What is a Lookalike Audience?
A lookalike audience (also called a similar audience) is a targeting option that uses machine learning to find new people who share behavioral and demographic characteristics with your existing customers or high-value users.
How It Works
Lookalike audiences start with a "seed" audience — typically your customer list, website visitors, or app users. The ad platform analyzes the characteristics of this seed audience (demographics, interests, online behavior, purchase patterns) and finds other people in its network who match those characteristics but are not yet your customers.
On Meta, you create lookalike audiences from Custom Audiences and select a percentage (1-10%) that controls how closely the lookalike matches your seed. A 1% lookalike is the most similar (and smallest), while a 10% lookalike is broader but less precise. Google calls them "Similar Segments" (though they deprecated this in 2023, replacing it with optimized targeting and audience expansion). LinkedIn calls them "Predictive Audiences." TikTok calls them "Lookalike Audiences" and offers narrow, balanced, and broad options.
The quality of your lookalike depends entirely on the quality of your seed audience. A lookalike based on your top 100 highest-LTV customers will outperform one based on all website visitors, because the signal is more specific. The minimum seed size varies by platform — Meta recommends at least 1,000 people for a reliable lookalike.
Why It Matters for Advertisers
Lookalike audiences are one of the most effective prospecting tools in digital advertising. They let you find new customers who resemble your best existing customers, which typically produces much better results than broad interest-based targeting.
However, lookalikes have become less precise since Apple's iOS 14.5 privacy changes reduced the data available for audience matching. Many advertisers have had to supplement lookalikes with broader targeting strategies and rely more on creative quality to attract the right audience. Understanding when lookalikes work well versus when to use alternative approaches is now a critical skill.
How Ad Superpowers Helps
Ad Superpowers helps you monitor the performance of your lookalike audiences versus other targeting methods. Ask "Compare CPA between my lookalike audiences and interest-based audiences on Meta" to see which approach is delivering better results.
Our Meta tools can also help you analyze your Custom Audience sizes and composition — the building blocks for effective lookalikes. By monitoring audience overlap and refresh rates, you can keep your seed audiences clean and your lookalikes performing.
Related Terms
Creative Fatigue
Creative fatigue is the decline in ad performance that occurs when your target audience has seen the same ad too many times, leading to lower engagement and higher costs.
Frequency Capping
Frequency capping is an ad delivery setting that limits the maximum number of times a single user can see your ad within a defined time period, preventing overexposure and creative fatigue.
Conversion API (CAPI)
A Conversion API (CAPI) is a server-side tracking method that sends conversion events directly from your server to an ad platform's servers, bypassing browser-based tracking limitations like cookie blocking and ad blockers.
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