ADMaP

ADMaP (Attribution Data Matching Protocol) is an IAB Tech Lab standard for joining conversions with ad exposures inside data clean rooms to produce aggregated attribution reports without sharing user-level personal data.

The specification itself writes the name as ADMAP. Its use case is narrow on purpose: an advertiser wants to measure and compare its campaigns across publishers, ad networks, channels and platforms (IAB Tech Lab, ADMAP specification). The protocol has two parts. A mapping component gives both sides common match keys for their first-party data. An attribution component matches conversions to exposures and then aggregates the results.

Only aggregates leave the system, and the mapping key never appears in them. The specification names privacy tools for the output, including noise and thresholds that stop a report from revealing any single person. Because the inputs, outputs and interfaces are standard, an advertiser can run the same measurement with publishers that use different clean room providers. The file was first published on GitHub on 26 February 2026 and updated on 26 March 2026.

Example: A direct-to-consumer brand and a CTV publisher run ADMaP daily. The publisher's clean room supplies exposures, and the brand's supplies orders. The output lists conversions by campaign and day, and any cell with too few people is suppressed.

Related terms: PAIR, clean room, MTA, differential privacy, k-anonymity, attribution window.

Authoritative source: IAB Tech Lab, "ADMAP: Attribution Data Matching Protocol" (GitHub, updated 26 March 2026).

Read the full guide: Clean room architectures compared.