A lookalike audience is a platform-built audience of people who statistically resemble a source you provide — your customers, converters, or high-value users — used to find new buyers who behave like existing ones.
Definition
You upload or connect a seed (customer list, pixel converters, engagers), and the platform's models find users with similar signals. Quality follows the seed: a lookalike of your best customers finds better prospects than a lookalike of everyone who ever visited. In the broad-targeting era, explicit lookalikes matter less on Meta — the delivery AI effectively builds them implicitly from your conversion signal — but the seed-quality principle still governs what the machine learns to chase.
Why it matters
Lookalikes turned first-party data into prospecting reach, and their logic now runs under the hood of every goal-based campaign: the platform models 'people like your converters' whether you build the audience or not. That makes conversion signal hygiene the real targeting lever.
In agentic execution
Adlyse's agents manage audience inputs as part of execution — refreshing seeds, retiring stale segments, and shifting between explicit audiences and broad delivery based on what's actually converting, with human approval on changes.
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