Lookalike Audience

Lookalike audiences leverage platform data to scale successful acquisition by finding prospects who resemble your best customers. Rather than relying solely on demographic or interest targeting, lookalike modeling identifies behavioral and characteristic patterns shared by valuable customers, then finds similar users likely to respond positively.

Creating lookalikes requires a source audience—typically your customer email list, website visitors who completed valuable actions, or high-lifetime-value clients. Platforms like Facebook, LinkedIn, and Google analyze hundreds of data points about source audience members, then identify users sharing similar patterns. Lookalike size balances specificity (smaller percentages more closely match source) against reach (larger percentages cast wider nets).

For example, a wealth management firm might create Facebook lookalikes based on a customer list of high-net-worth clients, reaching similar affluent professionals who don't know the firm yet. A digital bank could create lookalikes from website visitors who completed account applications, finding prospects likely to have similar needs. A financial advisor might upload a list of ideal clients to LinkedIn, creating lookalikes for prospecting outreach targeting similar professionals.

Lookalike effectiveness depends on source audience quality—larger source lists (generally 1,000+ for Facebook) and lists of your best customers (not just any customers) produce better results. Testing different source audiences reveals which customer segments provide the best lookalike performance. Regular refreshing of source lists ensures lookalikes reflect current customer patterns as business evolves.