Set Your Target CPA and ROAS From Unit Economics

    You are a performance marketing analyst. Every target below has to come from arithmetic I can defend, not from an industry benchmark.

What I sell and the price: {{product_and_price}}
Gross margin per sale, after cost of goods and delivery: {{margin}}
Whether customers buy again, how often, and for how long: {{repeat_behavior}}
Other costs per customer — support, onboarding, payment fees: {{servicing_costs}}
Lead-to-customer conversion rate, if I'm buying leads rather than sales: {{conversion_rates}}
How quickly I need the money back: {{payback_requirement}}
What I currently pay per acquisition: {{current_performance}}

Produce:

**Contribution per customer.** Start from {{product_and_price}} and subtract everything real — cost of goods, payment fees, delivery, support, and any servicing from {{servicing_costs}}. Show each line. The number people usually use here is revenue, which is why so many profitable-looking campaigns lose money.

**First-purchase versus lifetime.** Two numbers: what a customer contributes on the first transaction, and what they contribute over their expected life given {{repeat_behavior}}. Be conservative on lifetime value — use observed retention rather than a hoped-for curve, and state the assumption explicitly. Most over-spending traces to an optimistic lifetime figure that nobody revisited.

**Maximum affordable acquisition cost**, both ways: the most I could pay and still profit on the first purchase, and the most I could pay if I'm willing to wait for the lifetime value. The gap between them is the strategic decision, and it's a cash-flow question as much as a marketing one.

**Payback period.** Against {{payback_requirement}}: how long until an acquired customer has repaid their acquisition cost. Then the target cost per acquisition that satisfies that requirement — which is often stricter than the profitability ceiling and is the one that actually binds if cash is finite.

**Target cost per acquisition, and the equivalent return on ad spend.** State both, since platforms report one and finance thinks in the other, and show how they convert. Note that a return-on-ad-spend target is only meaningful alongside a margin figure — the same ratio can be profitable for one business and ruinous for another.

**Working backward up the funnel.** Using {{conversion_rates}}: the maximum cost per lead, per click, and per thousand impressions that's consistent with the target. These are the numbers to actually manage against day to day.

**Reality check.** Against {{current_performance}} and typical costs in this category: is the target achievable? If the affordable cost per acquisition is well below what the channel charges, say so plainly — the answer is a pricing, margin, or conversion-rate change, not better campaign management.

**The blended view.** Why judging each channel on its own reported return misleads when channels influence each other, and what blended number to watch alongside — total spend against total new customers, which is harder to argue with.

**Review triggers.** What has to change for these targets to be recalculated — a price change, a margin change, a shift in retention.