One of the most underused features in online advertising is also one of the most powerful: asking the platform to find people similar to your current best customers, instead of manually defining yourself who should see your ads.
What a lookalike audience actually is
Starting from a list of people (your current customers, those who visited your site, those who engaged with your social media) the platform (Meta, Google) analyses common patterns among them and looks for other people with similar behaviours and characteristics, even if they've never heard of your brand.
Why it usually works better than manual targeting
Manually defining an audience (age, location, stated interests) relies on assumptions about who should buy your product. A lookalike audience relies on real behavioural data from people who've already bought, which tends to capture patterns you wouldn't have thought to define manually yourself.
The quality of the source audience matters more than its size
A lookalike audience built from your highest-spending customers usually performs better than one based on any website visitor, even if the starting list is much smaller. The platform needs a minimum amount of data to find the pattern, but more quantity doesn't always mean better quality.
How to start if you've never tried it
The simplest starting point is usually a lookalike audience based on customers who've already bought, not any website visitor. From there, you can test more specific lists (customers who've bought more than once, for example) as you accumulate enough data.
Frequently asked questions
What's the minimum number of customers I need to build a reliable lookalike audience?
A minimum of a few hundred people in the source list is usually recommended, though platforms allow smaller lists; with less data, the pattern found is less precise.
Does a lookalike audience completely replace manual targeting?
Not necessarily; many campaigns combine both, using manual targeting to set basic boundaries (country, language) and the lookalike audience to refine within that framework.
Can this technique be used without any prior sales?
It's harder, but you can start from alternative lists: website visitors with a certain time on site, or social media followers, though the result tends to be less precise than starting from real customers.