Lookalike Audiences are one of Meta's most powerful advertising features. Instead of manually targeting interests and demographics, you show Meta a sample of your best customers and say "find more people like these." Meta's algorithm analyzes hundreds of behavioral signals to find matching audiences at scale.
How Lookalike Audiences Work
You provide a source audience (Custom Audience) — typically past purchasers or leads. Meta analyzes the common characteristics of that source audience (interests, behaviors, demographics, device usage, content engagement) and finds users who match those patterns across its 3 billion+ user base.
Source Audience Requirements
Minimum 100 people in the same country. For best results: 1,000–50,000 quality users. Source quality matters more than size — a Lookalike of 500 actual purchasers outperforms a Lookalike of 10,000 unqualified leads.
Lookalike Percentage (1%–10%)
1% Lookalike = most similar to source (smallest, most targeted). 10% Lookalike = broadest similarity match (largest, least targeted). Start with 1–2% for highest quality. Scale to 3–5% when 1% audience is exhausted.
Best Lookalike Source Audiences
Purchase converters (best), high-value customers (LTV segmented), lead form completers, video viewers (25%+ of video watched), website visitors who reached checkout, and engaged social media followers (lower quality but scalable).
Stacking Lookalike Audiences
Create multiple Lookalike Audiences from different sources and stack them in one ad set. A 1% purchase Lookalike + 1% high-LTV Lookalike combined gives Meta broader signal data while maintaining quality targeting.
Lookalike Audience Refresh
Source audiences should be refreshed regularly — at least monthly. Customer behavior and Meta's user base evolve. Stale Lookalikes from year-old data can underperform compared to Lookalikes built on recent converters.