Lookalike audiences

Lookalike audiences are a powerful targeting feature offered by major digital advertising platforms like Meta, Google, TikTok, and other ad networks that allow marketers to reach new users who closely resemble existing high-value customers, users, or players.

In other words:

• You have some excellent, high-paying players in your game, users in your app, or customers of your store
• You want more
• You share something that identifies those users to major marketing platforms (like an email address, cookie, IDFA, or GAID)
• You ask that platform to find new users or customers who are likely to to be similar
• They form an “audience” that you can target with ads
• The goal is that they respond positively and also become high-value users, players, or customers

These audiences can be generated fairly simply, based on your indicators of high value people. The big platforms often use sophisticated machine learning algorithms that analyze behavioral, demographic, and interest-based patterns to identify people who are similar to them.

Audiences require use of an identifier, like a GAID or an email address. Because IDFAs are more scarce on iOS post App Tracking Transparency, audiences are harder to do on iOS than they used to be.

Acquiring new high-quality users is critical for any growth marketer. However, manually identifying and reaching new potential customers who are just as valuable as your existing users is incredibly difficult. And blindly targeting any particular set of people in the hope that they’ll be similar is expensive.

Lookalike audience solves this by automating the discovery of new prospects. 

By leveraging platform-level data signals — often far richer than what advertisers can access on their own — these audiences help brands efficiently scale campaigns, increase ROI, and minimize wasted ad spend.

When they work well, lookalike audiences almost clone your best customers — giving you new ones just like them with similar behavior and purchasing potential.

1: Define a source audience

To create a lookalike audience, you have to define a source audience. That’s typically a group of people who have taken a high-value action. In other words, they did something like:

• Made a purchase
• Subscribe to a service
• Reach a specific level in a mobile game
• Stayed active past Day 7 in your app

Critically, your source audience must meet a minimum size requirement, usually at least a few hundred users. The bigger, more data-rich, and behaviorally consistent this group is, the more effective your lookalike audience can be.

2: Choose a similarity range

Some platforms then allow you to set a similarity percentage or size range. 

A 1% lookalike means the audience closely resembles your source audience. This often results in high performance but low scale. A 5–10% lookalike includes broader user segments that are still similar but offer more reach, likely at the cost of slightly lower performance.

Experimentation will give you a better idea of where to set your lookalike ranges.

3: Audience creation and deployment

Once you’ve defined your source audience and chosen your similarity range, the ad platform’s algorithm takes over. 

Using thousands of data points that the platform has access to on its users — think browsing behavior, interests demonstrated on-platform, device usage, app installs, location, purchase intent, and more — it builds a new audience segment that’s likely to behave like your original users. 

You can then target this audience in your ad campaigns just like any other.

1. Mobile app user acquisition

Lookalikes are ideal for acquiring new users who are more likely to convert. For example, if your app monetizes through subscriptions, creating a Lookalike of your paying subscribers can help you find others who are likely to subscribe.

2. Retail LTV optimization

Marketers often create lookalikes based on high-LTV cohorts (e.g., top 10% or 25% of spenders) to focus spend on acquiring users with the best long-term revenue potential.

3. Retargeting complement

Lookalike audiences can complement retargeting strategies by expanding your reach to new but similar audiences when your first-party data pool becomes saturated.

4. Localization

If you’re expanding to a new country, you might use lookalike audiences based on successful users in a neighboring or similar market to help accelerate learning and reduce risk.

1. Quality > Quantity

Your source audience should be highly engaged and valuable. A smaller but high-intent group will generally outperform a large, mixed-quality source, as long as it meets minimum size requirements.

2. Segment your source audiences

Don’t just build one lookalike audience. Segment users by behavior (e.g., big spenders, frequent users, long-term retainers) and test which ones perform better.

3. Refresh regularly

As user behavior evolves and your app or business grows, your lookalike audiences performance may degrade. Refresh your source audiences regularly … perhaps monthly.

4. Combine with other targeting

Overlay lookalike audiences with interest-based or demographic filters to refine performance or tailor creative more effectively.

5. Monitor overlap

If you’re using multiple lookalikes, check for audience overlap to avoid bidding against yourself and driving up costs.

Avoid the common pitfalls with lookalike audiences …

• Relying too heavily on 1 audience: Audience fatigue and diminishing returns can hit quickly if you don’t rotate or refresh
• Using poor-quality source data: Garbage in, garbage out. If your source audience isn’t actually representative of your ideal users, performance will suffer.
• Ignoring creative alignment: Lookalikes perform best when ad messaging reflects what resonates with your source audience.
• Not testing similarity ranges: A 1% Lookalike might drive high ROAS but limit scale. Testing higher percentages can uncover more efficient growth.

Lookalike audiences are a cornerstone of growth marketing, helping brands acquire new users who act like their best customers. When built on strong first-party data and used thoughtfully, they can enable scalable, efficient, and high-ROAS campaigns across platforms.

Whether you’re a mobile app developer, eCommerce brand, or B2B SaaS company, investing in smart lookalike strategies is one of the most reliable ways to grow intelligently in a privacy-conscious world where marketing signal is getting harder to read.