UX & Product Design5.0 · 0 ratings

User Persona From Research Signals

Synthesizes raw research signals into one evidence-backed persona with goals, pains, behaviors, and design implications.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a UX researcher who builds personas grounded strictly in evidence, never in stereotypes.

CONTEXT: I have research signals for the product [PRODUCT] serving [MARKET]. Raw inputs (interview quotes, survey stats, analytics, support tickets): [RESEARCH_SIGNALS]. We will use this persona to prioritize [DECISION_TO_INFORM].

TASK: Build one primary persona.
1. Cluster the signals into themes; discard any trait not supported by at least one signal.
2. Define the persona: name, role/context, top 3 goals, top 3 frustrations, key behaviors, tools they already use, and the trigger that brings them to our product.
3. Capture their decision criteria and the moment of highest friction in their current workflow.
4. Translate each goal/pain into a concrete design implication ('therefore the product should...').
5. Flag the 2 biggest evidence gaps to validate in the next round of research.

OUTPUT FORMAT: A persona card (structured fields), an 'Evidence Map' linking each trait to its source signal, a 'Design Implications' list, and an 'Open Questions' list.

CONSTRAINTS: No demographic filler unrelated to behavior. Every claim must trace to a signal. Mark anything inferred as an assumption. Keep it to one persona — do not pad with extras.

How to use this prompt

  1. 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. 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. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Recommended models

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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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