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Set Up Meta Lookalike Campaigns

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Last updated 3 days ago

You can use Primer to create lookalike audiences based on your CRM segments, then launch campaigns directly on Meta.

For additional details and real campaign outcomes, check out Primer's Meta Lookalikes Use Case

Here's how to set it up:

Create a "Best Customers" List (Champion Audience) in Primer

  • Select Meta: In Primer, choose Meta as your audience destination.

  • Upload Customer Data: Upload a list of closed/won customers or high-quality leads to build your seed list.

  • Use Historical Win Rates: Use Primer's "Historical Win Rates" feature to identify firmographic patterns among top-converting companies (e.g., industry, size, title).

  • Filter (Optional): Refine your list by job titles that lead to sales.

  • Sync to Meta: Send this champion seed list to your Meta account.

Create an Anti-Persona Exclusion List

  • Identify Exclusions: Build a list of companies or individuals you want to avoid targeting.

  • Define Rules: Exclude companies or contacts based on firmographics that don’t align with your ICP, such as small teams (<50 employees), students, or irrelevant job titles.

  • Push to Meta: Send this "anti-persona" exclusion list to your Meta account.

Set Up Your Meta Ad Campaign

  • Create Lookalike: In Meta, create a 1% lookalike audience from your "champion seed list."

  • Target Lookalike: In your ad set settings, target this 1% lookalike audience.

  • Add Exclusions: Add all your "anti-persona" exclusion lists to your ad set.

  • Disable Advantage+ Audience Expansion: This prevents Meta from expanding your audience beyond your selected lookalike and exclusions, maintaining precise targeting.

Launch and Test Your Campaign

  • Go Live: Activate your Meta ad campaign.

  • A/B Test: Set up an A/B test to compare:

    • Ad Set A: 1% lookalike + exclusions.

    • Ad Set B: 1% lookalike only.

  • Analyze Results: Compare performance to see how exclusions improve lead quality.

  • Track key metrics: Monitor metrics like CPL (cost per lead), match rate, and SQL rate to measure impact and optimize further.