Cookie Death Brings New Lift to Measurement

Google’s long-anticipated elimination of cookies, used to track online activity and guide more precise digital ad placement, is finally starting to become reality. The company recently began tests to eliminate cookies for a segment of Chrome browser users. If the schedule holds, Chrome will be cookie-less by the end of Q3’24.

How will the Ad and PR industry offset the loss of data-rich cookies? The first move is to remember that as good as cookies are, they have never been perfect. Like a genie, they give you what you say you want but often do so without giving you what you actually want. If you want impressions, for example, you get them, but you may not be aware that you’re getting them from kids on parent accounts or TVs left on, but unattended. Likewise, if your campaign is promising sales, cookies are just as likely to deliver ads to people already on their way to buy your product.

Our team has a new way forward, and the demise of cookies has actually made it possible. Today, we are using Bayesian impact analysis to determine not only what has happened with a planned marketing campaign, but what would have happened in its absence. This kind of experiment-based observation measures the difference of differences in large data sets, allowing us to see things that cookie tracking glosses over. By perfecting this approach, we are now even able to correlate PR launches to product sales lift. The loss of cookies made this possible because clients, knowing cookies were going away, were finally able to let go of their fixation with device identifiers.

Along with new algorithms, we are also emphasizing to clients, the importance of CRM utilization and prioritizing first-party data collection. We are deprioritizing interest and in-market targeting in favor of contextual keyword targeting as cookies become less relevant. Imagine, for example, reading an article about the benefits of a particular appliance. Up pops an ad in that context offering a rebate, not simply providing an additional and unnecessary awareness nudge. That’s a better way to move customers through their purchase journey. Our belief is that measurement teams will benefit by analyzing content consumption to understand context. Articles and transcripts from video and audio, for example, can serve as context maps. Recent privacy updates by Apple make this even more true. As more users opt out of tracking, post impression and post click conversions will be lost.

We are entering a new age of lift measurement – first-party context-based data combined with statistical modeling and A.I.-enabled analytics. CMOs and CCOs who have been chained to device trackers can now feel free to experiment with more creative approaches to measurement. Robust statistical models paired with data willingly and transparently given by consumers, provide the signals necessary for conversion reporting and better downstream actions like bidding, optimization, and attribution. It’s not a loss at all. It’s an overdue win for privacy and it’s time to move to what’s next.