Lookalike audiences (LAL) are how B2B advertisers reach niche audiences on consumer-focused platforms like Meta. The advertiser uploads a seed list (typically existing customers or qualified leads), and the platform builds a model of what those people share, then targets users with similar profiles.
How LAL sizing works on Meta
- 1% LAL — finds the 1% of users in the target country most similar to the seed. Most precise, smallest audience (~2-3M in US)
- 3% LAL — broader, less precise. ~7-10M in US
- 5-10% LAL — much broader; useful for prospecting at scale
Why LAL matters for mortgage
Native job-title targeting on Meta for ‘Mortgage Loan Officer’ is weak (Meta restricted B2B targeting in 2022-2023). Native interest targeting is too broad. The strongest signal is a custom audience uploaded as a seed (e.g., existing BNTouch customers, NMLS-registered MLOs), then expanded via 1% LAL. The platform’s algorithm finds people similar to actual MLOs without needing them to declare it on their profile.
LAL minimum requirements
Meta requires at least 100 matched users in the seed audience to build a LAL. Match rate on B2B emails (business addresses) is typically 15-30%; on personal emails it’s 50-70%. So a 1,000-record seed list typically produces 150-700 matched users, easily clearing the 100-user minimum.