> ## Documentation Index
> Fetch the complete documentation index at: https://docs.growthbook.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Compound Metrics

> Measure the share of experiment units who did every one of several things, in any order, with compound fact metrics in GrowthBook.

Compound Metrics measure the share of exposed units who did **every** one of several things, in any order. For example, users who viewed pricing **and** started a trial. The result is a single conversion rate, analyzed like any other proportion metric.

A compound metric is a [Fact Table](https://docs.growthbook.io/app/metrics.md) metric. Instead of a numerator, you define a list of **components**, each a Fact Table plus row filters.

> [!NOTE]
>
> **Compound, funnel, or threshold?**
>
> | Type | Use it for |
> | - | - |
> | Compound | Several distinct actions, order ignored, one number. |
> | [Funnel](https://docs.growthbook.io/app/metrics/funnel.md) | Steps that must happen in order, with a rate per step. |
> | [Threshold](https://docs.growthbook.io/app/metrics.md#proportion-metrics) | One action done at least N times, such as placed 3+ orders. |

## How a unit passes

A unit passes when it has at least one matching event for **every** component inside the [metric window](https://docs.growthbook.io/app/metrics.md#metric-windows).

* Order does not matter, and there is no co-occurrence window. Viewing pricing in week 1 and starting a trial in week 3 passes.
* One event can satisfy several components if it matches all component's row filters (e.g. `event_name = view_pricing` and `plan = trial` could be satisfied by a single event).
* Units with no matching events fail.

Metric windows, metric delay, target MDE, and [Bayesian priors](https://docs.growthbook.io/app/metrics.md#bayesian-priors) work as on a proportion metric.

A compound metric needs 2 to 20 components across at most 5 distinct Fact Tables, and no two components may be identical. In experiments, every component's Fact Table must share an identifier type with the assignment table (or reach it through a Join Table); otherwise the metric is excluded from analysis.

Not supported:

* Use as activation metrics
* [Metric Slices](https://docs.growthbook.io/app/metrics.md#metric-slices) are not supported.
* Standalone metric analysis or Product Analytics

## Compound metrics in experiment results

Results render like any other proportion metric. The [metric drilldown](https://docs.growthbook.io/app/experiment-results.md#metric-drilldown) adds a **Components** tab showing how many units in each variation matched each component. These counts are descriptive, shown for the overall result only, and carry no statistics.

## Managing compound metrics with the API

Set `metricType` to `compound` and pass `compoundSettings`. Omit `numerator` and `denominator`; they are not allowed. The metric inherits its data source from the first component's Fact Table.

```bash theme={null}
curl -X POST 'https://api.growthbook.io/api/v1/fact-metrics' \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "name": "Viewed pricing and started trial",
    "owner": "you@example.com",
    "metricType": "compound",
    "compoundSettings": {
      "components": [
        {
          "factTableId": "ft_events",
          "rowFilters": [
            { "column": "event_name", "operator": "=", "values": ["view_pricing"] }
          ]
        },
        {
          "factTableId": "ft_subscriptions",
          "rowFilters": [
            { "column": "plan", "operator": "=", "values": ["trial"] }
          ]
        }
      ]
    }
  }'
```

`compoundSettings.components` is a required array of 2 to 20 objects, each with `factTableId` and `rowFilters`. `GET` responses for compound metrics include `compoundSettings` and omit `numerator`. Listing fact metrics filtered by `factTableId` returns compound metrics with a component on that Fact Table.