Discount Conversion Hurdle Calculator

A contribution comparison, not a sales forecast

This calculator asks how much conversion must change to offset lower contribution per order and extra campaign cost. It compares one reference offer with one promotion over the same eligible traffic and planning period. At most one qualifying order is counted per visit. Inputs remain local; it needs neither an AI API nor a homepage audit credit.

Enter one reporting currency. The reference basket price is tax-exclusive and before the proposed effective discount. Shared variable cost includes product, fulfilment, fixed payment charges and any explicitly scoped expected return loss. The percentage fee below is excluded from that cost line. Extra per-order promotion cost could be a delivery subsidy; do not include it again in shared cost or subtract it from price as well.

Definitions and formulas

Let P be reference basket revenue, d the effective discount fraction, f the revenue-based fee fraction, C shared variable cost, S additional cost per promotion order, V equal eligible visits, b reference conversion, p assumed promotion conversion and K additional campaign cost. Rates entered as percentages are divided by 100.

• Reference contribution per order m0 = P × (1 − f) − C.
• Promotion revenue = P × (1 − d).
• Promotion contribution per order m1 = P × (1 − d) × (1 − f) − C − S.
• Reference contribution B = V × b × m0.
• Promotion contribution A = V × p × m1 − K; change = A − B.
• Required conversion q = (B + K) / (V × m1), only for positive m1.
• Percentage-point change = 100 × (q − b); relative lift = q / b − 1 when b is positive.

The hurdle preserves scoped contribution, not net profit. Common media spend and overhead are excluded. If they change, the relevant incremental cost belongs in the model or the equal-scope assumption fails.

Reproduce the synthetic default

P = 80, d = 20%, C = 38, f = 2.5%, S = 2, V = 10,000, b = 2%, p = 3%, K = 500. Reference contribution per order is 40; promotion contribution is 22.40. Reference total is 8,000, promotion total 6,220, change −1,780. The hurdle is 3.794642857…% conversion, approximately +1.79464 percentage points or +89.73214% relative to reference. Reset restores these values.

Validation and boundary behaviour

Numeric values must be finite, nonnegative and no greater than one billion; percentage inputs are bounded 0–100. Price and whole-number visits must be positive. Blank fields are rejected, not converted to zero. Positive reference unit contribution is required. Zero reference conversion is allowed but makes relative lift undefined. Zero or negative promotion contribution returns no growth hurdle: each additional order adds nothing or worsens contribution. With zero reference orders and no extra campaign cost, zero promotion orders can tie the reference; that is not a growth strategy.

A positive-margin hurdle above 100% is arithmetically unreachable here. Near-zero positive margins may exceed representable numeric limits and are flagged. Expected orders can be fractional because this is a rate scenario, not an invoice ledger. Calculations use floating-point values with rounded displays; exported values retain calculation precision. Use a finance-grade decimal implementation for real monetary posting, not this planning tool.

What the result cannot tell you

It cannot predict price elasticity, validate a control group, estimate a confidence interval or approve a promotion. Different basket mix, traffic acquisition, fee bases, refund behaviour or repeat purchases require extra modelling. Resolve the real effective discount from the actual checkout; do not assume two advertised percentages stack multiplicatively. A lower hurdle is not evidence that a particular audience will reach it.

Source boundaries

Checked 25 September 2026. Shopify's current combination documentation distinguishes product, order and shipping discounts and their eligibility. Google's discount-event guide documents monetary item discounts and the paid-price field. These are implementation references, not validation of this original decision model or proof that a discount causes growth.