Lookalike audience
Also: Similar audience, LAL, Lookalike modeling, Audience similaire, Audience de jumeaux
An audience created by ad platforms to target new prospects who resemble your best existing customers, based on shared traits and behaviors.
What it is
A lookalike audience (also called a similar audience) is a targeting segment built by an advertising platform. You provide a source audience (a "seed") of people you already value, for example past purchasers or high lifetime value customers. The platform then analyzes the shared traits of that seed and finds new users in its network who statistically resemble them.
The key idea: you are not choosing targeting rules by hand (age, city, interests). Instead, the platform infers the pattern from your seed and expands it to strangers who look similar.
Why it matters
- Prospecting at scale: it moves you beyond retargeting (people who already know you) into finding net new prospects.
- Efficiency: a good seed usually beats broad demographic targeting on cost per acquisition.
- Quality control: the better your seed, the better the lookalike. Feeding "all buyers" produces a weaker result than feeding "top 10 percent by revenue."
How it is used in practice
1. Build the seed from a customer list (emails, phone numbers, hashed identifiers) or from platform events (purchases, sign ups).
2. Upload or select the seed inside the ad platform.
3. Choose the expansion size, often as a percentage of the target country's population. A 1 percent lookalike is tighter and more similar; a 5 to 10 percent lookalike is broader and less precise.
4. Launch campaigns against the resulting audience and measure incremental conversions.
Common pitfalls:
- Seeds that are too small (aim for at least a few thousand quality records).
- Stale seeds that no longer reflect current best customers.
- Privacy and consent gaps when uploading personal data.
Concrete worked example
A subscription software company exports its top 5,000 customers by annual contract value. It hashes their emails and uploads them as a seed. The platform builds a 1 percent lookalike in the target market, roughly 250,000 people.
- Before: broad interest targeting delivered a cost per trial of 40 dollars.
- After: the 1 percent lookalike delivered a cost per trial of 24 dollars with higher trial to paid conversion.
The team then tests a 2 percent version to grow reach once the 1 percent audience saturates, accepting a slightly higher cost for more volume.