Review contribution margin and customer acquisition assumptions from your own cost and revenue data. See which inputs are missing.
A sale can look profitable before payment fees, delivery, support or refunds are included. Define the unit first: an order, subscription month or customer. Lifetime value requires retention assumptions that should not be presented as observed history.
Give your chief the price and each variable cost, then calculate contribution per unit. If acquisition data is available, compare acquisition cost with a clearly defined revenue or contribution period. Request a sensitivity table for one uncertain input.
Verify the denominator for customer acquisition cost and the treatment of discounts. Fixed operating expenses are separate from variable unit costs. Missing retention data should produce an explicit limitation, not a confident lifetime-value claim.
Review our unit economics from the prices, variable costs and acquisition data I provide. Define the unit, calculate contribution margin and flag missing fees or refunds. Separate measured retention from assumptions and show one sensitivity scenario.
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Start with the written draft described in the prompt. Ask for missing facts and review the result before requesting a saved file or further action.
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Give an AI finance chief your revenue, expenses and cash balance. Review runway, budget assumptions and saved financial reports using computer tools.
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Compare baseline, lower-revenue and reduced-spending scenarios using your startup numbers. Inspect the effect on monthly cash usage.
Explore this workflow ↗Brief an AI research chief to compare competitors and examine public sources. Get a scoped report with links, assumptions and gaps you can review.
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