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

# AdAdvisor Targeting Skill: Broad-First Meta Ad Audience Strategy

> Broad-first prospecting, lookalike tiers, retargeting funnels, custom-audience creation, and the exclusion logic that keeps Meta (Facebook) prospecting from cannibalizing retargeting.

The **AdAdvisor targeting skill** encodes the post-iOS 14 reality of Meta (Facebook) ads: **broad has decisively won** for prospecting, and creative does the targeting. Lebesgue's 2025 data and Meta's own published case studies converge. Broad targeting plus strong creative outperforms detailed interest stacking at virtually every budget level.

## When should I use the targeting skill?

Triggers on phrases like:

* "Audience"
* "Lookalike", "LAL"
* "Retargeting"
* "Interests"
* "Exclude"
* "Custom audience"
* "Broad targeting"
* "Audience size"
* "Who should I target"
* "Estimate reach"
* "Build a lookalike"

## What is the right Meta audience hierarchy in 2026?

For prospecting:

| Priority    | Approach                              | When                                                               |
| ----------- | ------------------------------------- | ------------------------------------------------------------------ |
| 1 (default) | Broad + Advantage+ Audience ON        | Most ecom, most lead-gen, almost all DTC                           |
| 2           | Lookalike (1% LAL of high-value seed) | When you have a seed with 1,000+ high-value customers              |
| 3           | Lookalike (3% to 5% LAL)              | For scale, lower precision but more reach                          |
| 4           | Interest targeting                    | Only when broad and LAL are exhausted, OR for very specific niches |
| 5           | Lookalike (10%)                       | Essentially equivalent to broad. Use broad instead.                |
| 6           | Detailed-interest stacking            | Dead since June 2025 (Meta consolidated). Skip.                    |

For retargeting (layered funnel):

| Layer         | Audience                          | Retention       |
| ------------- | --------------------------------- | --------------- |
| Warm-1        | All website visitors              | 30 days         |
| Warm-2        | View Content / Add to Cart        | 30, 60, 90 days |
| Warm-3        | Email subscribers (customer list) | n/a             |
| Engagement    | Page / IG profile engagers        | 180 days        |
| Video viewers | 25%+ or 50%+ completion           | 180 days        |

## How do I build a Meta lookalike audience that actually works?

The skill's seed-quality hierarchy, best to worst:

1. LTV-tier customer list (top 25% by lifetime value)
2. Repeat purchasers (2+ orders)
3. All purchasers (180-day)
4. High-engagement video viewers (75%+ completion)
5. All-page-view (worst seed. Resembles broad.)

Then start at 1% LAL for precision and expand to 3% and 5% in separate ad sets as you scale. Value-based LALs (seeded with revenue data per customer) outperform basic LALs per Salesforce 2026 data, but require sending purchase value through pixel and CAPI.

Meta requires seeds of 100+ people. The skill flags any seed below 1,000 as statistically thin.

## Which exclusions should every prospecting ad set use?

Cannibalization is the silent killer. The skill enforces exclusions:

<AccordionGroup>
  <Accordion title="Exclude purchasers (30 to 90 days) from all prospecting">
    Otherwise you bill yourself to serve ads to people who already bought. Use `excluded_custom_audiences` on every prospecting ad set.
  </Accordion>

  <Accordion title="Exclude existing email subscribers from prospecting">
    Same logic. Customer-list audiences from CRM go in the excluded list.
  </Accordion>

  <Accordion title="Exclude active retargeting audiences from ASC">
    Otherwise ASC and manual retargeting bid against each other.
  </Accordion>

  <Accordion title="Exclude cart abandoners from broad retargeting going elsewhere">
    Avoid conflicting messaging from two different retargeting flows hitting the same person.
  </Accordion>
</AccordionGroup>

## What audience sizes work for prospecting, retargeting, and lookalikes?

| Use case                            | Healthy range           | Below threshold                                                                  |
| ----------------------------------- | ----------------------- | -------------------------------------------------------------------------------- |
| Prospecting                         | 1 million to 50 million | Under 500K means slow learning. Over 50 million means Meta over-delivers poorly. |
| Retargeting                         | 1,000+                  | Below 1,000 means delivery is unstable.                                          |
| Lookalike seed                      | 100+ (Meta requirement) | Under 1,000 is statistically thin.                                               |
| Custom audience for active delivery | 1,000+                  | Below means Meta pauses delivery.                                                |

The skill uses `adadvisor:estimate_audience_size` to validate any new targeting spec before committing.

## What is the AdAdvisor targeting MCP workflow?

```
adadvisor:list_custom_audiences         → existing audiences with subtype and delivery_status
adadvisor:search_targeting(...)         → interest, geo, behavior IDs (never invent these)
adadvisor:estimate_audience_size(...)   → reach sanity check
adadvisor:create_website_audience(...)  → build retargeting from pixel events
adadvisor:create_lookalike_audience(...)→ build LAL from a seed (1 to 6 hours to populate)
adadvisor:update_adset_targeting(...)   → apply with auto-fix for deprecated interest IDs
```

The MCP server runs Meta's `/reachestimate` validation and auto-fixes deprecated interest IDs (up to 3 retry attempts) before applying the change. If it cannot fix, the skill surfaces the exact validation error.

## What anti-patterns does the targeting skill prevent?

<AccordionGroup>
  <Accordion title="Stacking 8 interests as detailed targeting on prospecting">
    Dead since June 2025. The skill defaults to broad with Advantage+ Audience on.
  </Accordion>

  <Accordion title="Building a 100K-person retargeting audience and treating it like prospecting">
    Retargeting is tactical, not scalable. The skill keeps prospecting on broad and lookalike.
  </Accordion>

  <Accordion title="Forgetting excluded_custom_audiences=[purchasers] on prospecting">
    Always exclude existing customers. The skill enforces this on every prospecting `create_adset` call.
  </Accordion>

  <Accordion title="Pasting interest IDs from a different account">
    Interest IDs are account-scoped per Meta. The skill always re-queries via `search_targeting` in the current account.
  </Accordion>

  <Accordion title="Setting advantage_audience: false to 'control' targeting">
    Advantage+ Audience finds buyers outside your spec. That is the point. The skill leaves it on unless there is a regulatory reason.
  </Accordion>

  <Accordion title="Building a lookalike on a 50-person seed">
    Meta requires 100+. The skill flags any seed below 1,000 as statistically thin.
  </Accordion>
</AccordionGroup>

## How do I install the targeting skill?

<Columns cols={2}>
  <Card title="Claude Code" icon="terminal" href="/skills/install-claude-code">
    Ships with the full plugin install.
  </Card>

  <Card title="Claude.ai & Desktop" icon="cloud" href="/skills/install-claude">
    Download [adadvisor-targeting.zip](https://github.com/AdAdvisor/skills/releases/latest/download/adadvisor-targeting.zip) and upload via Settings, Capabilities, Skills.
  </Card>
</Columns>

## Frequently asked questions

<AccordionGroup>
  <Accordion title="Should I use broad targeting or interest targeting for Meta ads in 2026?">
    Broad targeting with Advantage+ Audience ON, for almost every account. Lebesgue's 2025 data and Meta's own case studies converge: broad plus strong creative outperforms interest stacking at virtually every budget level. Detailed-interest stacking has been dead since Meta's June 2025 detailed-targeting consolidation. The targeting skill defaults to broad.
  </Accordion>

  <Accordion title="What is the best seed for a Meta lookalike audience?">
    LTV-tier customer list (top 25% by lifetime value) gives the best lookalikes. After that: repeat purchasers (2+ orders), then all purchasers within 180 days, then 75%+ video completers. All-page-view is the worst seed since it resembles broad. Meta requires 100+ people in the seed. Under 1,000 is statistically thin.
  </Accordion>

  <Accordion title="What is the difference between 1%, 3%, and 5% Meta lookalikes?">
    The percentage is the share of the country's population that resembles your seed audience. 1% LAL is the most similar but smallest (about 2 million people in the US). 3% and 5% trade similarity for reach. Use 1% for precision when you have proven creative, 3% to 5% for scale. 10% LAL essentially equals broad targeting and is usually skippable.
  </Accordion>

  <Accordion title="Why should I always exclude existing customers from prospecting?">
    Otherwise you are paying Meta to serve ads to people who already bought. Cannibalization inflates CPA and tanks measured ROAS. The targeting skill enforces `excluded_custom_audiences=[purchasers]` on every prospecting `create_adset` call. Use a 30 to 90 day purchaser audience as the exclusion.
  </Accordion>

  <Accordion title="What is Advantage+ Audience and should I keep it on?">
    Advantage+ Audience lets Meta find buyers *outside* your targeting spec when it sees high-value signal. It is on by default on most objectives in 2026 and the targeting skill leaves it on unless there is a regulatory reason to disable it. Disabling it deliberately limits Meta's ability to find buyers and almost always hurts performance.
  </Accordion>

  <Accordion title="How big should my Meta prospecting audience be?">
    1 million to 50 million people. Below 500K means slow learning (Meta cannot collect 50 conversions per week to exit the learning phase at a healthy budget). Above 50 million, Meta over-delivers poorly because the signal-to-noise ratio drops. The skill uses `adadvisor:estimate_audience_size` to validate before committing.
  </Accordion>
</AccordionGroup>

## Related skills

<Columns cols={3}>
  <Card title="Launch" icon="rocket" href="/skills/adadvisor-launch">
    Pairs with launch when targeting is part of a new campaign.
  </Card>

  <Card title="Scale" icon="chart-line" href="/skills/adadvisor-scale">
    Horizontal scaling = audience expansion via new LAL tiers or geos.
  </Card>

  <Card title="Audit" icon="magnifying-glass" href="/skills/adadvisor-audit">
    Audit surfaces audience overlap and missing exclusions. This skill fixes them.
  </Card>
</Columns>