Nutrition-to-Benefit Translator

How to use it

1. 1Drop the prompt into ChatGPT, Claude or Gemini.
2. 2Fill the bracketed inputs (nutrition panel, audience, placement, market).
3. 3Answer its clarifying questions about audience and occasions.
4. 4Iterate: ask it to rewrite the ladders for a second audience or occasion.

See it in action

Benefit Translation — Meadowbrook Cottage Cheese (excerpt)

Ladder 1 — Protein (14g per serving)
Attribute: 14g protein per serving.
Functional: fuller for longer — the snack that holds you from 3pm to dinner.
Felt outcome: no desk-drawer spiral before dinner.
Gen Z phrasing: 'more protein than your bar, none of the candy-bar energy.' (Verify the comparison against your actual competitive set before using.)

Ladder 2 — Live cultures
Attribute: live and active cultures.
Functional: a fermented food, same family as yogurt and kimchi.
Felt outcome: earns a spot in the gut-friendly rotation.
Flag: any 'supports digestion' phrasing is a structure/function claim — route through regulatory before it ships.

Hierarchy: Lead with protein — an active search behavior for this audience (assumption to validate). Cultures support. 'High in protein' likely qualifies as a nutrient content claim; confirm serving thresholds.

Where facts beat marketing: On the PDP, '14g protein, 90 calories' outperforms adjectives. State the numbers plainly; let social carry the personality.

Want me to turn ladder 1 into five caption-length lines for social?

The prompt

Here's the start of the prompt. Download the free bundle for the full, ready-to-paste version — plus the installable Claude Skill and Custom-GPT instructions.

# Role
You are a senior food and beverage brand strategist with deep claims experience — you have written pack and PDP copy that survived both consumer testing and regulatory review. You translate chemistry into outcomes, and you refuse to write a health claim dressed up as a caption.

# Context I'll provide
- Product and nutrition panel: [PRODUCT + KEY NUTRITIONALS e.g. protein, fiber, sugar, sodium, live cultures]
- Target consumer: [AUDIENCE — who they are and what they care about]
- Where the copy will appear: [PLACEMENT e.g. pack front, PDP, social, shelf talker]
- Market and regulatory context: [MARKET e.g. US, EU — affects claim caution]
- Competitive framing: [WHAT COMPETITORS CLAIM] (optional)
- Brand voice notes: [TONE GUARDRAILS] (optional)

# Your task

Frequently asked questions

What is nutrition-to-benefit translation?

It is the discipline of converting nutrition facts — grams of protein, live cultures, fiber content — into language that describes what the product does for the person eating it: fuller afternoons, easier mornings, a gut-friendly rotation. This skill builds those benefit ladders systematically and flags where consumer-friendly phrasing crosses into regulated claim territory.

How is this different from the Claims & Pack Copy Optimizer?

The Claims & Pack Copy Optimizer polishes the words already headed for your pack. This skill works one step earlier: it decides which benefits deserve to be communicated at all, builds the attribute-to-outcome ladders, and sets the hierarchy — the strategic layer you hand to whoever writes the final pack or PDP copy.

Does it replace regulatory review?

No — and it says so explicitly. The skill flags phrasing that likely constitutes a nutrient content, structure/function, or health claim in your market, and pairs each flag with a safer fallback, which makes the regulatory conversation faster and better prepared. Final sign-off on any claim stays with your legal and regulatory team.

Which AI models support this skill?

Any capable chat assistant — ChatGPT, Claude, or Google Gemini. The prompt is model-agnostic and works the same whether pasted fresh each time or saved as a Custom GPT or a reusable Claude Skill, which helps when several teams keep translating the same nutrition panel in different ways.