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THE TECHNICAL LANGUAGE OF DIGITAL B2B INFRASTRUCTURE

CONCEPT
PERFORMANCE ADVERTISING

Lookalike Audience

An ad targeting audience built by a platform to reach new people who share traits with an advertiser's existing customers or source list.


BUSINESS RELEVANCE

Lookalikes turn first-party customer data into prospecting reach, so the quality of the seed list, such as high-value buyers rather than all leads, directly shapes the cost and quality of the new customers acquired.


IMPLEMENTATION EXAMPLE

An online retailer uploads its top 2,000 customers by 12-month revenue as a Meta custom audience, builds a 1% lookalike in Germany and a broader 3% to 5% lookalike in a separate ad set, and compares cost per first purchase after four weeks.


LIMITATIONS

Platforms do not disclose how similarity is calculated, and broad automated targeting often performs similarly. Seed lists need valid consent and enough matched users, and Google is turning Demand Gen lookalike segments into optimization signals during 2026, which loosens reach control.


TECHNICAL EXPLANATION

The advertiser supplies a source such as a customer list, pixel audience or page engagers, and the platform models shared traits to find similar users. Meta requires at least 100 people in the source and sets lookalike size as a ratio from 1% to 20% of a country's users, where smaller ratios mean closer similarity. Google's Demand Gen lookalike segments use narrow, balanced and broad settings of about 2.5%, 5% and 10%. Seeds come from First-Party Data, and Paid Social campaigns usually exclude existing customers.


Secondary Topics

Data Engineering

Sources

Meta for Developers — Lookalike Audiences — https://developers.facebook.com/docs/marketing-api/audiences/guides/lookalike-audiences; Google Ads Help — Use Lookalike segments to grow your audience — https://support.google.com/google-ads/answer/13541369