My Current UX Research Toolkit & Workflow

This document outlines the tools, platforms, and workflows I use to design, execute, and analyze user experience research. My toolkit is built for hybrid AI + biometric testing, rapid iteration, and minimal friction between concept, test, and result.

tools

1. Selection Criteria for Tools

Integration — Must plug directly into my testing ecosystem without hacks.
Efficiency — Reduces steps from idea to validated result.
Accuracy — Captures or analyzes data without distortion or excessive interpretation bias.
Portability — Works seamlessly across my main macOS setup and mobile workstation.

2. Core Tool Categories

Research & Testing

Eye Tracking: Tobii Eye Tracker 5 for heatmaps and gaze plotting
EEG Capture: Muse 2 for emotional/cognitive load monitoring
GSR Sensor: WHOOP Life for physical stress response logging
UX Simulation: Blindfold (in development) for accessibility testing

AI-Assisted Analysis

UXray (in development) — AI-driven heatmap + attention prediction engine
Local Models: Devstral 30B, IBM Granite for offline, private data processing
Data Crunching: CoreML for visual reporting

Design & Prototyping

Framer: Wireframes + collaborative prototyping
Spline: 3D interactive UI concepts
Unity: Vector-based assets for reports and UI elements
Photomator: Apple based photoshop editing application
Pixelmator: Apple based vector visual design tool
Motion: Apple based vector motion design editor

Automation & Orchestration

Raycast: Global shortcuts for launching research workflows
n8n: Conditional automation between data collection and processing pipelines

3. Workflow: From Idea to Insight

1. Define research question in Obsidian → Assign tags (#cognitive, #accessibility, #conversion)

2. Build or adapt test scenario in Figma/Spline

3. Configure biometric devices and open analysis container in Docker

4. Conduct test session (AI + human observation)

5. Export datasets → Run automated preprocessing scripts

6. Generate heatmaps, EEG trend lines, and user flow overlays

7. Summarize findings in Documentation site under “Experiments”

4. Why This Workflow Works

This toolkit is not about having the most tools — it’s about having the right mix so data moves frictionlessly from raw capture → processed insight → published documentation. Every tool here exists to shorten the distance between question and proof.

The AI-Enhanced UX Research Toolkit ›