UXCascade: Scalable Usability Testing with Simulated User Agents

2026-01-22

AI Summary

This work addresses the challenge of transforming unstructured feedback from simulated user agents in usability testing into actionable user experience insights. To this end, it introduces UXCascade, an interactive analysis tool that pioneers a multi-level analytical framework integrating user personas, task objectives, and usability issues to link agent reasoning traces with specific interface problems. The system supports exploratory analysis—from macro-level patterns to micro-level refinements—through structured overviews, reasoning trace visualization, annotation views, and interactive editing capabilities. A user study demonstrates that UXCascade effectively integrates into existing UX workflows, facilitating rapid iteration during early design stages and yielding high-value, actionable feedback.

Technology Category

• Humans and AI: User Experience and Usability
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Web Mining and Content Analysis: Bridging structured and unstructured data
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Simulated user agents are increasingly used in usability testing to support fast, iterative UX workflows, as they generate rich data such as action logs and think-aloud reasoning, but the unstructured nature of this output often obscures actionable insights. We present UXCascade, an interactive tool for extracting, aggregating, and presenting agent-generated usability feedback at scale. Our core contribution is a multi-level analysis workflow that (1) highlights patterns across persona traits, goals, and outcomes, (2) links agent reasoning to specific issues, and (3) supports actionable design improvements. UXCascade operationalizes this approach by listing agent goals, traits, and issues in a structured overview. Practitioners can explore detailed reasoning traces and annotated views, propose interface edits, and assess their impact across personas. This enables a top-down, exploration-driven analysis from patterns to concrete UX interventions. A user study with eight UX professionals demonstrates that UXCascade integrates into existing workflows, enabling iterative feedback during early-stage interface development.

Problem

• usability testing
• simulated user agents
• unstructured data
• actionable insights
• UX feedback

Innovation

• simulated user agents
• usability testing
• multi-level analysis
• actionable feedback
• interactive tool