Common questions about Lookalike Audiences, answered.
What are lookalike audiences?▾
Lookalike audiences (called Similar audiences on some platforms) are targeting audiences a platform builds by finding new users who resemble a source group you provide — typically your best customers or converters. The platform analyzes the traits and behaviors of your seed audience and finds others who look similar, letting you prospect for new people most likely to behave like your existing high-value customers.
How are lookalike audiences built?▾
You supply a seed (source) audience — a custom audience like your customer list, purchasers, or high-value users — and the platform's algorithm identifies common characteristics, then finds other users who match that profile across its user base. You usually choose a size (how broadly to expand), trading similarity for reach. The quality of the seed strongly determines the quality of the lookalike.
Why do lookalike audiences work?▾
Because your existing customers are the best predictor of who else will convert — people who resemble them in behavior and attributes are more likely to want what you offer than a random or broad audience. Lookalikes let you prospect efficiently by extending the patterns of proven customers to new people, often outperforming generic interest or demographic targeting for finding net-new buyers.
How do I choose the best seed audience?▾
Use a high-quality, relevant source: your best customers, recent purchasers, or high-value/high-LTV users rather than all visitors or a low-intent list. A seed of genuinely valuable converters teaches the algorithm to find more like them; a noisy or low-intent seed produces a weak lookalike. Larger seeds give the algorithm more signal, but quality (who's in it) matters more than size.
How big should a lookalike audience be?▾
It's a similarity-versus-reach trade-off. A smaller percentage (e.g. 1%) is most similar to the seed and usually highest-quality but limited in reach; larger percentages (e.g. 5–10%) expand reach at the cost of similarity. Start tighter for quality, then test expanding for scale. With modern broad-targeting trends, some advertisers rely less on narrow lookalikes and more on the algorithm plus signals, but lookalikes remain a useful prospecting tool.
