Q01
Message
All templatesEducation & Academic
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
Frequently asked questions
What questions are in the “Vignette Experiment: Scenario & Framing Test” template?
The template includes 6 ready-to-use questions, starting with: “You'll read a short, realistic scenario and give your honest reaction. Your responses are completely confidential and an…” · “Please read the scenario and rate your agreement with the statement below it.” · “If this happened to a service you pay for, how likely would you be to look for an alternative?”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 6 questions in about 5 minutes.
Can I customize this template?
Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.
Is this template free to use?
Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
Related templates
More studies on similar topics.
Education & Academic
AI Literacy Self-Assessment for Undergraduates
A validated self-assessment instrument measuring undergraduate AI literacy across five dimensions: conceptual understanding, practical skills, critical evaluation, ethical reasoning, and awareness of limitations. Estimated completion time: 10-12 minutes.
View templateEducation & Academic
Interview Experience Study
A controlled comparison instrument for evaluating interview experiences across different moderator formats. This survey measures pre-interview expectations, embeds an interview session, and captures post-interview evaluations of comfort, quality, depth, trust, and willingness to participate again.
View templateEducation & Academic
Advertisement Concept & Creative Evaluation Survey
Tests a single ad — video, print, or social creative — for clarity, appeal, relevance, and purchase impact before it goes live. An AI follow-up interview digs into the specific moment respondents got confused, bored, or excited, surfacing the 'why' behind the ratings so creative teams know exactly what to cut, keep, or clarify.
View templateEducation & Academic
Marketing Claims and Messaging Testing Survey
Tests how believable, relevant, and differentiating your candidate marketing claims are, using a best-worst trade-off to force priority among competing lines and an AI follow-up that digs into why the top claim landed or fell flat. Built for brand, product marketing, and comms teams validating messaging before a campaign launch.
View templateEducation & Academic
New Concept Evaluation and Pricing Study
Tests reaction to a new product or service concept — appeal, differentiation, purchase intent, and an optimal price range — for teams deciding whether to build or launch. An AI follow-up interview digs into what would make respondents actually buy or walk away.
View templateEducation & Academic
Interactive Story Engagement & Choice Satisfaction Survey
Measures how readers or players experienced a branching narrative — engagement, satisfaction with the choices offered, and pull toward replaying alternate paths. Built for interactive fiction studios, narrative game teams, and branching-content publishers, with an AI follow-up that reconstructs a specific choice moment to reveal whether decisions actually felt like they mattered.
View template