IAB Data Clean Rooms in Commerce 2026

On September 30, 2026 Research & Resources

Data Clean Rooms in Commerce is a practical framework to help retailers, brands, agencies, publishers and technology partners decide when a data clean room is the right tool for the job. Rather than asking “What is a data clean room?”, it starts with the business question and works back to whether a clean room is needed to answer it.

As clean room adoption has grown, so has confusion about when they are necessary, how they differ from existing analytics and reporting tools, and which use cases justify the investment in time, cost and technical resources. The framework separates the use cases a clean room makes possible from those where it strengthens workflows that already exist.

A global collaboration

The framework was developed by IAB US with partners across the IAB Global Network. Contributors from five markets shaped the guidance, giving local practitioners a common reference point that reflects how clean rooms are being used internationally.

IAB US
United States
BVDW
Germany
IAB Australia
Australia
IAB Canada
Canada
IAB Europe
Europe

Five questions to ask before pursuing a data clean room

1What business question are we trying to answer? Define objectives and use cases from the outset.
2Does it require data from multiple parties? If one party’s data is enough, a clean room may not be needed.
3Does it need privacy-enhanced collaboration on sensitive data? Identity resolution, onboarding or APIs may be enough for a simple audience match or transfer. A clean room matters when governed analysis across datasets is required.
4Can existing capabilities answer it? Retailer dashboards, attribution platforms, reach and frequency tools and brand studies may already deliver the output.
5Can we operationalise the analysis? Account for platform fees, data science and technical resources, and ongoing management.

Inside the framework

Use cases enabled by clean rooms

Cross-party collaboration that typically depends on a governed environment.

Audience overlap analysis · Data enrichment · Bring your own data (BYOD) targeting · Suppression and exclusion · Retailer audience activation

Use cases enhanced by clean rooms

Work often done with existing tools, extended when data sits across organisations.

Attribution and outcome measurement · Incrementality · Reach and frequency · Customer journey analysis · Consumer and category analytics · Audience discovery · Customer segmentation · Lookalike modelling · Media mix and channel analysis

For each use case, the framework sets out what it is, when a clean room adds value, and the typical outputs. It also makes clear that a clean room is a technical and governance mechanism: it does not, by itself, establish a legal basis for processing or sharing data. Organisations remain responsible for meeting their legal, contractual and governance obligations.

IAB Australia thanks the members of the Commerce and Retail Media Council for their input into this framework and for representing the Australian market in its development.

Download the framework:

Data Clean Rooms in Commerce (PDF)

Data Clean Rooms in Commerce was published by IAB in September 2026 in collaboration with BVDW, IAB Australia, IAB Canada and IAB Europe. The framework uses the IAB Tech Lab definition of a data clean room.

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