Commerce
Average order value calculator
Average order value is sales divided by orders. The arithmetic is trivial; the reporting is where it goes wrong.
Used for revenue per customer and the repeat rate.
Average order value
$77.74
- Revenue per customer
- $100.42
- Orders per customer
- 1.29
- Above 1 means repeat purchasing.
AOV = total sales ÷ number of orders
The mistake almost every chart makes
There are two ways to compute AOV over a week and only one is right. Sum the week's sales, sum the week's orders, divide. Do not compute each day's AOV and average the seven numbers.
The second method treats a Sunday with two orders as equal in weight to a Black Friday with two thousand, and a single quiet day with one expensive order can move it by a third.
This is also why a correct AOV chart looks inconsistent with its own headline: each point is that day's ratio and the headline is the period's. They are not supposed to match.
Use the same filter on both sides
The easiest bug to write here is filtering the sales total to exclude refunded orders and forgetting to filter the order count. AOV then quietly drops and nothing looks obviously wrong.
Include refunded orders in both and AOV is the average value of orders placed. Exclude them from both and it is the average value of orders kept. Both are defensible. Only mixing them is not.
What actually moves AOV
Price increases move it evenly across every order, which is the easiest case to read.
Bundles and upsells move it only for the orders that take them, so the mean rises while the median order does not change at all. If AOV is up and nothing feels different, look at the distribution before celebrating.
One wholesale order moves it for a single day and then it falls back. If a single order can visibly move your AOV, the mean is the wrong statistic and you want the median.
Read it with volume
AOV rising while orders fall is a smaller, richer customer base. That might be the strategy or it might be a problem, and the ratio alone cannot say which.
Put sales, orders and AOV side by side. Sales climbing on flat orders is a bigger basket; sales climbing on flat AOV is simply more customers. One number cannot tell you which happened.
Questions
- How do you calculate average order value?
- Divide total sales in a period by the number of orders in the same period. Do not average the daily values: that weights a quiet Sunday equally with Black Friday.
- Why does my AOV headline not match my AOV chart?
- Because each chart point is that day's own ratio and the headline is the period's total sales divided by its total orders. They are not supposed to match, and a tool whose headline equals the mean of its points is calculating it wrongly.
- Should refunded orders count in average order value?
- Either, as long as both sides match. Include them in sales and in the order count and AOV is the average value of orders placed; exclude from both and it is the average value of orders kept. Filtering one and not the other is the common bug.
- Is average order value the same as revenue per customer?
- No. AOV divides by orders and revenue per customer divides by customers. A shopper who orders four times is four orders and one customer, so the two diverge as repeat purchasing rises.
- How do I increase average order value?
- Price rises move it evenly. Bundles and upsells move it only for the orders that take them, so the mean rises while the median does not. Watch the distribution rather than the mean if a single large order can move your figure.