Survey Questionnaire Designer
Design a clean, unbiased survey questionnaire for any research topic.
What is the Survey Questionnaire Designer?
The Survey Questionnaire Designer is a free AI skill that writes a clean, unbiased quantitative survey for any food or beverage research topic — usage and attitudes, satisfaction, positioning, packaging reaction, or a question that doesn't fit a named category yet. You give it the research topic, the audience, and the decision the survey needs to inform; it returns screener questions to reach the right respondents, neutral core questions with standardized scales, a question order that avoids priming later answers, skip and routing logic, and a field-readiness checklist before you launch. It is built for insights managers and researchers who need a general-purpose instrument for whatever question just landed on their desk, not a survey narrowly built to test one new product concept. Because every question is checked for neutrality and every scale is standardized, the results benchmark cleanly against past waves. Pairing the finished questionnaire with live food and beverage demand data helps you sanity-check what respondents say against what they actually search for and buy.
Who it's for
- Insights managers fielding a general research study, not a concept test
- Market research analysts building a fresh questionnaire from scratch
- Brand teams commissioning a usage-and-attitudes or satisfaction study
- Founders running their first structured consumer survey
What you get
- A screener that qualifies the right respondents
- Neutral, unbiased core questions with standardized scales
- A logical question order that avoids priming later answers
- Skip and routing logic for branching questionnaires
- Open-ends that capture the 'why' behind the ratings
- A field-readiness checklist before you launch
How to use it
- 1Paste the prompt into ChatGPT, Claude or Gemini.
- 2Fill in the brackets (research topic, audience, decision, question areas).
- 3Answer its clarifying questions about scope and length.
- 4Ask it to trim the survey to a shorter version if it's running long.
See it in action
Example input
Topic: usage and attitudes study for fictional 'Willowmere' herbal tea drinkers. Audience: US tea drinkers who buy herbal or wellness tea at least twice a month. Decision: whether to expand from 6 flavors into a functional (sleep, calm, digestion) sub-line. Constraint: survey must run under 12 minutes and fit our existing Qualtrics template.
Example output
Survey questionnaire — Willowmere herbal tea usage & attitudes (target: under 12 minutes) Screener S1. Which of the following have you personally purchased in the past 3 months? [Herbal or wellness tea / Black or green tea / Coffee / None of these] — qualify respondents who select herbal or wellness tea. S2. How often do you purchase herbal or wellness tea? [Multiple times a week / About once a week / 2-3 times a month / Once a month / Less often] — qualify 2-3 times a month or more often. S3. Age band — quota to your target distribution. S4. Do you or anyone in your household work in market research, advertising, or the food and beverage industry? [Yes / No] — terminate if yes. Core questions Category behavior Q1. Which herbal or wellness tea brands have you purchased in the past 3 months? [Multi-select brand list + Willowmere + Other] Q2. Thinking about your last purchase of Willowmere, what occasion was it for? [Wind-down before bed / Mid-day break / Feeling under the weather / Digestive discomfort / Just enjoy the taste / Other] Q3. How many cups of herbal tea do you drink in a typical week? [Open numeric] Attitudes toward the category (5-point agree/disagree, randomized order) Q4. "I buy herbal tea because I want a specific benefit, not just a beverage." Q5. "I would pay more for a tea brand that clearly targets one specific need, like sleep or digestion." Q6. "Most herbal tea flavors on the market taste similar to me." Brand-specific ratings (5-point scale) Q7. Rate your overall satisfaction with Willowmere. Q8. Rate Willowmere on: taste, packaging, price, availability where you shop, variety of flavors. [grid] Functional sub-line reaction (shown only to Willowmere buyers who qualify past S2) Q9. If Willowmere launched teas formulated for specific needs — Sleep, Calm, and Digestion — how likely would you be to try at least one? [5-point purchase-intent scale; Top-2-box is the headline metric] Q10. Which of the three needs would you be most interested in? [Sleep / Calm / Digestion / None of these] Q11. Open-end: "What, if anything, would make you hesitant to try a functional Willowmere tea?" Closing Q12. Household income band [standard ranges] Q13. Any final thoughts on Willowmere or herbal tea in general? [Open-end, optional] Field-readiness checklist - Estimated length: 10-12 minutes at 13 questions plus screener — on target. - Randomize Q4-Q6 and the brand list in Q1 to avoid order bias. - Set the action standard before fielding: proceed with functional sub-line scoping if Q9 Top-2-box intent clears your category's historical concept-test norm (insert your norm) and Q10 shows a clear lead need rather than a three-way split. - Confirm Qualtrics logic: S1-S4 must terminate or route correctly before Q1 loads. - Sample size isn't set here — confirm with your research team based on the confidence interval you need for the Q9/Q10 read. Note: Q9's "likely to try" measure is a stated-intent proxy for an undeveloped concept, not a screened concept test — treat the functional-line read as directional interest that justifies further concept development, not a launch decision on its own. Want a shorter 5-minute version for an intercept or app-based sample, or this 13-question version formatted for a different survey tool?
The prompt
Here's the start of the prompt. Download the free bundle for the full, ready-to-paste version — plus the installable Claude Skill and Custom-GPT instructions.
# Role You are a senior quantitative research methodologist for food & beverage brands. You write clean, neutral survey instruments for any research topic — not just concept tests — and you never let a question's wording nudge the respondent toward an answer. # Context I'll provide - Research topic: [TOPIC — e.g. usage & attitudes, satisfaction, positioning, packaging reaction] - Target audience: [AUDIENCE] - The decision this survey needs to inform: [DECISION] - Specific question areas to cover (optional): [QUESTION AREAS] - Length or platform constraints: [CONSTRAINTS e.g. under 12 minutes, must fit Qualtrics/SurveyMonkey] # Your task 1. If the research topic, audience, or decision are missing or vague, ask up to 3 clarifying questions BEFORE writing anything.
Frequently asked questions
- What is a survey questionnaire in market research?
- A survey questionnaire is the actual instrument — screener, core questions, scales, and open-ends — fielded to a sample of respondents to answer a specific research question. Unlike a concept test, it isn't limited to reacting to one new idea; it can measure usage and attitudes, satisfaction, positioning, or any topic a team needs a structured, comparable read on. This skill writes that instrument end to end.
- How is this different from the Concept Screening Survey Designer skill?
- The Concept Screening Survey Designer is purpose-built for one job: testing a new product concept, with a neutral concept exposure and measures like purchase intent, uniqueness, and believability tied to that concept. This skill is general-purpose — it writes a clean, unbiased survey for any research topic, from usage and attitudes to satisfaction to positioning, with no concept exposure required. Use the concept screener when you're testing a specific new idea; use this one for everything else.
- Which AI models does this prompt work with?
- Any capable chat model — ChatGPT, Claude, or Google Gemini. The prompt is model-agnostic, so paste it directly into a chat, save it as a Custom GPT, or store it as a reusable skill so every new research topic gets the same clean, unbiased instrument.
- Will it invent benchmark norms or sample sizes?
- No. It structures screeners, questions, and scales, but it will not fabricate past-wave benchmarks, category norms, or a required sample size — those get labeled as assumptions to validate against your own research history or a statistician's input, so you don't walk into a debrief with an invented comparison point.
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