Share on LinkedIn
Share on XFor the past two years, IAS has been working closely with Google and the IAB Tech Lab on the development and testing of Google’s Privacy Sandbox. Much progress has been made to ensure that critical programmatic advertising use cases — particularly third-party measurement and optimization — continue to be supported in a Privacy Sandbox environment. However, outstanding items exist and continued collaboration between Google and the broader ad tech community is needed.
What is Privacy Sandbox?
Privacy Sandbox is an umbrella term for a set of proposed privacy-related updates to Google’s Chrome browser and Android operating system. According to Google:
The Privacy Sandbox initiative aims to create technologies that both protect people’s privacy online and give companies and developers tools to build thriving digital businesses.
The Privacy Sandbox has two core aims:
- Provide alternative solutions for browsing without third-party cookies.
- Reduce cross-site and cross-app tracking while helping to keep online content and services free for all.
These updates fundamentally change how ads are targeted, purchased, served, and measured for Chrome users.
IAS’s Contributions to Privacy Sandbox
IAS is an active member of the IAB Tech Lab’s Privacy Sandbox Task Force, focusing on third-party measurement and optimization use cases. Our analyses were captured in the group’s Privacy Sandbox assessment published in February 2024.
In addition to our contributions to the IAB Tech Lab’s Task Force, we are partnering directly with Google’s Privacy Sandbox team to discuss third-party measurement requirements and brainstorm solutions to ensure measurement partners have continued access to the critical signals needed to detect fraud and brand safety risks and protect buyers.
IAS’s Privacy Sandbox Testing & Findings
We started testing by setting up a local development environment where we could test and understand the flow of the Protected Audience API end-to-end. This helped us to understand how our tags were rendered, limitations in Fenced Frames, and how we might need to receive data (like top level URL) from partners in the future.
- The Protected Audience API enables on-device auctions by the browser to choose relevant ads from websites the user has previously visited.
- A Fenced Frame is a privacy-enhanced version of traditional iframes.
Fully understanding the flow of data inside the Protected Audience auction has helped us work with our DSP partners to help advise them on changes they might need to make to ensure IAS can continue to provide fraud and brand safety protection in both pre-bid and post-bid.
A challenge we identified while setting up testing with our DSP partners is ensuring that we continue to receive creative macros.
Today, we utilize data being passed to us by DSPs through creative macros at ad render time to enrich our understanding of the ad serving environment and parties involved in the ad auction. These signals are critical components for us to inform and protect our customers and they have come to rely on this useful context.
Based on the current Privacy Sandbox design, it is no longer up to the DSP to provide these macros during creative render time, but rather the SSP to replace these macros on the winning ad’s “renderUrl,” which is the endpoint used to render an ad creative.
Coordination is now needed between DSPs and SSPs to ensure the SSP provides these macros in the renderUrl they provide to DSPs. We believe a macro standard is needed to ensure this data is consistently exchanged between SSP and DSP. We are working with Google and the IAB Tech Lab to develop this macro standard.
IAS’s Commitment to Privacy
IAS is a strong advocate of consumer privacy. Our platform is cookie-less, and we have strict data retention and access policies for personal data such as IP addresses. We continue to monitor privacy-driven changes and will adapt accordingly.
Supporting Privacy Sandbox is a strategic imperative for IAS. We have been pleased with the collaboration and partnership we have with the Privacy Sandbox team. We continue to work together to ensure third-party measurement and optimization use cases are supported in a Privacy Sandbox environment.
