Automated User Experience Study System with Validation Filtering
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Solution Overview
Problem
Current methods for assessing user experience on websites are inefficient, expensive, and unreliable, particularly due to biases in user feedback and limited types of feedback collected, which hinders improvements in web design and marketing.
Innovation Solution
A system and method for generating, administering, and analyzing user experience studies that includes participant selection based on demographics, various study types such as card sorting and click tests, and advanced data analysis using machine learning for insights into user behavior and emotions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If focus groups are used to assess user experience, then user feedback can be collected, but the process becomes long, expensive and unreliable due to unrepresentative demographics
Solution Approach 1:
The patent replaces the mechanical human moderator system with automated computer-based systems that administer surveys, conduct user testing, and analyze results automatically. This eliminates the need for manual focus group coordination while maintaining data collection capabilities, thereby reducing both time and cost while improving reliability through standardized automated processes
Solution Approach 2:
The patent changes the demographic parameters of participants by using automated systems to recruit and select users based on specific criteria, ensuring more representative samples. The system can filter and select participants with precise demographic characteristics, replacing the unrepresentative focus group demographics with systematically selected user populations
2Productivity
If mass online surveys are used to collect user feedback, then feedback can be gathered efficiently, but the studies suffer from biases in responses and limited types of feedback collected
Solution Approach 1:
The patent merges multiple feedback collection methods including automated surveys, user testing tasks, behavioral tracking, and experimental conditions into a single integrated system. This combination allows efficient automated data collection while gathering diverse feedback types (self-reported, behavioral, experimental) that reduce response biases and improve overall feedback quality
Solution Approach 2:
The patent introduces automated intermediate systems that mediate between users and researchers, using algorithms to administer surveys, present tasks, track behavior, and analyze results. This intermediary layer eliminates direct human bias in data collection while maintaining efficiency, and the systematic approach ensures more reliable and diverse feedback collection
Data Source
AI summary
Advanced user experience study can be accomplished by enabling recording on a device such as a smart phone, providing a participant with one or more survey questions and a task. Typically, the participants are recorded and redirected to a starting URL. The recording can be terminated when the participant reaches a validation condition. Results, for example, videos, survey results, click flows, and heat maps may be filterable across any participant feature or any study validation criteria. Validation criteria includes time taken to complete a given action, ending up at a particular URL (or class of URLs), based upon question answers, or any combination thereof. These criteria can be classified as either a successful completion of the study, or a failed attempt. Additionally, the validation criteria can also include a decision by the participant to abandon the study.