Definition
A data clean room is a secure, privacy-controlled environment where two parties - typically an advertiser and a platform, or two companies - can match and analyse their datasets against each other without either side seeing the other's raw, individual-level data. Records are matched on hashed identifiers inside the room, only aggregated or privacy-thresholded results come out, and rules restrict what queries can be run.
It lets an advertiser measure campaign performance, audience overlap or incrementality against a platform's data while complying with privacy constraints and the platform's data-sharing limits.
Clean rooms became prominent as third-party cookies declined and platforms restricted raw data exports: they are a way to keep doing joined-up measurement and audience work on first-party data without moving personal data between parties.
In context
For iGaming operators with significant first-party data and paid media across major platforms, clean rooms are increasingly how joined-up measurement gets done: matching the operator's registration and deposit events against a platform's exposure data to estimate real campaign contribution, measuring audience overlap between channels, and running incrementality analysis, all without exporting personal data. For large operators this is a practical response to attribution loss from privacy changes.
The compliance and governance requirements are substantial. The data going into a clean room is still personal data with a lawful basis and consent scope, the matching and any resulting audiences must respect the purposes the user agreed to, and responsible-gambling suppression (self-excluded and at-risk players) must apply to anything built from the output.
A clean room reduces data-movement risk but does not remove data-protection obligations, and the queries and outputs need governance so the environment is not used to effectively reconstruct individual-level data. For affiliates, clean rooms are almost entirely an operator-and-platform concern, but the concept matters as context: it is part of how large advertisers now measure, it depends on first-party data quality, and it does not change the underlying requirement to have consent and to exclude protected players.
For affiliate-facing content, the framing is that a data clean room lets parties match and analyse datasets without sharing raw personal data, that it is a privacy-era measurement tool used mainly by large operators and platforms, and that it reduces data-movement risk but still carries full data-protection and responsible-gambling obligations.
Worked example
A large operator uses a clean room to match its consented FTD events against a platform's ad-exposure data, estimating the campaign's real contribution and audience overlap with another channel, without either side exporting individual records. Self-excluded players are excluded from anything built on the output, and the queries are governed so no individual-level data can be reconstructed.
Related terms
Frequently asked questions
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