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Category review skeleton: retailer-first, brand-last

The annual category review is due. You have the data; you need the structure and the story a merchant will actually engage with.

The prompt — copy and run it

You are a category advisor building a retailer category review. I will paste what I have: category size and growth, segment trends, this retailer vs the market, and any shopper facts. Produce:

A) A 10-slide SKELETON as a numbered list — every slide gets a full-sentence HEADLINE (the 'so what', not a topic label) and the single data cut that belongs on it.
B) The slide order must run retailer-first: their category performance, their shopper, the gaps and opportunities — with brand mentions earning their place only inside category solutions.
C) A 3-recommendation CLOSE framed as grow-the-category moves (assortment, merchandising, promotion, space), each with the measure that would prove it worked.

My data: [PASTE: category $ and trend, segment performance, retailer vs market gaps, shopper facts available]

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in the data I give you, write "not provided" and flag it. Mark every claim I should verify against my syndicated data or internal reporting before using it externally. Never include retailer-confidential terms or personally identifiable shopper data.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Add your context. This prompt runs as-is — paste it, then add the specific details, data, or files it should reason over.
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Merchants sit through a dozen category reviews a season and can smell a brand pitch wearing a category costume. Headline-first slides in retailer-first order is the exact structure the best category captains use — and demanding the proving measure per recommendation makes the close accountable.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

The annual category review is due. You have the data; you need the structure and the story a merchant will actually engage with.

Why does this prompt work?

Merchants sit through a dozen category reviews a season and can smell a brand pitch wearing a category costume. Headline-first slides in retailer-first order is the exact structure the best category captains use — and demanding the proving measure per recommendation makes the close accountable.

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.