Definition
A lookalike audience is a targeting segment an ad platform builds by finding users who resemble a source audience the advertiser provides — typically its existing customers, its highest-value players, its recent converters, or its email list. The platform analyses the shared characteristics of the source group and assembles a much larger audience of users who match that profile but are not yet customers, for prospecting.
Lookalike quality depends heavily on the source. A lookalike built from all registrations includes the profile of low-value and one-time users; a lookalike built from the top decile of players by lifetime value points the platform at people who resemble whales.
The tighter and more valuable the seed, the better the lookalike, though a very small seed can be too narrow to expand well, so there is a practical minimum size.
In context
For iGaming operators, value-based lookalikes are a standard prospecting tool in markets where the platform permits gambling ads. Seeding a lookalike with high-LTV depositors, or with players who retained past 90 days, directs the platform's optimisation toward similar prospects, and combining that with a qualified-FTD conversion signal lets the algorithm compound the targeting with the outcome data.
The privacy changes that weakened behavioural targeting also constrain lookalikes somewhat, since the source data and the matching both depend on identifiers, but value-based seeds remain effective on the platforms and markets where they are allowed.
For affiliates, lookalikes are usually limited to their own first-party data. A media-buying affiliate can build a lookalike from users who registered through its funnels, but it cannot seed one with the operator's player data, so its lookalikes are less powerful than the operator's. Audience overlap is a related concern — running lookalikes, interest targeting and retargeting for the same brand at once means those audiences share users and bid against each other — so buyers check overlap reports and merge or exclude accordingly.
Worked example
An operator replaces an all-registrations lookalike seed with the top 10% of players by 90-day value. The new lookalike's prospecting cohort has a 30% higher deposit-to-registration ratio and materially better retention, so cost per qualified FTD falls even though cost per click is slightly higher.
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