Yesterday, Google released a blog post confirming it will not adopt alternative user-level identifiers once third party cookies are eliminated in 2022. Its key points included:
- The proliferation of individual user data has eroded trust, and digital advertising must evolve. Google says its approach aims to protect user anonymity.
- Performance is not at odds with privacy. Technologies like automation and machine learning, new tagging and analytics approaches, and new measurement technology – such as the Privacy Sandbox – will provide value and performance for data-driven advertisers.
- First-party relationships are vital. Google will continue to support use of first-party data within its ad platforms and will strengthen its tools supporting the relationship between consumers, brands and publishers.
So what will this mean for advertisers?
To future-proof campaigns, now is the time to prepare for and experiment with alternatives to third party cookies. In December, Kepler hosted a webinar on Navigating the Shifting Data Landscape to provide an overview on coming changes and how brands can begin to adapt. This included preparedness in four key categories:
- Identification. Without third-party cookies to provide holistic cross-site identification, brands must consider whether they have the appropriate tools and processes to manage and segment consented first-party data they collect.
- Utilization. Acting on this first-party data requires matching owned audience data with consented first-party data on the publisher side. This will require user management and segmentation tools (such as CDPs (Customer Data Platforms) or server side tagging platforms) and identification tools (such as Customer Match Conversions APIs and data onboarding partners). This likely requires development time and additional resources.
- Activation. Brands should review their reliance on third-party cookie-based identification and use of third-party data to assess likely impact of coming changes. Begin testing and comparing the performance of new targeting alternatives such as contextual targeting, cohort-based audiences, and publisher-curated audiences.
- Attribution. These changes will impact how performance is measured. Brands should evaluate their measurement approach, including reliance on “a single source of truth,” log files, and view-based attribution. Research on modeling, machine learning, Data Clean Rooms, and holdout testing not reliant on cookies will aid in evaluating media impact and measurement.