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Algorithm Strategy•8 min read

Does Broad Targeting Work Better Than Lookalike Audiences?

Author

Digitopia LB

Published October 28, 2024

Reviewed August 6, 2026

Does Broad Targeting Work Better Than Lookalike Audiences?

Executive Summary

  • • Privacy changes reduced some observable conversion and matching signals used in audience creation.
  • • Broad Targeting allows Meta's AI to use your Creative as the primary targeting signal.
  • •
    Action: Test broader targeting when narrow audiences limit delivery or add unnecessary assumptions.

There is no universal winner between broad targeting and Lookalike Audiences. Broad gives Meta more room to optimize, while a strong lookalike can still be useful when its source data is relevant and large enough.

Why Lookalikes Failed (The iOS14 Effect)

Lookalike audiences rely on "Seed Data" (e.g., your email list or pixel events). Since Apple's App Tracking Transparency (ATT) rollout, the match rate of this data has dropped below 40%. This means when you upload a customer list to build a 1% LAL, Meta can only match a fraction of those users. The "Lookalike" is based on incomplete, low-quality data.

"Restricting the audience with Interests or LALs is actively preventing the AI from finding cheaper conversions." — Meta Engineering Team

The Power of Broad Targeting

Broad targeting gives Meta more flexibility within the location, age, and other controls you keep. Delivery can use creative response, conversion signals, and platform behavior to find likely responders.

How it works:

  • You launch an ad about "Dog Toys."
  • Meta shows it to a small sample of users.
  • Dog owners click on it.
  • Meta's AI learns: "Oh, dog owners like this."
  • It finds MORE dog owners, even if they aren't in your "Dog Interest" list.

This is called Creative Targeting. Your ad copy and creative *are* the targeting.

Sources & References

  • 1. Meta AI Sandbox. "Generative AI and the Future of Ad Targeting." (2024).
  • 2. Common Thread Collective. "The Death of the Lookalike Audience." (Case Study).

?Frequently Asked Questions

In many modern Meta ad accounts, broad targeting outperforms lookalikes because Meta’s AI can use creative engagement signals to find buyers more effectively.
Apple’s privacy updates reduced data accuracy and match rates, weakening the quality of seed data used to build lookalike audiences.
Broad targeting gives Meta’s machine learning more flexibility to identify likely buyers using creative signals, engagement patterns, and pixel data.
Lookalikes can still work in some cases, especially with strong first-party data, but most modern scaling strategies rely heavily on broad targeting.
Creative targeting means the ad itself becomes the targeting mechanism. Meta learns who responds to the creative and automatically expands toward similar users.

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