Q01
Message
All templatesResearch
Vignette Experiment: Scenario & Framing Test
A true factorial vignette experiment: respondents judge realistic scenarios whose key details (price framing, messenger, wording) rotate systematically, so you can measure how each factor shifts judgment. The built-in vignette question type generates the scenario combinations for you.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
6 questions · ~5 min
Q02
Vignette experimentRequired
Please read the scenario and rate your agreement with the statement below it.
Q03
Opinion ScaleRequired
If this happened to a service you pay for, how likely would you be to look for an alternative?
Scale: 1 – 7
Min:Wouldn't consider switchingMax:Would start looking immediately
Q04
Short TextRequired
Which detail of the scenario most influenced your rating?
Q05
AI Interview
Debrief the vignette judgment: which detail they weighed most and whether that surprised them, what would have made the scenario feel fair (or unfair), and how a similar real experience of theirs shaped the reaction. Do not reveal that other participants saw different versions until the end; then ask whether knowing that changes their view.
Q06
Message
Thank you! Because different people saw systematically different versions, we can measure exactly how much each detail — the framing, the messenger, the reason — moved judgments.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- A native vignette-experiment question type generates the factorial scenario combinations and randomization for you — no manual branching gymnastics
- Behavioral follow-ups (switching likelihood) and a which-detail-mattered check accompany the core judgment scale
- The AI debrief explores the reaction before revealing the manipulation, then tests whether knowing changes the judgment
- Regression-ready structure: every respondent's scenario composition is recorded with their response
tickStat
Factorial vignette experiments - tickStat DocumentationRare example of a survey platform with a genuinely native factorial-vignette feature: users define attributes and levels, the tool builds full or fractional factorial designs and assigns balanced randomized scenarios, respondents rate on a 0-100 slider or Likert scale, and it exports analysis-ready coded data for regression. Strong methodological tooling, but it's a rating/estimation instrument with no adaptive qualitative follow-up on why a respondent judged a scenario as they did.
What it does well
- Genuinely native factorial-vignette engine (define attributes/levels; auto-generate full or fractional designs)
- Balanced randomization so every level appears at the right frequency, across within- and between-subject designs
- Choice of continuous 0-100 slider or Likert-style discrete response formats
- Analysis-ready export with attribute levels pre-coded for regression
Where it falls short
- Collects only structured ratings; no adaptive AI follow-up asking why a scenario was judged that way
- No auto-generated narrative report interpreting which attributes drove judgments
- Design/methodology assumes a statistically literate user; little hand-holding for non-researchers
- No pairing with a qualitative interview layer to explain surprising level effects
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
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