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Comparison · E-commerce

Average Order Value vs Units per Order

Separate order value, unit count, and product mix so a larger basket is judged by contribution rather than revenue alone.

By PriceAndProfit Editorial Updated

Average order value measures revenue per order, while units per order measures quantity per order. Both can increase without improving contribution. A higher-priced item can lift order value without adding units, and a discounted multipack can add units while reducing revenue per unit. Track the two measures together with contribution per order and total contribution so the dashboard reveals which economic change actually occurred.

Calculate a consistent starting point

A hypothetical period contains 200 completed orders, $12,000 of merchandise revenue after discounts, and 300 units sold. Average order value is $60 and units per order is 1.5. Average revenue per unit is $40. For this example, shipping collections and taxes are excluded from order value. Other reporting systems may use different definitions, so write the scope next to the metric and keep it consistent across periods.

Average order value = defined revenue ÷ orders; units per order = units ÷ orders; contribution per order = (revenue − included variable costs) ÷ orders
Hypothetical periods with consistent revenue definitions
MeasurePeriod 1Period 2
Orders 200 200
Average order value $60 $65
Units per order 1.5 2.0
Contribution per order $25 $20
Total contribution $5,000 $4,000

Explain a mixed result

In a second hypothetical period, 200 orders contain 400 units and generate $13,000 of comparable revenue. Order value rises to $65 and units per order rises to 2, but revenue per unit falls to $32.50. Suppose variable product and fulfillment costs rise from $7,000 to $9,000. Contribution falls from $5,000 to $4,000, despite higher revenue and more units. Per-order contribution drops from $25 to $20.

Identify the driver before changing the offer

Break the result into price changes, discounts, product mix, and quantity. A promotion may encourage an extra low-margin item that adds weight or crosses a parcel threshold. A shift toward a higher-value product can lift order value while increasing returns. Compare the same product baskets where practical, then separately explain changes in the mix of baskets. An aggregate average cannot reveal which item caused the change.

Include customers who did not buy

A bundle test can raise average order value among completed orders while reducing the number of buyers. Suppose the original offer generated 200 orders contributing $25 each, or $5,000. A revised offer generating only 150 orders at $30 contribution each produces $4,500. The higher per-order measure does not offset lost order volume. Use comparable traffic or customer groups and account for acquisition expenses when interpreting the total.

Handle returns and measurement boundaries

Decide whether order count includes fully refunded orders and whether unit count is gross shipped units or retained units. Apply the same definition to numerator and denominator; subtracting refunded revenue while excluding the refunded order entirely can distort comparisons. Zero orders make order averages undefined, and zero units make revenue per unit undefined. Report those conditions explicitly. These metrics describe the observed basket and its costs; they do not prove that increasing order value causes higher profit.

Average order value

  • Measures: Revenue generated by an average completed order
  • Misses: Product cost, quantity, and the number of lost orders

Units per order

  • Measures: Quantity in an average completed order
  • Misses: Selling prices, discounts, and incremental fulfillment costs
Bottom line

Read basket metrics alongside contribution and total order volume; neither is a profit measure.

Method references: Shopify: customers reports; OpenStax: break-even and contribution analysis. Accessed October 22, 2026. All dollar figures are hypothetical worked examples.

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