Design a rigorous protocol in minutes, not weeks
Compose structured study protocols from a library of scenario blocks — questions, prototype tasks, preference tests, rating scales, and more — with AI-assisted study descriptions built in.
Sections
Language
Gift Shopping UX Study
Section 1: Homepage Experience
Walk me through how you usually shop for gifts online.
Find headphones and go through checkout as if buying them as a gift.
You paused at the top right — what did you expect to find there?
1 to 5 — how confident did you feel completing that checkout?
Scenario blocks
Every scenario type you need, in one library
Protocols are composed of blocks. Click any type below to see exactly what participants experience during the session.
When navigating through our website, how many items have you observed and were fitting your needs? How did you find the information you needed about the product?
Respond orally
Your answer is captured as the call is recorded
Participant view — live session interface with real-time video feed and AI transcription
AI-assisted setup
A complete study context, generated in seconds
Describe your research question in plain language and let the AI agent structure it into a complete study brief — problem statement, domain, background context, and primary and secondary objectives — ready to review and refine.
- Two modes — Type freehand or generate from a plain-language prompt.
- Confidence signals — Each field is flagged Complete, Partial, or Low confidence.
- Always editable — Adjust any field inline or re-prompt anytime. Auto-saved.
The agent will use your study description above plus these instructions. · 0 / 500
Segmentation
6 screening blocks
Import all screening questions from your segment definitions.
What is your primary role?
How often do you shop online?
Which devices do you use most?
Segmentation
Qualify participants directly inside the protocol
Import screening questions from your segment definitions into the protocol with one click. Participants are filtered before they reach your first scenario — no separate screener tool required.
- One-click import — Pull all screening questions from any segment definition you have set up — they appear as a dedicated block in the protocol.
- Consistent screeners — Screening logic lives in one place. Update the segment definition and every protocol that imports it stays in sync.
- Qualify before the first task — Participants who do not match your criteria are redirected at the screener stage, keeping your session data clean.
End of study
Control what happens after the last scenario
Redirect participants to a confirmation page, a panel system, or an incentive link — without extra steps. Optionally collect a quick evaluation rating on the thank you page.
- Custom redirection URL — Send participants anywhere — your panel, a landing page, or a Calendly link — automatically after their last scenario.
- Thank-you page evaluation — Add a smiley scale, star rating, or NPS on the closing page to capture overall session confidence in one tap.
- Per-study configuration — Each study has its own end-of-study setup. Change the URL or evaluation type without touching the protocol.
Customize redirection URL for participants
Redirect participants to a custom page once they complete the study.
Add evaluation questions
Collect feedback on the thank you page.
From brief to ready-to-run, in three steps
Step 1
Describe the study
Enter your research context and objectives. The AI assistant generates a structured study description — problem statement, domain, background, and goals — ready to refine or use as-is.
Step 2
Build from blocks
Compose the protocol by adding scenarios: questions, prototype tasks, preference tests, rating scales, and segmentation filters. Arrange sections and blocks in minutes, not hours.
Step 3
Preview and launch
Run a test session to validate the flow, configure end-of-study redirection, and publish. Use the same protocol for moderated live sessions or unmoderated self-serve tests.
Build your first protocol in minutes
See how teams design rigorous, repeatable research without starting from scratch every time.