What Are Lookalike Audiences? A Clear, Beginner-Friendly Explanation of How They Work

Definition in simple terms

A lookalike audience is a generated group of prospects that share similar attributes or behaviors with an existing audience you care about. You give a platform a seed—such as customers who bought your product—and the platform finds more people who resemble that seed.

What the seed is

The seed audience is the foundation. Common seed sources include customer email lists, website visitors tracked by a pixel, app users, people who added items to cart but didn't buy, or subscribers. The stronger and more representative the seed, the better the lookalike outcome.

What the platform does

Platforms like Meta, Google, and LinkedIn use their large datasets and machine learning to model the traits that characterize the seed audience. That modeling can include:

• Demographics (age, gender, location)
• Behavioral signals (pages visited, content consumed, purchase frequency)
• Interests and inferred affinities
• Device and platform usage patterns

Then the platform finds other users who match that profile within a defined geographic or similarity threshold.

What types exist

• Platform lookalikes: Native to ad platforms (Meta Lookalike, Google Similar Audiences, LinkedIn Matched Audiences lookalikes).
• Third-party modeled audiences: Providers that offer custom modeling and audience lists built from diverse data sources.
• Custom segments: Hybrid approaches that combine lookalikes with demographic or interest filters for tighter targeting.

How similarity is measured

Platforms typically allow advertisers to choose a similarity/scale tradeoff. For example, a 1% lookalike may mean the top 1% most similar users in a country—higher similarity, smaller audience. Larger percentages increase reach but decrease closeness to the seed.

What you need to create them

1. A seed audience: customer list, pixel events, or app activity.
2. Compliance with platform data rules and privacy laws (hashed emails, consent where needed).
3. An ad account with access to audience tools.

What they’re used for

Lookalike audiences are primarily used for prospecting—finding new potential customers—to expand acquisition while maintaining relevance. Common campaign goals include conversions, app installs, lead generation, and e-commerce sales.

Real-world example

A SaaS company selects its highest-value trial-to-paid converters as a seed. The ad platform builds a lookalike, the company runs a conversion-focused campaign, and CPA drops because the ads reach people behaviorally similar to those who convert.

What metrics matter

Track click-through rate, conversion rate, cost per acquisition, and post-acquisition metrics like retention and lifetime value. Compare lookalike performance to baseline targeting to judge effectiveness.

Limitations and considerations

• Seed quality is everything—garbage in, garbage out.
• Privacy policies and platform restrictions limit the granularity of data that can be used.
• Bias in seed data can propagate—if the seed represents a narrow demographic, the lookalike will reflect that.

Summary

Lookalike audiences are a machine-assisted way to find new users who behave like your best existing customers. For beginners: start with a clear, high-value seed, choose an appropriate similarity size, run controlled tests, and measure outcomes against other targeting approaches.