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Platform mechanics

What is a Lookalike Audience?

A lookalike audience is an audience the ad platform builds by taking a source list of your existing customers and finding more people who resemble them. On Meta you set its size from 1% to 20% of the population in the locations your ad set targets (location is no longer set on the lookalike itself): 1% is the closest match to your source with the smallest reach, and larger percentages trade similarity for reach. Its quality is capped by the quality of the source list.

The two levers

A lookalike has exactly two inputs, and both decide its quality. The seed is the source customer list you feed it; the lookalike inherits that list's quality exactly, so a small, clean list of real buyers produces a far better audience than a large, noisy one. The audience size is how wide you cast: 1% is the slice of the targeted population most similar to your seed, and each step up toward 20% adds reach while loosening the resemblance.

How to use it

For quality-led lead generation, start tight at 1% to 2% off a high-intent seed and widen only once you have exhausted it, watching lead quality as you go. It pairs naturally with retargeting in a full-funnel setup, and it is only as trustworthy as the pixel or CAPI signal feeding the seed. We work through the trap in a lookalike only copies the seed you feed it.

Common questions

What percentage should a lookalike audience be?

For quality, start at 1% to 2%, the closest match to your source. Larger percentages such as 5%, 10%, or up to 20% reach more people but resemble your source less, so they suit scaling for volume rather than precision.

Why is my lookalike audience low quality?

Usually the seed. A lookalike copies whatever list you built it from, so a noisy or low-intent source produces a low-intent audience at scale. Rebuild it from a clean list of your real, high-value customers.

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