# AOV

> Average order value (AOV) is the average revenue of one order, calculated by dividing total purchase revenue by the number of purchases recorded in the same period.

Source: https://adops.id/glossary/aov/
Last updated: 2026-08-20
Publisher: AdOps (https://adops.id) — an independent product, not affiliated with Meta Platforms, Inc.

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**Abbreviation:** AOV

**Also known as:** Average order value, Average basket value

**Formula:** AOV = purchase revenue ÷ number of purchases

**In AdOps:** AdOps has no metric named AOV. It carries both inputs separately — Purchase Value (`action_values.omni_purchase`) and Purchases (`actions.omni_purchase`) — and a target AOV maintained in a Google Sheet can be pulled into a condition as a custom metric.

Average order value (AOV) is the average revenue of one order: purchase revenue divided by the number of purchases in the same period. AdOps has no AOV metric, but it carries both inputs, Purchase Value and Purchases, and a target AOV kept in a Google Sheet can be referenced inside a condition as a custom metric.

## How is AOV calculated?

Divide revenue by orders over the same window. A campaign that produced Rp 42,000,000 of purchase value from 300 purchases has an AOV of Rp 140,000. The same Rp 42,000,000 from 600 purchases gives an AOV of Rp 70,000, which halves the amount that campaign can afford to pay for each purchase.

## Why does AOV set your cost ceiling?

AOV multiplied by contribution margin is the most an order can cost before it loses money. At an AOV of Rp 140,000 and a 35% margin, the ceiling is Rp 49,000 per order. A Cost per Purchase condition set at Rp 45,000 leaves Rp 4,000 of headroom, and it needs revisiting the moment the product mix shifts.

## How do you use AOV inside AdOps?

Custom metrics in AdOps are backed by Google Sheets. A metric names a spreadsheet id, a sheet name, a lookup column and a value column, and the engine resolves it at evaluation time, caching rows in memory for 2 minutes with a MongoDB fallback. That lets a condition test a live Meta metric against a target a human maintains in a spreadsheet.