A questionnaire draft in a minute, rigor in the hour after
Zunoform's AI generation writes a questionnaire from a plain description — screening questions, demographics, matrix batteries on a shared scale, rating items, and open-ended prompts — and drops it into your workspace as an editable form. It is on the Business plan at $24.99/month. What it produces is a competent skeleton, and the parts that make a questionnaire defensible are still yours to write.
Questionnaire, not just form
A questionnaire is a measurement instrument: the same questions, in the same order, on the same scales, asked of everyone in your sample, so the answers can be compared. That is a higher bar than a form that collects information, and it is where generated drafts fall short in specific, predictable ways.
The generator handles the mechanical layer well. Describe your study and it picks question types sensibly — a matrix when six items share one scale, a dropdown when a list runs long, an open text box where a number would flatten the answer — writes out real option labels, orders the sections into something coherent, and adds a display-only statement to introduce a section. For a first pass at a 20-item instrument, that is an hour saved on typing.
It also has a hard ceiling of 30 questions per generation. Longer instruments are built in sections: generate the battery you need, then assemble and reorder in the builder, where question count is unlimited.
Four things to write yourself
Not because the model refuses, but because a plausible-sounding paraphrase is worse than an obvious gap — you will not notice it is wrong.
Validated instruments
If your study uses a published scale, do not let a model reproduce it from memory. Item wording, order, and scale anchors are what make the norms comparable, and a near-miss paraphrase quietly breaks that comparison while looking correct. Type those items from the source and let the generator draft everything around them.
Consent and data-handling language
Consent text has to state what you collect, why, how long you keep it, and how someone withdraws — and it usually has to match what your ethics board or your privacy notice approved. Generated consent language reads convincingly and commits you to nothing accurate. Write it, or paste the approved version.
Screening and quota logic
Who qualifies, who is disqualified, and who sees which block is study design. The generator may add one to three simple rules; a real screener with disqualification paths and branching by segment is built in the logic panel, where rules are per-question and unlimited on every plan.
Demographic categories
Model-written demographic options default to whatever is statistically common in its training data, which may not match your population, your region, or the categories your analysis needs. Age bands, gender options, income brackets, and job categories should all be chosen deliberately, with opt-outs.
Reviewing the generated draft
The same failure modes appear in nearly every AI questionnaire draft.
- Split any item asking about two things at once — the double-barrelled question is the most common defect.
- Remove evaluative adjectives from question stems; they lead the answer.
- Make every scale balanced, with equal positive and negative points and a genuine midpoint.
- Use one scale direction and one set of anchors throughout, so items stay comparable.
- Move demographics to the end and mark them optional unless the analysis requires them.
- Add Prefer not to say and Not applicable wherever a respondent could reasonably have no answer.
- Check for priming: an early specific question changes how a later general one is answered.
- Pilot with five people from the real population and ask them what each question meant to them.
From draft to fielded instrument
Generate the skeleton
Describe the population, the construct you are measuring, and the scale you want. Specifics you name come back verbatim; vagueness comes back generic.
Replace the load-bearing items
Swap in validated items, your approved consent statement, and demographic categories that fit your sample. Keep the generated wording only where you would have written something similar.
Build the routing and the exit
Add screening rules that end the questionnaire early for non-qualifiers, branch by segment, and set the ending page. Then connect where responses go — Google Sheets, a webhook, or your own systems.
Research questionnaires already built
Free on every plan, including the consent and screening structures.
A Likert matrix, usage questions, and an optional follow-up opt-in.
Standard optional demographics with respectful answer choices.
Qualifies participants and routes non-matches to a polite ending.
Study overview, acknowledgments, recording consent, and a signature.
Questions people ask
Is the AI questionnaire generator free?
No — it is on the Business plan at $24.99/month. Building questionnaires by hand is free, with unlimited forms, 500 responses a month, matrix questions, conditional logic, and 133 templates including research and consent forms.
How long a questionnaire can it generate?
Up to 30 questions in a single generation, typically 5 to 15. For longer instruments, generate sections and assemble them in the builder, where there is no question limit.
Can it reproduce a validated scale?
It will try, and that is the problem. Paraphrased items look right and break comparability with published norms. Enter validated items from the source document and use the generator for the surrounding questions.
Can it handle screening and disqualification?
Partly. It can add a few rules such as ending the questionnaire when someone answers no to an eligibility question. Multi-criteria screening and quota routing you build yourself in the logic panel, which is free and unlimited.
What about consent forms and sensitive data?
Write the consent language yourself or paste your approved version — generated text reads convincingly without being accurate about what you actually collect. There is a research consent form template on the free plan you can start from.
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