Example Inputs
Offer
Fractional COO advisory
Current Price
$2,000 monthly retainer
Constraint
Only capacity for 6 clients
Pressure-test pricing options using positioning, value, buyer psychology, and business constraints.
Pricing decisions are rarely just math. This prompt helps you weigh pricing options against value communication, market expectations, and internal business realities so you can choose a stronger range or structure.
Copy-And-Paste Prompt
Works well in ChatGPT, Claude, Gemini. Replace any bracketed variables before you run it.
Variables to customize
Act as a pricing strategist balancing value, market context, and business constraints. Your task is to analyze pricing options for my business and recommend a structure that fits the value proposition, audience, and operational realities. Use these inputs when available: - [Offer or Product] - [Target Customer] - [Current or Proposed Prices] - [Competitor Pricing Context] - [Margin, Capacity, or Delivery Constraints] Requirements: - Explain trade-offs rather than just naming one price. - Consider buyer psychology and perceived value. - Note operational or margin constraints clearly. - Recommend a pricing structure, not only a number. Return the answer in this format: 1. Pricing option analysis 2. Recommended structure and rationale 3. Messaging notes for how to present the price Tone and style: commercial, balanced, and strategic Ask me concise follow-up questions only if a missing detail would materially change the quality of the final answer.
Offer
Fractional COO advisory
Current Price
$2,000 monthly retainer
Constraint
Only capacity for 6 clients
A higher-touch advisory offer with clear deliverables may justify a smaller client roster and better margin than continuing to compete on an underpriced generic retainer.
This is a mock example only. Your result should change based on the variables, context, and constraints you provide.
The structure of this prompt is meant to make the AI do more than generate a loose first pass. It frames the model with a role, directs it toward a concrete goal, forces relevant inputs into the request, and asks for a usable output format instead of an open-ended answer.
That combination usually makes the result easier to review, edit, and reuse inside a real workflow. If the first output is still too generic, your best move is usually to add more context rather than abandon the prompt entirely.
These related calculators and guides add more depth when you want to connect this business prompt to real numbers, strategy, or supporting tools.
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Straight answers to the questions readers usually have before using these prompts.
Replace the bracketed variables with your own context, then add any constraints that matter for your audience, offer, or workflow. The more specific you are about goals, tone, and output format, the stronger the result will usually be.
Yes. The prompt is written in plain English so it works well across major AI assistants. If one model gives an answer that is too short or generic, paste the same prompt back in with an extra sentence telling the model to be more specific.