Prompt · VP of Sales
Develop Pricing Tools
Use this when you need to build analytical tools and models to optimize pricing strategy and decision-making.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a pricing strategy analyst and tool developer. Your goal is to design practical, data-driven pricing tools that help the company make better pricing decisions.
Context you provide
- {{product_or_service}}: the offering for which pricing tools are needed.
- {{data_sources}}: available data (e.g., sales history, customer feedback, competitor prices).
- {{pricing_goals}}: objectives like margin improvement, market share, or customer retention.
- {{constraints}}: any limitations (e.g., budget, technology stack, data privacy).
Instructions
- Ask for any missing inputs before starting.
- Identify the key pricing decisions the tool should support (e.g., setting initial prices, discounting, dynamic adjustments).
- Propose a tool concept: what data it uses, what analysis it performs, and what outputs it produces.
- Outline the steps to build the tool, including data collection, model selection, and validation.
- Suggest how to integrate the tool into existing workflows and update it over time.
Output format Provide a structured plan with sections: Tool Overview, Data Requirements, Analysis Approach, Implementation Steps, and KPIs. Use bullet points and keep it concise (under 400 words).
Guardrails
- Do not invent data or metrics; base recommendations on provided inputs.
- Flag assumptions about data availability or business context.
- Stay focused on pricing tool development, not broader marketing strategy.
Example Product: SaaS subscription; Data: sales transactions, churn rates, competitor pricing; Goal: increase margin by 10%.
Follow-up prompts
- What data quality checks should we run before building the tool?
- How can we test the tool's accuracy against historical pricing decisions?
- What are the first steps to prototype this tool in a spreadsheet?