Practical promotion economics

Review the promotion, not just its sales chart.

A promotion review should explain what changed in contribution and which assumptions make that comparison meaningful. Start with a defined product, campaign and time window, then reconcile the result before deciding whether to repeat it. The examples here are synthetic.

Write the decision before calculating

Decide whether the review is about repeating an offer, choosing a discount, negotiating supplier support or clearing inventory. These decisions need different comparisons. A profitable campaign can still be inferior to doing nothing; a clearance offer can sacrifice product margin while improving future recoverable value.

Define the commercial boundary as well. The contribution of one promoted product is not automatically the contribution of the category, customer relationship or whole business. List the effects outside the initial row so they are not silently treated as zero.

  • Name the campaign and product or SKU.
  • Use one currency and one cost definition.
  • Specify the no-promotion sales expected over the same dates.
  • Record returns, supplier support and later displacement separately.

Build a bridge that reconciles

For a simple campaign with no returns or later effects, baseline contribution is baseline units × (regular price − variable unit cost). Promotion contribution is promotion units × (promotion price − variable unit cost) − additional campaign spending + supplier funding. Their difference is conditional on the baseline.

The same change can be explained as volume at the original unit contribution, the discount applied to all promotion units, campaign spending and funding. These components must sum to the total difference. This reconciliation is an accounting identity, rather than evidence that each component is a separately identified causal mechanism.

Worked review: higher sales, lower contribution

Suppose 1,000 units would have sold at €50 without the offer, with €25 variable cost. The promotion sells 1,600 units at €40 and costs €300 to run. Revenue rises from €50,000 to €64,000, but contribution falls from €25,000 to €23,700.

Bridge componentContribution effect
600 additional units × €25 regular contribution+€15,000
€10 price reduction × all 1,600 units−€16,000
Additional campaign spending−€300
Total change versus supplied baseline−€1,300

Map the decision worksheet to the workbench

Use the promotion-margin-trap template to reproduce the example. Enter gross sales units, not units already reduced by separately entered returns. Allocate each fixed cost once across product rows.

Worksheet itemCSV fieldExample
No-promotion volumebaseline_units1000
Gross promotion volumepromo_units1600
Regular / promotion pricesregular_price / promo_price50 / 40
Variable costunit_cost25
Additional fixed spendingpromo_spend300

What the result can support

The result supports a transparent comparison under the supplied inputs. It does not prove that the offer caused 600 additional sales. Availability, customer mix, seasonality and other campaigns can change the counterfactual. Review a range of plausible baselines before converting a small positive difference into a repeat decision.

Shopify's profit-report documentation also distinguishes product margins from margins after discounts and refunds. Use those source records to reconcile transaction definitions; do not assume a platform's gross-profit report contains every cost in this contribution model.

Questions before repeating the offer

Can a campaign with negative contribution change still serve a purpose? It can have an explicitly valued inventory, acquisition or retention objective. Document that separate benefit and its evidence rather than relabeling a loss as success.

Should all overhead be allocated to the campaign? Include the costs relevant to the decision. Keep unavoidable shared overhead separate from additional campaign spending, and explain the boundary in the report.

Put it to work

Source context

Guide text and examples were prepared independently for MarginTrial. Sources provide the stated methodological or product context. They do not validate the hypothetical commercial outcomes.

Open the worked case