Lookalike Audiences use customer lists or conversion data to find Meta users with similar traits and behavior, supporting prospecting beyond existing buyers.
Lookalike sizes can range from 1%, the closest match, to 10%, the broadest reach, with a trade-off between similarity and scale. Seed quality strongly influences results: purchasers, especially high-value customers, usually provide more valuable signals than general visitors.
It helps acquisition campaigns find new prospects based on similarity to existing strong customers, identifying audiences that may be difficult to discover through manual targeting alone.
Use at least 100 eligible users in the seed and preferably 1,000 or more high-quality records, such as verified purchasers, to support stronger matching.
Traditional targeting configured directly from Meta's demographic, location, interest and behavioral options, allowing advertisers to begin without first-party customer data.
Meta's official tool for managing advertising across Facebook, Instagram, Threads, Messenger and other supported Meta inventory through a unified account.
JavaScript tracking code installed on a website to capture behaviors such as visits, cart additions and purchases, supplying data for Meta conversion optimization, retargeting and lookalike audiences.
A server-side tracking method that sends conversion data directly from an advertiser's server to Meta, reducing reliance on browser cookies and exposure to browser-level ad blocking.
Meta's AI automation framework for targeting, creative combinations, budget allocation and placements, increasingly incorporated into default campaign workflows since 2024.
An ecommerce campaign format that uses AI to automate audience selection, creative combinations and budget allocation, building on dynamic product advertising and product catalog capabilities.
Some websites are seeing sharp increases in site: operator queries in Search Console performance reports. Explore possible causes, measurement effects and diagnostic responses.
