Background

Ad-tech providers have historically used third-party cookies for conversion measurement, and for attributing conversions to ad interactions. Conversion measurement is critical for evaluating the performance of ad campaigns and automated bidding strategies. Now, with technology changes and privacy regulations on the rise, traditional ad-measurement systems must change in order to remain effective while protecting user privacy.

Chrome’s Attribution Reporting API (ARA), part of the Privacy Sandbox initiative, offers a new path to conversion measurement after Chrome’s planned third-party cookie deprecation in the second half of 2024, subject to addressing any remaining competition concerns of the UK’s Competition and Markets Authority (CMA). Google’s ads teams have made significant investments in learning to use the ARA more effectively, to help advertisers achieve more accurate measurement.

In a previous post, we provided a high-level overview of the approach Google’s ads teams are taking to effectively blend the ARA event-level and aggregate summary reports to maximize accuracy. A key point is that your configuration determines what data you query, and how you query it. It’s crucial for ad-tech providers to effectively configure the ARA for their use cases. Google’s ads teams have found that configuring specific ARA settings can lead to notable accuracy improvements. We encourage other ad-tech providers to integrate with the ARA to retrieve the conversion data they need, and process the ARA's output to help maintain accurate measurement in a post-third-party-cookie world.

The ARA is flexible to support various use cases. Google’s ads teams use this flexibility to configure unique ARA settings for each advertiser. This way, ARA-based measurement adapts to each advertiser’s specific needs. For example, we’ve noticed that when advertisers differ in conversion volume, it’s better to have advertiser-specific configurations related to the granularity of aggregation keys and the maximum observable conversions per ad interaction.

Google’s ads teams’ approach

Here's how Google's ads teams use the ARA to ensure the raw data we receive is as useful as possible for downstream blending. We configure ARA settings as explicit mathematical optimizations by defining objective functions to represent data quality, then choosing settings to optimize those functions. Ad-tech providers can choose their own approach. Google’s ads teams plan to continue sharing insights we learn from our own optimizations with the ad-tech community.

Please see our detailed technical explainer for more information about our approach to ARA configuration.

- Harikesh Nair, Senior Director, Data Science, Ads Measurement

Overview

Historically, ad-tech providers have used third-party cookies (3PC) as a mechanism for conversion measurement, and for attributing conversions to ad interactions. Conversion measurement provides critical ad performance data to advertisers, and helps optimize auction-based bidding strategies.

Currently, the online advertising ecosystem is pivoting towards improved ways to protect user privacy. Chrome’s Attribution Reporting API (ARA), a part of the larger Privacy Sandbox initiative, offers an alternative for measurement after the third-party cookie deprecation in 2024. Ad-tech providers, including Google’s ads platforms, should consider adopting the ARA to maintain high-quality conversion measurement and support the pivot toward user privacy protection.

Google Ads has made significant investments to use the ARA more effectively and to help advertisers achieve more accurate measurement. We encourage other ad-tech providers to integrate with the ARA, configure the integration to retrieve the data they need, and process the ARA's output to help maintain accurate measurement after the planned third-party cookie deprecation in 2024.

Goals of the ARA

The ARA has two goals:

• Protect users’ cross-site and cross-app identities from ad-tech providers, advertisers, publishers and other entities by using differential privacy techniques, such as aggregation, or adding an element of noise to the data.
• Provide useful measurement information to ad-tech providers, advertisers, and publishers.

The ARA represents a change to both the format and granularity of conversion data available to ad-tech providers. As a result, ad-tech providers must change their current measurement protocols in order to start leveraging the ARA.

A glimpse into our approach

Ad-tech providers who participate in the Privacy Sandbox initiative receive data from the ARA in two forms: event-level reports and aggregate summary reports. This way, two independent views of the same underlying data are available. We encourage ad-tech providers to configure the reporting settings in the API to optimize for better measurement accuracy without 3PC, as well as improve how these two types of reports can be post-processed and used together.

There are many possible ways to utilize the ARA reports. The methodology that works for an ad-tech provider will ultimately depend on its conversion data and measurement requirements. Google Ads has found that leveraging both report types can help the industry benefit from the strengths of each report.

Google Ads leverages both event types to produce a more complete, ad event-level log. We are committed to sharing our process and engaging with the ecosystem to help our partners and the broader industry transition into a future without third-party cookies.

For more details on how we’re implementing the Attribution Reporting API, please refer to our detailed technical guide.

Harikesh Nair, Director, Data Science, Ads Measurement