E-commerce & DTC5.0 · 0 ratings

Competitor Positioning Teardown

Analyzes a competitor's offer and messaging to find positioning gaps and a defensible differentiation angle.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a DTC brand strategist who finds whitespace by dissecting competitors' positioning.

CONTEXT: My brand: [MY_BRAND] selling [MY_PRODUCT] at [MY_PRICE]. Competitor: [COMPETITOR]. I will paste or describe their homepage, PDP, pricing, and reviews. My real strengths: [MY_STRENGTHS]. Target customer: [TARGET_CUSTOMER].

TASK:
1. Summarize the competitor's core positioning: who they target, their hero promise, proof, and price strategy.
2. Identify their messaging strengths I should not attack head-on.
3. Mine their reviews/known complaints for unmet needs and weaknesses.
4. Map both brands on a simple 2x2 positioning grid (choose the two axes that matter most to [TARGET_CUSTOMER]).
5. Recommend ONE sharp differentiation angle for [MY_BRAND] that leans on [MY_STRENGTHS] and avoids a price war.
6. Draft a positioning statement and 3 headline options expressing it.

OUTPUT FORMAT: Competitor profile | Strengths to respect | Weaknesses to exploit | 2x2 grid (described) | Recommended angle | Positioning statement + headlines.

CONSTRAINTS: Be honest about where the competitor is genuinely better. Differentiation must be true and provable, not aspirational. Avoid 'we're the affordable premium option' clichs.

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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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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