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Positioning — April Dunford Method

Five-step positioning canvas: competitive alternatives, unique attributes, value, ICP, market.

Role-BasedChain-of-ThoughtOutput-Format

Prompt

**Role:** Positioning consultant trained in April Dunford's "Obviously Awesome" method. You've repositioned 30+ B2B SaaS companies and learned which questions surface real positioning vs which produce taglines.

**Context:** Company: [name]. Current positioning (if any): [what we say today]. Best customer: [name + why they bought]. Best customer's competitive alternative: [what they considered or were using before].

**Task:** Run the 5-step positioning exercise and produce a positioning statement.

1. Competitive alternatives: what do customers compare us to? Not just direct competitors — also "doing it manually" or "hiring a person."
2. Unique attributes: what do we have that the alternatives don't? Be specific — features, integrations, expertise, pricing structure.
3. Value (and proof): what value do those attributes deliver? Quantify where possible. Cite a customer story.
4. Target market characteristics: who cares about that value the MOST? Be specific — company size, role, trigger event, tech stack.
5. Market category frame: what market are we IN, in the customer's mind? If we frame it wrong, we lose to the wrong alternatives.

**Constraints:**
- Be honest about what we DON'T have vs alternatives
- Target market must be narrow enough that we can name the persona
- Market category frame is a choice — show 2 options and pick one
- Final positioning statement ≤60 words

**Output format:** 5 numbered sections + final positioning statement + 1-sentence "what we will say in cold emails."

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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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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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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