In a move to make browsing the Web more private, Google FLoC is steadily pushing towards discontinued support of third-party cookies and replacing them with an assortment of privacy-centric enhancements to their marketing tech stack.
New privacy-first Google features include FLoC or Federated Learning of Cohorts, Google Analytics 4 (GA4), and Consent Mode Beta, along with a Privacy Sandbox which will power Google’s web products post-third-party cookie world.
Here’s a quick update on some of these new initiatives and tracking alternatives relevant to a renewed privacy-first digital focus.
Privacy Sandbox
Google’s Privacy Sandbox is essentially an invitation for the internet marketing and technology community to join them as they define new privacy-centric approaches to measuring digital performance. Ultimately, these new technologies will support advertiser’s campaigns within Google Ads.
Marketers can tune into updates from this initiative within forums, such as W3C’s Improving Web Advertising Business Group, while developers can experiment with Chrome Origin Trials.
FLoCs
According to Google’s Privacy Sandbox Product Manager, Marshall Vale, Google FLoC or Federated Learning of Cohorts help your browser determine cohorts or groups of thousands of other people that resemble your browsing history. In this scenario, cohorts or groups of people with common interests replace individual identifiers while enabling privacy-centric targeting.
FLoCs are different from third-party cookies, which allow companies to follow you individually across various sites. FLoCs works on your device without sharing your browsing history while living within each browser. Everyone in the ads ecosystem, including Google’s advertising products, will have the same access to FLoCs.
“Cohorts are dynamic and will update every seven days during the initial trial. As a person’s browsing behavior changes, their browser will assign them to a different FLoC cohort that reflects those interests.” – Ginny Marvin, Google Ad Products Liaison
A cohort ID number is the only item relayed to any website requesting this information. Instead of a 3rd-party cookie that can tie to an individual, FLoCs pass information from your device without personal browsing history shared.
Want to block FLoCs?
If you’re already blocking third-party cookies in Chrome, you already have. If not, you can go to Chrome settings, Privacy and security, Cookies and other site data, and select “Block third-party cookies in incognito.”
Analytics
Aiming to fill the gaps left sans cookie-based data, Google introduced Google Analytics 4 in late 2020. According to Google, GA4 uses a “flexible approach to measurement, and in the future, will include modeling to fill in the gaps where the data may be incomplete. With this update, you can rely on Google Analytics to help you measure your marketing results and meet customer needs now as you navigate the recovery and as you face uncertainty in the future.”
Google Analytics 4 combines measurement across websites and apps to give marketers a 360-degree view of the customer journey and cross-channel attribution while providing richer data for machine-learning models.
You can find more predictive metrics available within Google Analytics 4 here.
Conversion Modeling: Google Ads Global Site Tag and Tag Manager
Conversion modeling refers to the use of machine learning to quantify the performance of digital marketing tactics in the absence of direct conversion data. Cross-device and online-to-offline tracking, for example, may lack the cookies necessary to link a combination of devices within a conversion path. Without modeling in place, there will be gaps within your performance data. With modeling in place, aggregated and anonymized data power algorithmic performance predictions in a privacy-centric manner.
As the void in measurement increases, digital marketers can benefit from years of automation learning unavailable until now. By continuing to feed these systems with expanded datasets, you can maximize your intelligence across platforms, devices, browsers, and operating systems.
By implementing Google Ads global site tag for conversion tracking and Google Tag Manager, digital marketers can augment data required to enable conversion modeling.
Other Tracking Levers to Consider Outside of Google Updates
First-Party Data
First-party data such as events, email subscriptions, and form submissions provided by visitors to your website enable marketers to remarket to these individuals and create look-alike audiences based upon these user lists.
Marketers can also target people who sign up to receive information on a product or service but do not ultimately convert or purchase from the site by linking their Google Ads and Analytics accounts. For first-party list uploads, Google uses Transport Layer Security (TLS), which is the industry standard to transfer files securely. Investing in strategies to maximize collection and safe usage of this data is becoming a bigger priority for digital marketers with 3rd party cookies phase-out.
Contextual
Contextual targeting considers the content people consume as a signal of their interest. For example, people reading an article about the top five things to do in Chicago will likely plan a vacation and show interest in related products (restaurants, hotels, rental cars).
Contextual targeting isn’t new but has gained importance within a privacy-centric digital future, making context and SEO an even more critical focus of your digital efforts.
Google Ads also offers custom audience targeting based on Display, Discovery, Gmail, and Video campaigns. Custom audiences enable advertisers to add contextually related keywords, URLs, and apps to dial in ad targeting.
Second-Party Data
Second-party data or another companies first-party data is also comprised of transactional or behavioral data pulled through website or app interaction. Second-party information is matched to existing customer data to enhance advertisers’ ability to optimize customer behavior, scale engagement channels, and drive acquisition.
Digital marketers commonly leverage this type of data to make campaigns more efficient through more sophisticated audiences.
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