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

# Targeting

> Set up targeting experiments to test different audiences for your ads.

A targeting experiment is an audience-level group that sits beneath an initiative. Each targeting experiment defines who sees your ads — their age, gender, location, interests, and daily budget. Because each initiative can have multiple targeting experiments, you can A/B test completely different audiences within the same campaign without duplicating your creative work.

## Add a targeting experiment

<Steps>
  <Step title="Select the initiative">
    On the funnel canvas, locate the initiative you want to add targeting to.
  </Step>

  <Step title="Add a targeting experiment">
    Click the **+** button on the initiative node. A new targeting experiment node is created and connected below the initiative.
  </Step>

  <Step title="Name the experiment">
    Click the targeting node to open its settings panel. Enter a name that describes the audience — for example, "Women 25–44 US broad" or "Lookalike 1% purchase list".
  </Step>

  <Step title="Configure targeting parameters">
    Set the audience parameters in the settings panel:

    * **Targeting type** — Choose the audience strategy:
      * `broad` — Let Meta's algorithm find the best audience within your other constraints.
      * `interest_stack` — Target by specific Meta interests. Add interests by name; Fig resolves them to Meta interest IDs.
      * `lookalike` — Target users similar to a source audience in your Meta ad account.
      * `retargeting` — Reach people who have previously interacted with your ads or pages.
    * **Age range** — Set the minimum (default 18) and maximum (default 65) age.
    * **Gender** — Target `all`, `male`, or `female`.
    * **Geo locations** — Add one or more countries, regions, cities, or radius targets. Defaults to the United States if left empty.
    * **Interests** — If using `interest_stack`, search for and add Meta interest targets. Fig stores the canonical Meta interest IDs so your targeting is accurate when published.
    * **Conversion event** — Specify the Meta pixel event to optimize for (e.g. `Lead` or `Purchase`).
    * **Daily budget** — Set a budget at the targeting level. Use this when the parent initiative has its budget type set to `set at group`.
  </Step>
</Steps>

## Multiple targeting experiments per initiative

Add as many targeting experiments to an initiative as needed. Each experiment appears as a separate node below the initiative on the canvas, and each can have its own unique audience settings and daily budget.

<Tip>
  Running two targeting experiments simultaneously — for example, broad vs. interest-stacked — is an effective way to discover which audience delivers better results for the same offer and creative.
</Tip>

## Targeting statuses

Targeting experiments share the same status lifecycle as initiatives:

| Status    | Meaning                   |
| --------- | ------------------------- |
| `draft`   | Not yet submitted to Meta |
| `syncing` | Being pushed to Meta      |
| `review`  | Under Meta review         |
| `live`    | Active and delivering     |
| `paused`  | Paused                    |
| `error`   | A problem occurred        |

<Warning>
  Moving a targeting experiment to `syncing`, `review`, or `live` requires its parent initiative to be properly configured with a connected Meta account.
</Warning>

## Reorder targeting experiments

Use the left and right arrow controls on a targeting node to change its position under the parent initiative. This is a visual change only.

## Delete a targeting experiment

Open the targeting node's settings panel and select **Delete**. Deleting a targeting experiment removes it and all the ad assets beneath it from the workflow.