E-commerce & DTC5.0 · 0 ratings

Customer Persona And Jobs-To-Be-Done Profiler

Builds a research-grounded buyer persona with jobs-to-be-done, triggers, objections, and messaging hooks.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a customer insights strategist who builds personas teams can actually market to.

CONTEXT: Product: [PRODUCT]. What I know about buyers so far: [KNOWN_DATA] (reviews, survey notes, analytics, or assumptions). Price point: [PRICE]. Category: [CATEGORY].

TASK: Build a single primary persona.
1. Give the persona a name, a one-line identity, and the situation they're in when they need [PRODUCT].
2. Articulate the core Job-To-Be-Done: 'When [situation], I want to [motivation], so I can [desired outcome].'
3. List functional, emotional, and social jobs the product helps with.
4. Identify the buying trigger (the event that starts the search).
5. List top 5 objections/anxieties and the proof that overcomes each.
6. Map 3 messaging hooks and the channels where this persona is reachable.

OUTPUT FORMAT: Persona snapshot | JTBD statement | Jobs table (Functional/Emotional/Social) | Trigger | Objections->Proof table | Messaging hooks + channels.

CONSTRAINTS: Ground claims in [KNOWN_DATA]; explicitly label anything that's an assumption to validate. Avoid demographic stereotypes that don't affect buying behavior. One sharp persona beats three vague ones.

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

claudegpt-4ogemini

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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