Changes to Google’s Tracking Metrics

For search engine marketers like Scribendi Digital Marketing, Google’s ability to track individual users and share that information with us has been extremely helpful. With this information we are able to hyper-tailor messaging and track ROI down to the penny. But changes are on the way that could roll back some of that tracking ability.

“Why it’s such a big change. Advertisers are used to targeting via third-party cookies, which enable them to reach specific individuals. With FLoC*, individuals are put into a cohort based on their interests, adding a layer of anonymity that may help increase user privacy.

Another distinction is that the assigning of cohorts is all done within the browser, which means users’ information is kept locally. With third-party cookies, a third party may be storing user data on one of their own servers.” Source

This is an on-going roll out that we at Scribendi will be monitoring closely. As of yet, there is no clearly defined changes to Google Analytics or Google Search Console reports. We don’t see it as a big issue, as putting individuals into “cohorts,” as Google calls them, by interests and habits is still better tracking than we ever had with any other medium of advertising. The companies that will be truly effected by these changes are the ones spending billions of dollars on digital advertising a year (your Nike’s.)

We’ll keep you updated as Google reveals more and we’ll make sure we are tailoring our PPC advertising campaigns and analytics reports to ensure that we are monitoring ROI properly for the size of businesses with which we work. As always, with Google, the changes will start with the top spenders and over time trickle down to effect smaller and medium sized businesses.

If you have any questions or want to learn more about how analytical tracking can help you improve your digital marketing, give us a call at (339) 244-4222 or fill out our contact form.

* Federated Learning of Cohorts (FLoC) is a method for browsers to enable interest-based advertising. It works by gathering data about a user’s browsing habits and then clustering groups of users with similar interests into cohorts. The algorithm used to develop those cohorts may look at the URLs of sites that the user visited and the content of those pages, among other factors, according to the FLoC proposal on GitHub. Information about the cohort is then shared for advertising purposes. Source.