Virtual User Model Simulation for Web Experience Testing
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Solution Overview
Problem
Current methods for testing and optimizing user experiences on websites and applications are costly and prone to human error, lacking a practical way to simulate user interactions before implementation, making it difficult to identify improvements.
Innovation Solution
A computer-implemented method using a virtual user model defined by user intent parameters, simulated through a probabilistic network to replicate user interactions, measure statistically relevant information, and analyze results for conversion rates and other metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human users are hired to conduct testing prior to implementation, then user experience effectiveness can be measured, but testing costs increase and human errors may occur
Solution Approach 1:
The patent creates virtual human models that copy and simulate real human user behaviors, intentions, and interactions with the application. These virtual models replicate user decision-making processes, navigation patterns, and conversion behaviors without requiring actual human testers, thereby reducing costs while maintaining measurement accuracy.
Solution Approach 2:
The patent replaces the mechanical system of human users physically interacting with the application with an automated computational system. The virtual human models use algorithms and probabilistic networks to simulate user interactions, substituting human mechanical actions with automated digital simulations that eliminate human errors and reduce testing costs.
2Loss of information
If human users are hired to conduct testing prior to implementation, then user experience feedback can be obtained, but the testing process becomes susceptible to human errors
Solution Approach 1:
The virtual human models copy realistic user behaviors and decision-making processes while eliminating human errors. The models simulate authentic user interactions including navigation, product selection, and conversion behaviors without the susceptibility to human mistakes, providing reliable feedback data.
Solution Approach 2:
The system performs self-testing through automated virtual human models that independently interact with the application. The models autonomously execute testing scenarios, collect data, and generate feedback without human intervention, ensuring consistent and error-free testing procedures.
3Measurement precision
If a fully built website or application is required for testing, then comprehensive user experience testing can be performed, but development time and costs increase
Solution Approach 1:
The patent enables preliminary user experience testing by simulating user interactions with the application before full implementation. Virtual human models can test and provide feedback on application concepts, prototypes, or partial implementations, allowing developers to identify and correct issues early in the development process without waiting for complete builds.
Solution Approach 2:
The virtual human models create simplified copies of real user interactions that can be performed on application prototypes or wireframes. This copying approach allows comprehensive testing of user flows and interactions without requiring the full production-ready application, saving development time while maintaining testing value.
4Loss of information
If sufficient human user testing is conducted, then user experience insights can be gathered, but it becomes difficult to identify specific changes needed for improvement
Solution Approach 1:
The virtual human model system implements automated feedback mechanisms that track and analyze user interactions at each step of the application flow. The system provides detailed feedback on conversion rates, drop-off points, and user behavior patterns, automatically identifying specific changes needed for improvement without requiring complex manual analysis of human testing data.
Solution Approach 2:
The patent replaces complex manual analysis of human testing data with automated computational analysis. The system uses algorithms to process virtual user interaction data, automatically identifying patterns, bottlenecks, and optimization opportunities, thereby reducing analysis complexity while maintaining insight quality.
Data Source
AI summary
Computer-implemented methods of using artificial intelligence (AI) to simulate user experiences with websites or applications can be used to improve the design and functions of computing systems supporting the platform for the website or application. The methods may involve one or more of the following: creating models of virtual users defined by parameters characterizing intent, identifying user options provided by the websites or applications, generating probabilistic networks defining transition dependencies between the identified options, and simulating the user experiences with websites or applications based on the user models.