Plain answer
A lookalike audience is a cold audience Meta builds by finding people who resemble a group you supply — usually your customers or converters. You provide the seed; Meta's models study who's in it and reach similar people you've never met. It's prospecting powered by your own data.
How lookalike audiences actually work
You pick a seed — a custom audience of purchasers, leads, or top customers — and a similarity range: the closest slice of a country's users, or a broader, looser one. Meta's models find the patterns in your seed and assemble strangers who share them. You never learn what the patterns are; you just target the output.
Why the seed decides everything
A lookalike is a photocopy — it inherits whatever the original contains. Seed it with purchasers and Meta hunts for buyers. Seed it with everyone who ever visited your site, including bounces, and Meta faithfully finds you more people who leave quickly. Given the choice, a smaller seed of your best customers beats a bigger seed of everyone. Garbage in, lookalike garbage out.
Lookalikes vs interest targeting
Interest targeting is you guessing what your buyers have in common ("small business owners," "fitness"). A lookalike lets the data answer instead, and it typically finds patterns no owner would articulate. Meta's own automation (Advantage+) increasingly blurs and expands these choices anyway — but the principle survives: the strongest signal you can hand any of it is a clean seed of real buyers.
What this means for your ads
Earn your lookalike before you build it: get the pixel collecting purchase or lead events first, since a seed audience too small to model won't produce anything useful. Then test the lookalike against your best interest audience in separate ad sets and let cost per result pick the winner — it usually does so quickly.
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