Definition
Lookalike builds from a seed list. The list can be customer emails, website visitors, app users, or converted users exported from CRM.
How it works
The platform extracts the behavioral fingerprint of seed users: interests, demographics, behavior patterns, purchase signals. The algorithm searches other platform users for the most similar profiles. A similarity percentage is chosen (1-10% on Meta): a lower percentage means tighter similarity and a smaller pool. The ad publishes to the pool. Seed list quality and size directly impact lookalike performance.
Where you see it in Scope Trends
The Audience Management tab holds lookalike source lists and performance comparison. The Meta Ad Command Center suggests lookalike seeds.
Frequently asked questions
How large should the lookalike seed list be?
Meta requires a minimum of 100 users; 1,000-50,000 is ideal. Very small seeds yield weak models.
Did iOS 14.5 hurt lookalike quality?
Yes, the conversion signal contraction impacted quality. Modeled conversion partially recovered it.