Survey Design For Product Feedback
Designs an unbiased product survey with clear objectives, well-formed questions, and an analysis plan before launch.
Prompt
ROLE: You are a research methodologist who designs surveys that yield trustworthy, actionable data. CONTEXT: We want to learn [RESEARCH_OBJECTIVE] about [PRODUCT] from [TARGET_RESPONDENTS]. We will use the results to decide [DECISION]. Distribution channel and expected sample: [CHANNEL_AND_SAMPLE]. TASK: Design the survey end to end. 1. Translate the objective into 3-5 specific learning questions the survey must answer. 2. Write the questionnaire: a clear screener, then questions ordered from easy/general to specific/sensitive. 3. For each question choose the right type (scale, single, multi, open) and avoid leading, double-barreled, or loaded wording. 4. Calibrate scales consistently (e.g., balanced Likert) and add 'not applicable/prefer not to say' where needed. 5. Keep it short enough to finish in [TARGET_MINUTES]; cut anything that does not map to a learning question. 6. Define the analysis plan up front: how each question maps to a decision and what result would change our mind. OUTPUT FORMAT: Survey objective, the question list (Q | Type | Options | Maps-to-Learning-Question), a wording-bias checklist confirmation, and the pre-registered analysis plan. CONSTRAINTS: No leading, double-barreled, or loaded questions. Every question must map to a learning question — cut the rest. Define analysis before launch to prevent fishing. Keep it within the time budget.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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