Prompt library · Research

Customer survey design prompt

This prompt produces a concise customer survey for researchers at small businesses. It turns a realistic fictional brief into a usable first draft with explicit assumptions and verification steps.

When to use it

Use this when you need a concise customer survey and want a concrete starting point rather than generic advice. Replace the fictional details with your own confirmed facts before using the result in a real setting.

The prompt

## Role
Act as a survey methodologist. Apply professional judgment while keeping your reasoning understandable to someone who is not a specialist.

## Context
HearthBox sells home cooking kits and wants to understand why customers stop after their second order. The team can invite recent two-order customers and continuing subscribers, but has no representative population panel. The survey should take under four minutes. Its purpose is discovery, not estimating national demand.

## Objective
Design a neutral survey that separates experience, barriers, and future preferences without pushing a renewal offer.

## Audience
The primary users are researchers at small businesses. Make the deliverable usable in their day-to-day work, with enough explanation to support decisions but no unnecessary background lecture.

## Requirements
Provide an introduction, consent language appropriate for a voluntary research invitation, eight to ten questions, response options, and routing notes. Ask about actual recent behavior before hypothetical preferences. Include not applicable and prefer not to answer where useful, plus one optional open-text question. Add a pilot checklist and analysis plan covering response rates, segment comparisons, missing data, self-selection, and how small groups will be reported without exposing individuals.

## Constraints
Do not collect unnecessary personal details, combine several concepts in one rating, assume all churn is price-related, or imply the sample supports population-wide conclusions. Work only with the scenario and any material explicitly supplied. Label assumptions and distinguish proposed actions from confirmed facts.

## Tone & style
Be direct, thoughtful, and specific. Prefer plain English, concrete examples, and short paragraphs. Match the language to the intended reader rather than relying on jargon or generic motivational phrasing.

## Output format
Present the requested deliverable first, using descriptive headings and tables only where they improve usability. Keep supporting notes separate from copy intended for publication or direct use. Finish with a short checklist of outstanding decisions or verification steps.

## What to avoid
Avoid filler, unsupported certainty, and details invented to make the result seem more complete. Do not let a polished presentation conceal missing information or conflicting requirements.

## Success criteria
Respondents can answer accurately without guessing, and the analysis can distinguish respondents’ experiences from researchers’ interpretations. Check the result against the stated constraints before presenting it and correct any inconsistencies you find.

## Clarifying questions
Ask up to three focused questions only if missing information would materially change the result. Otherwise proceed with the fictional scenario, state any necessary assumptions briefly, and identify what a real user should confirm before relying on the output.

Why it works

  • The scenario gives the model concrete facts and boundaries instead of asking it to invent a brief.
  • The requirements specify the actual deliverables and the important edge cases for this task.
  • The constraints make unsupported claims and unapproved commitments harder to slip into the result.
  • The success criteria turn review into a practical check: respondents can answer accurately without guessing, and the analysis can distinguish respondents’ experiences from researchers’ interpretations.

Make it yours

Build a tailored version with PromptDeck by replacing the fictional scenario with your own context, audience, and constraints. Keep the verification steps so the final result reflects what you actually know.

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