How to use Finance-Based Pricing Advisor in your AI agent

What you'll get

This skill helps you decide if a proposed pricing change—like raising prices, adding a premium tier, or offering discounts—will actually improve your business. It walks you through estimating revenue impact, churn risk, conversion changes, and payback implications so you can make a data-driven go/no-go call on your pricing move.

Step 1 — Get the skill source URL

The Finance-Based Pricing Advisor skill lives at:

Step 2 — Add it to your AI agent

Copy one of these prompts and paste it into your AI tool. The agent will fetch and install the skill for you.

Add the agent skill from https://github.com/deanpeters/Product-Manager-Skills/tree/main/skills/finance-based-pricing-advisor to my project.

Install this agent skill: https://github.com/deanpeters/Product-Manager-Skills/tree/main/skills/finance-based-pricing-advisor

Add this skill to .codex/skills/: https://github.com/deanpeters/Product-Manager-Skills/tree/main/skills/finance-based-pricing-advisor

Add the skill at https://github.com/deanpeters/Product-Manager-Skills/tree/main/skills/finance-based-pricing-advisor to my .gemini/skills/ directory.

Install this agent skill from https://github.com/deanpeters/Product-Manager-Skills/tree/main/skills/finance-based-pricing-advisor

Add this skill: https://github.com/deanpeters/Product-Manager-Skills/tree/main/skills/finance-based-pricing-advisor

Step 3 — Try these prompts

Once the skill is installed, ask your AI things like:

• Considering raising prices and need to know if the revenue lift outweighs potential churn
• Launching a new premium tier or paid add-on and want to estimate adoption and cannibalization risk
• Present a pricing change proposal to leadership or your board with financial projections
• Deciding between pricing options (annual discount vs. monthly, new tier vs. price increase) and need to compare trade-offs

What this skill does

• Estimates revenue impact from price increases, new tiers, add-ons, or discounts using your current ARPU and customer data
• Assesses churn risk by segment and helps you decide whether to grandfather existing customers
• Calculates conversion impact and shows how pricing changes affect trial-to-paid rates or sales close rates
• Evaluates CAC payback and LTV:CAC ratio changes to ensure pricing improves unit economics
• Provides a go/no-go recommendation with supporting math and risk assessment