finance-based-pricing-advisor — an installable skill for AI agents, published by deanpeters/product-manager-skills.
Evaluate financial impact of pricing changes using ARPU, conversion, churn, and payback analysis. Quantifies revenue lift, conversion risk, churn impact, and CAC payback for price increases, new tiers, add-ons, usage-based pricing, discounts, and packaging changes Models three scenarios (conservative, base, optimistic) and identifies go/no-go decisions with supporting math Recommends implementation, A/B testing, modified approaches, or holding pricing based on net revenue impact and risk tolerance Assumes you have a specific pricing change in mind; not a strategy design tool for building pricing from scratch or conducting willingness-to-pay research Purpose Evaluate the financial impact of pricing changes (price increases, new tiers, add-ons, discounts) using ARPU/ARPA analysis, conversion impact, churn risk, NRR effects, and CAC payback implications. Use this to make data-driven go/no-go decisions on proposed pricing changes with supporting math and risk assessment. What this is: Financial impact evaluation for pricing decisions you're already considering. What this is NOT: Comprehensive pricing strategy design, value-based pricing frameworks, willingness-to-pay research, competitive positioning, psychological pricing, packaging architecture, or monetization model selection. For those topics, see the future pricing-strategy-suite skills. This skill assumes you have a specific pricing change in mind and need to evaluate its financial viability. Key Concepts The Pricing Impact Framework A systematic approach to evaluate pricing changes financially:
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