Build the pre-launch test in order
Inputs and decision boundaries
- Choose one promotion period, currency and indirect-tax basis. (not complete)
- Record the eligible audience and a supportable reason for the offer without calling every visitor incremental. (not complete)
- Record the regular offer and price, the evidence supporting any former or reference price, and the exact offer difference. (not complete)
- Set an honest start, end and repeat rule, including who can approve an exception. (not complete)
- Reconcile baseline orders and contribution per order before the discount. (not complete)
- State discount eligibility, campaign cost and the assumed incremental-order range. (not complete)
- State how many baseline orders would receive the discount anyway. (not complete)
- Set contribution, cash, stock and capacity stop points before reviewing the result. (not complete)
- Define regular-price restoration and the post-offer full-price observation window before launch. (not complete)
incremental promotion contribution = assumed incremental orders × (baseline contribution per order - discount per order) - campaign cost - discount on baseline orders
- assumed incremental orders
- Orders assumed to occur because of the promotion for scenario testing only (orders in the promotion period) — user assumption
- baseline contribution per order
- Contribution before the promotion discount on a consistent cost boundary (currency units per order) — business record
- discount per order
- Reduction in retained contribution for an eligible order (currency units per order) — user scenario
- campaign cost
- Total included campaign cost for the period (currency units per period) — business record or user scenario
- discount on baseline orders
- Contribution lost on orders that would have occurred without the promotion (currency units per period) — user scenario
Use the promotion planner for full period comparisons. Keep discount-recovery output with the separate Discount Profit Impact owner.
- Rebuild the baseline with the same product, cost and period boundary.
- Calculate contribution after discount for eligible orders.
- Test downside, base and no-lift assumptions without treating any as a forecast.
- Add campaign cost and the discount given to baseline orders.
- Stop or redesign if the downside breaches the pre-set contribution or cash boundary.
- Check stock and service capacity before approving the assumed order volume.
- Restore the documented regular offer when the stated end event occurs.
- Review full-price behaviour in the declared post-offer window before stop, repeat or redesign.
Record the offer boundary and regular-price recovery plan
| Field | What to record | Stop or review boundary |
|---|---|---|
| Eligible audience | Named segment and eligibility evidence | Stop if the audience cannot be applied consistently |
| Offer reason | Supportable purpose such as one launch window or a defined inventory event | Do not invent urgency or imply causal demand |
| Start and end | Real calendar or observable start and end events | No rolling “last chance” deadline |
| Repeat rule | Named evidence, minimum review fields and approver required before another offer | No automatic cadence or ideal frequency |
| Reference-price expectation | Regular offer, actual price history and support for any former/reference-price statement | Stop for local review when a price comparison or deadline claim is unsupported |
| Regular-price restoration | Offer presentation and price restored at the declared end, with an owner and completion record | Do not leave the promotion permanently active by default |
| Post-offer full-price review | Observation window, comparable audience, full-price orders, contribution and known confounders | Treat recovery or deferral as observed context, not proof of promotion causation |
Worked example: base and no-lift cases
Invented neutral scenario: 30 contribution per order before discount, an 8 discount, 600 campaign cost and 40 assumed incremental orders. First assume no baseline order receives the discount, then expose that omitted risk.
| Scenario | Assumed incremental orders | Contribution before discount | Discount on incremental orders | Campaign cost | Scenario contribution |
|---|---|---|---|---|---|
| Base assumption | 40 | 1,200 | (320) | (600) | 280 |
| Downside assumption | 20 | 600 | (160) | (600) | (160) |
| No lift | 0 | 0 | 0 | (600) | (600) |
| Window | Record or scenario | Interpretation boundary |
|---|---|---|
| Pre-offer reference window | 100 observed baseline orders plus regular-price contribution on the declared comparable basis | Business record; not a forecast for the offer window |
| Offer window | No-lift, downside and base scenarios from the table above | User-entered scenarios; no scenario proves incremental demand |
| Post-offer full-price window | Record full-price orders and contribution for the same eligible audience after regular-price restoration | Compare with known seasonality, availability and campaign changes; do not claim causal recovery or deferral |
| Repeat decision | Stop, repeat or redesign only after the declared economics and full-price records are reviewed by the named owner | No automatic repetition and no ideal cadence |
Decide proceed, redesign or stop
Approval checkpoint
- Contribution remains acceptable in the chosen downside case. (not complete)
- The campaign and discount cash outflow fits the available cash window. (not complete)
- Stock and delivery capacity can serve the tested order range. (not complete)
- Baseline-order cannibalisation is included, not hidden. (not complete)
- The measurement window and comparison records are documented. (not complete)
- A named owner will review actual records without claiming causal proof. (not complete)
Promotion planning questions
- What is the minimum lift required?
- It depends on the entered contribution, discount, campaign cost and baseline-order treatment. Calculate a decision threshold, but do not call it a demand forecast.
- Why include discounts on baseline orders?
- Those customers may have purchased at full price without the campaign. Ignoring their discount can overstate the scenario contribution.
- Does a profitable result prove the promotion caused the sales?
- No. It is a planning scenario. Seasonality, other campaigns and customer behaviour can affect observed sales.
- How often should the offer repeat?
- No ideal cadence is supplied. Apply the recorded repeat rule only after regular-price restoration, promotion economics and the post-offer full-price window are reviewed.
- Can I use a “was” price or recurring deadline?
- Only when the claim is truthful, supportable and permitted under the applicable local rules. This global guide does not approve a reference price, scarcity statement or deadline.
Methodology sources
- Promotion Calendar Profit methodology — Margin101
- Discount Profit Impact methodology — Margin101: Separate owner for discount recovery and required-volume calculations.
- Consumer Price and Promotion Expectations — Journal of Marketing Research: Peer-reviewed context for promotion frequency, depth and expected prices; not an individual forecast.
- Reference-price adaptation under repeated promotion exposure — Journal of Retailing and Consumer Services: Peer-reviewed experimental context only; no universal effect size or cadence.
- Dynamic pricing and reference-price response — Journal of Business Research: Corroborates context dependence; does not establish an outcome for one business.
Test the promotion and adjacent constraints
- Promotion Calendar Profit Planner
Compare cumulative promotion contribution across periods
- Discount Profit Impact Planner
Find whether added volume can recover profit after a discount