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Data & identity · also called Clean room, DCR

Data clean room

A data clean room is a secure environment where companies combine and analyse their customer data together, getting aggregated insights or audiences without exposing each other's raw personal data.

The short answer, from the AdTech Sumo glossary

Brands, retailers, publishers and platforms each hold valuable customer data, but sharing raw lists is risky and often unlawful. A clean room lets them match and analyse data together under strict rules: only approved queries run, outputs are aggregated above minimum thresholds, and no party can see the other's individual records.

Common uses include measuring whether people exposed to a campaign bought a product, finding audience overlaps for targeting, planning reach across publishers, and powering retail media and closed-loop measurement. Walled gardens offer their own clean rooms, such as Google Ads Data Hub and Amazon Marketing Cloud, and neutral providers built on cloud data platforms serve many parties. IAB Tech Lab has published interoperability standards so clean rooms can work together.

Clean rooms are privacy-enhancing, not a legal exemption. The data inside is still personal, so consent and lawful basis under laws like GDPR and DPDP still matter, and weak query controls can leak information. Matching usually relies on hashed emails or IDs like RampID.

Think of it like this

A clean room is like two chefs each bringing secret ingredients to a sealed kitchen where only the finished dish, not the recipes, comes out.

An example

A cereal brand and a UK supermarket match data in a clean room and learn that households exposed to the brand's video ads bought 9% more cereal than similar unexposed households, without either side seeing the other's customer list.

Related terms

Sources: IAB Tech Lab Open Private Join & Activation (clean rooms), GDPR Article 5: principles