Average Order Value (AOV)

The Average Order Value (AOV) metric represents the average revenue per purchase. It is calculated as total revenue divided by the number of purchases.

Metric model

Name
metric
Type
string
Description
Always aov for this metric.
Name
value
Type
float
Description
AOV value for the current period.
Name
previous
Type
float
Description
AOV from the previous comparable period.
Name
change
Type
float
Description
Percent change between periods.
Name
formattedValue
Type
string
Description
Human-friendly value of AOV.
Name
formattedPrevious
Type
string
Description
Human-friendly previous AOV.
Name
period.id
Type
string
Description
Time period ID (e.g., 7d).
Name
period.name
Type
string
Description
Readable label for the period.
Name
periodRange.current.start
Type
string
Description
ISO timestamp for current period start.
Name
periodRange.current.end
Type
string
Description
ISO timestamp for current period end.
Name
periodRange.previous.start
Type
string
Description
ISO timestamp for previous period start.
Name
periodRange.previous.end
Type
string
Description
ISO timestamp for previous period end.
Name
performance.duration
Type
float
Description
Duration in milliseconds to compute the metric.
Name
performance.formatted
Type
string
Description
Formatted response time.

GET/api/metrics/average-order-value

Retrieve AOV metric

This endpoint returns the average order value over a specified period.

Optional query parameters

Name
period
Type
string
Description
The time period for which to fetch the metric. Common values:
- today
- yesterday
- 7d
- 30d
- this_month
View full list of supported periods →

Request

GET

/api/metrics/average-order-value

curl -G http://localhost:3000/api/metrics/average-order-value \
  -H "Authorization: Bearer {token}" \
  -d period=7d

Response

{
  "metric": "aov",
  "value": 33.62,
  "previous": 33.70,
  "change": -0.25,
  "formattedValue": "€ 33,62",
  "formattedPrevious": "€ 33,70",
  "period": {
    "id": "7d",
    "name": "Last 7 days"
  },
  "periodRange": {
    "current": {
      "start": "2025-03-16T08:50:55.027Z",
      "end": "2025-03-23T08:50:55.026Z"
    },
    "previous": {
      "start": "2025-03-09T08:50:55.027Z",
      "end": "2025-03-16T08:50:55.026Z"
    }
  },
  "performance": {
    "duration": 823.27,
    "formatted": "823 ms"
  }
}

Use cases

Track how order size evolves over time
Segment by campaign to assess cart behavior
Optimize upsells, bundles, and pricing strategies