimizes feedback accuracy by including only relevant parameters, reducing unnecessary network energy consumption while maintaining precise user experience evaluation.
Data Source
AI summary
Implementations and techniques for measuring and improving the quality of a user experience are generally disclosed.