MiQ’s testing shows the Attribution Reporting API’s efficacy for conversion measurement
At a glance
- MiQ launched independently run Attribution Reporting API testing to gauge its effectiveness for conversion measurement use cases and develop accurate, privacy-preserving measurement capabilities.
- Testers found that the Attribution Reporting API reported 85% of the same unique converters as third-party cookies and an additional 3.7% that third-party cookies did not capture.
- As experts in the cloud space, MiQ implemented summary reports on a cloud-based trusted execution environment to maintain signals without third-party tracking. While this initiative is in the early stages of testing, it has already helped scale Attribution Reporting testing and informed new implementation processes for marketers using TEEs.
Advancing privacy-forward targeting and measurement capabilities
MiQ is a global programmatic media provider that offers full-service campaigns, analytics, and performance solutions to brands and agencies. As the advertising ecosystem enters a new era of online privacy, MiQ recognized a need for alternative systems that don’t rely on third-party cookies and began integrating the Privacy Sandbox APIs to enable accurate, privacy-forward solutions for measuring ad effectiveness.
This led the MiQ team to explore the API’s buy-side use cases—including leveraging Attribution Reporting API signals for optimization and ad relevance—alongside proprietary and partner solutions to gauge the technology’s efficacy for event-level reporting and conversion measurement.
Testing the Attribution Reporting API for event measurement
Because MiQ’s existing proprietary technology already uses privacy-conscious data—including first-party data, browser data, and privacy-centric IDs—for audience segmentation, testers were well equipped to integrate Attribution Reporting and use the Privacy Sandbox APIs to build a cross-DSP measurement solution.
MiQ’s independent Attribution Reporting analysis used data from six brands across four different markets to gauge the API's measurement capabilities. As testing progressed, the team encountered privacy limitations with event-level reports that needed to be accounted for, including data loss and increased noise. They found that they had to limit the campaign to one high-priority conversion per user to effectively reduce noise without distorting the results. After reviewing feedback from stakeholders across the ecosystem, the Privacy Sandbox team decided to release Flexible Event-Level Configurations, which allow testers to customize Attribution Reporting to meet their needs.
Data loss and device availability proved to be more complex challenges. MiQ’s testers noted that the API was only present across ~25% of ad impressions, which could be attributed to a number of factors, including policy restrictions on providing the Attribution Reporting API on iOS. They also found that cookies recorded 11% more unique converters than Attribution Reporting when running on an eligible Chrome browser. These factors informed a working hypothesis that pointed to the preconfigured seven-day reporting delay—a privacy-preserving configuration that seeks to limit the ability to re-create a user-level cross-site identifier—as the primary cause. To solve for this, MiQ reconfigured their measurement approach to optimize for the Attribution Reporting API while still achieving a high level of measurement accuracy.
“We believe Attribution Reporting API has the potential to become a pivotal source of measurement and optimization data, potentially with more scale than can be garnered using cookies. Iterating and improving upon Privacy Sandbox APIs is only possible through continued testing, which marketers can and should get involved with now, for the benefit of both their campaigns and the wider industry.”
Results and Learnings
MiQ’s testing found that the Attribution Reporting API reported 85% of the same unique converters as cookies and an additional 3.7% that cookies did not capture. Given that event-level reports capture the same data richness as legacy conversion pixels, this proved to be a highly viable dataset. While MiQ concluded that a combination of summary and event-level reports are needed to accurately model a campaign’s true ROI, they felt optimistic about the Attribution Reporting APIs’ viability for understanding ads’ impact on business outcomes and optimizing bidding models.
As experts in the cloud space, MiQ has also begun implementing summary reports using Aggregation Service on a cloud-based trusted execution environment to maintain signals without third-party tracking. This initiative is in the early stages of testing and will help inform resources for future testers.
MiQ sees Attribution Reporting as one of many powerful solutions that marketers can use in combination to deliver the best campaign outcomes. Moving forward, MiQ and the Privacy Sandbox team strongly encourage marketers and agencies to participate in testing and share their feedback.
