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Lookalike Audience

A lookalike audience is a platform-built audience that matches the attributes of a seed list (e.g., converters) to find similar new prospects.

Definition

Lookalike audiences use a high-quality seed (like converters, high-LTV customers, or engaged leads) to find new people who resemble them based on platform data signals. Used in Meta/LinkedIn/Google, they expand reach to likely converters while maintaining targeting efficiency.

Why This Matters

Lookalikes scale prospecting with better fit than broad interest targeting, often yielding lower CPL/CAC when the seed is strong.

Common Types

Customer Lookalikes

Seeded with paying customers or high-LTV users.

Lead Lookalikes

Seeded with MQL/SQL/PQL leads for more qualified prospects.

Engagement Lookalikes

Seeded with high-engagement site visitors or email engagers.

Real-World Examples

1High-LTV Seed

Using top 10% LTV customers as seed improved ROAS on Meta.

2SQL Seed

Lookalikes from SQLs delivered lower CAC than generic interest targeting.

3Engager Seed

Lookalikes from long-session visitors outperformed broad audiences.

4Country-Specific

Separate seeds per region for localized performance.

How to Use This in MagnetHub

Export high-quality MagnetHub leads (or customers) to ad platforms as seeds. Build lookalikes to find new audiences likely to opt into your best-performing lead magnets.

See MagnetHub in Action

Watch how MagnetHub helps you implement this concept effortlessly

Best Practices

  • Use high-quality, clean seeds (converters, high LTV, SQLs)
  • Test different seed sizes and recency
  • Exclude converters from prospecting campaigns
  • Pair lookalikes with strong offers and proof
  • Monitor overlap and frequency to avoid saturation
  • Refresh seeds periodically to keep data current

Frequently Asked Questions

Related Terms

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