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From pm-copilot
Use this skill when the user asks to "review our pricing", "help me think through pricing", "should we change our price", "pricing strategy", "how should we price this", "pricing tiers", "is our pricing right", "freemium vs. paid", or wants to evaluate or design their product's pricing model.
npx claudepluginhub productfculty-aipm/pm-copilot-by-product-facultyHow this skill is triggered — by the user, by Claude, or both
Slash command
/pm-copilot:pricing-reviewThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are helping the user evaluate or redesign their pricing model. Pricing is strategy made visible — it signals positioning, affects who buys, and determines who stays.
Guides pricing decisions, tier structure, packaging, and monetization strategy for SaaS products. Covers value-based pricing, pricing research, discount frameworks, and pricing experiments.
Guides SaaS pricing and monetization strategy with value-based pricing, packaging, tiers, metrics, and competitive analysis using gathered business context.
Analyzes and designs pricing strategies: models (flat-rate, per-seat, usage-based, tiered, freemium), competitor pricing, willingness to pay, elasticity. Use for pricing setup, evaluation, changes, or freemium comparisons.
Share bugs, ideas, or general feedback.
You are helping the user evaluate or redesign their pricing model. Pricing is strategy made visible — it signals positioning, affects who buys, and determines who stays.
Framework: Lenny Rachitsky (AI feature monetization data), Palle Broe (How should you monetize your AI features), Patrick Campbell (value-based pricing), April Dunford (positioning-informed pricing).
Key insight from Palle Broe's analysis of 44 tech incumbents: 59% bundle AI features in existing packages; 23% offer as an add-on; 18% build standalone AI products. For products with clear customer value and high variable costs, direct monetization is best.
Read memory/user-profile.md for product stage, business model, and current bets. Read context/company/competitors.md for competitive pricing context.
Evaluate which model fits:
Flat subscription: Simple, predictable revenue; good when value doesn't vary much by usage. Best for: Tools used at a consistent rate; B2C or SMB.
Usage-based / metered: Price scales with value delivered; aligns costs with revenue. Best for: AI-powered features with significant per-use costs (API calls, compute); enterprise customers with variable volume.
Tier-based (Good/Better/Best): Multiple tiers; works well when value delivered varies significantly by customer segment. Best for: When you have distinct ICP segments with different willingness to pay and different feature needs.
Freemium: Free tier drives adoption; paid tier captures value for power users. Best for: When the free tier has a real viral or word-of-mouth effect; when converting 2–5% of free users to paid is sufficient.
Per-seat: Simple, scales with team size. Best for: Collaboration tools; B2B where value scales with the number of users.
The value metric is what you charge for — the thing that scales as customers get more value.
Good value metrics:
Poor value metrics:
Estimate willingness to pay for the ICP:
Van Westendorp price sensitivity meter: Ask (or infer from context):
The acceptable price range is between "too cheap" and "too expensive" responses.
Competitive anchoring: What do alternatives cost? How does our product's value compare? If we're 10x more valuable, we shouldn't be 10x more expensive — but we shouldn't be the same price as an inferior alternative.
If evaluating freemium:
The freemium test: Is the free tier genuinely useful enough to drive adoption, but limited enough to justify upgrading?
Common freemium mistakes:
For PM Copilot specifically (as a reference model):
Produce: