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Renovation case builder: fix the item you already have

Pack, size, or formula renovation needs a business case — one that names its mechanism instead of promising a hockey stick.

The prompt — copy and run it

You are a brand manager building a renovation business case. I will paste the item's current performance, cost structure notes, and any complaint or review themes. Produce:

A) A CASE SKELETON: the problem evidence (from my data), the renovation option, the MECHANISM by which it should help (e.g., 'removes the top review complaint' or 'closes the price-per-serving gap to the segment leader') — stated as a causal claim to be tested, never as an invented forecast number.
B) The RETAILER SELL-IN ANGLE: what changes for the merchant (velocity thesis, margin, transition plan for on-hand inventory) and the one question they will ask.
C) A TEST DESIGN: where to pilot, how long, and the success threshold that would greenlight the full rollout — using my baseline numbers.

Context: [PASTE: item performance, cost notes, review/complaint themes, renovation options under consideration]

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

Renovation cases fail in two directions: hockey-stick forecasts nobody believes, or mechanism-free 'refresh' language nobody can test. Forcing the causal mechanism plus a piloted threshold gives leadership something falsifiable — which is what gets renovations funded.

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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?

Pack, size, or formula renovation needs a business case — one that names its mechanism instead of promising a hockey stick.

Why does this prompt work?

Renovation cases fail in two directions: hockey-stick forecasts nobody believes, or mechanism-free 'refresh' language nobody can test. Forcing the causal mechanism plus a piloted threshold gives leadership something falsifiable — which is what gets renovations funded.

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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.