AI-Based UX Test Analysis Automation

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Solution Overview

Problem

User experience (UX) testing often requires significant time and expertise to extract key findings from test results, leading to sub-optimal product design choices and inefficient resource use, whether conducted in-house or by third-party service providers, who may struggle to identify relevant insights amidst manual and costly analysis processes.

Innovation Solution

The implementation of AI-based systems using generative language models to automate the analysis of UX test results, reducing processing overhead and providing actionable insights by crafting prompts, interacting with the models, and integrating their outputs into structured analyses, enabling faster product design improvements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual analysis methods are used to extract key findings from UX test results, then expertise and time investment are required, but the process becomes inefficient and resource-intensive

Engineering Contradiction:

Improvequality of test result analysisVSAvoidefficiency of analysis process

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent replaces manual mechanical analysis processes with an AI-based automated analysis system. The system uses machine learning models to process UX test results, substituting human researchers' manual work with automated computational processes that can analyze data faster and at lower cost while maintaining or improving analysis quality.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The AI-based analysis system enables self-service by automatically processing UX test results without requiring human researchers to manually analyze each dataset. The system autonomously extracts key findings, identifies patterns, and generates actionable insights, allowing organizations to independently analyze their own test results without external expertise.

Inventive Principle:

Principle #25Self-service

2Reliability

If third-party service providers are used to perform UX testing, then expertise is leveraged, but the analysis process becomes expensive and cumbersome

Engineering Contradiction:

Improvequality of test administrationVSAvoidcomplexity of analysis process

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent creates a universal analysis system that can handle multiple types of UX test results from different testing methodologies and providers. The AI-based system is designed to process various formats and types of test data, making it adaptable to different testing scenarios and reducing dependency on specific third-party providers.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent extracts the analysis function from the test administration process. Instead of requiring third-party providers to perform both testing and analysis, the system separates these functions by enabling organizations to administer tests themselves and then use the AI-based system to automatically analyze the results, simplifying the overall process.

Inventive Principle:

Principle #2Taking out (Extraction)

3Loss of information

If comprehensive UX test analysis is performed manually, then detailed insights can be obtained, but the time from testing to design improvements increases

Engineering Contradiction:

Improvecompleteness of key findingsVSAvoidtime to implement design improvements

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The AI-based analysis system enables continuous processing of UX test results without the interruptions and delays inherent in manual analysis. The system can automatically process results as they become available, continuously extracting insights and enabling faster iteration cycles for product design improvements.

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The system performs preliminary analysis actions automatically upon receiving test results, immediately extracting key findings and identifying actionable insights before human researchers can manually review the data. This preliminary automated analysis reduces the overall time required to translate test results into design improvements.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12169803B2Systems and methods for automating comparative user experience test analyses

Publication Date: 2024.12.17 WEVO INC

AI summary

Techniques are described herein for using artificial intelligence (AI) and machine learning (ML) to automate, accelerate, and enhance various aspects of comparative user experience testing. Embodiments interface with generative language models to compare user experiences and summarize the results of the comparison. In some embodiments, automated systems and programmatic processes access a series of analysis contexts, where a context includes a collection of message content fragments. The systems and processes may use the message content fragments for a given context to construct a dialogue with a generative language model to compare separate user experiences based on the results of a set of user experience tests. The output of the generative language model at one stage of the analysis may be combined with content fragments for another context to craft a dialogue at another stage of the analysis and/or to perform additional analyses of the user experiences.