finance-based-pricing-advisor

Provide your current ARPU, churn rate, conversion rate, and customer count, then model the ARPU lift against expected churn and conversion losses. The skill nets these effects and recommends implementing, testing first, modifying, or holding.

Estimate churn elasticity by segment and model conservative, base, and optimistic churn scenarios against the revenue lift. Grandfathering existing customers and raising prices for new customers only is the standard way to reduce churn risk.

Test first when impact estimates are uncertain, churn or conversion risk is moderate, and your customer base is large enough for statistical significance. Use control and test cohorts of 100+ customers each over 60-90 days with defined roll-out and kill criteria.

No. It evaluates a specific pricing change you are already considering, not value-based pricing, willingness-to-pay research, packaging architecture, or monetization model selection. Those topics belong to separate pricing strategy frameworks.

You need baseline ARPU or ARPA, monthly churn rate, trial-to-paid conversion rate, customer count or MRR, CAC, and ideally NRR. Estimates are acceptable, but without baseline metrics the financial impact analysis cannot be grounded.