Google Analytics Consent Mode is a new functionality for Google Analytics 4 (GA4) that provides a solution for the challenge of reporting user engagement when users have opted out of the use of cookies and processing of personal data. Although seemingly contrary to user preference, Consent Mode works by collecting anonymous visitor interaction data without the inclusion of any user identifiers, thereby reporting on site engagement while respecting and honoring visitors’ privacy preferences.
Google Consent Mode is a framework introduced by Google to help websites and apps manage user consent for tracking and analytics in a way that respects privacy regulations like General Data Protection Regulation (GDPR). It allows websites to adjust how Google tags behave based on the user’s consent status.
Google Consent Mode has two means of implementation: basic and advanced. The fundamental difference between basic and advanced Google Consent Mode occurs where users have not given their consent or have opted out of targeted advertising.
Basic – Google tags fire only where a user has granted consent (Google receives no data)
Advanced – Google tags fire regardless of if a user has granted consent (Google receives anonymized interaction data)
Google Consent Mode V2 receives additional signals so that the user’s preferences are respected throughout the Google ecosystem (frontend and backend). This, combined with anonymized data, allows Google Advanced Consent Mode to be a viable privacy-centric solution.
Benefits of Google’s Advanced Consent Mode
Although basic consent mode implementations are common, advanced consent mode implementations provide additional insight into visitor engagement. Regarding GA4, the real advantages of advanced consent mode are associated where users have not given consent or have opted out of targeted advertising:
Conversion reporting for key events
Behavioral modeling to mitigate data collection gaps (requires data thresholds)
Deterministic reporting of event interaction via anonymized data pings (requires export of data to BigQuery)
For websites with a larger user base, the advantages of Google Advanced Consent Mode are obvious as data modeling can be a powerful tool. Not all websites, however, are high-volume. So the question arises, what is the value of Google Advanced Consent Mode implementation on websites with lower traffic volume (as defined as a number insufficient for data modeling)? For these sites, the advantages of Google Advanced Consent Mode are not only associated with the reporting of conversions but also the GA4 anonymized data pings reporting events of user engagement with digital content.
Case Study – Advanced Consent Mode
To illuminate the reporting of event interaction via anonymized data pings, we conducted an analysis to evaluate data reported across three separate datasets: GA4 without modeling (device-only reporting), GA4 reporting with behavioral modeling (blended reporting), and GA4 data exported to BigQuery (BQ Native). The analysis evaluates reported interaction counts for three separate conversion metrics along with the proportions of interaction data reported from consenting vs nonconsenting users.
Consumers denying consent for the processing of their personal data and/or accessing of cookies results in a loss of visibility to behavioral actions on the site. Critical for any organization is understanding the comprehensive number of conversion events on each website. The loss of visibility due to consent makes reporting for critical events difficult in Google Analytics.
Our analysis compared data for identified event metrics across each of the tracking methods available: Google Analytics UI reporting, and BigQuery reporting from GA4 to BQ Native connection. Results were compared to determine which measurement methods best represented the behavior of consumers (regardless of consent) on the website.
The metrics evaluated were counts for the following events:
Purchase
Add_to_cart
View_item_list
Cross-Method Comparison Findings
Note – No user or session metrics are in the BigQuery dataset because without cookie identifiers these metrics are not possible to be reported upon (as can be seen in the following table).
GA4 Native and BQ Native Connection Details
These findings demonstrate the value of advanced consent mode implementations. Additional intelligence is provided in conditions where a user’s consent has not been given. Respecting user requests for privacy, BQ Native dataset contains deterministic event counts and metrics regardless of the user’s consent choice. And to repeat, all while respecting user consent via anonymized data pings.
This dataset, because of the holistic perspective of reporting regardless of user consent, is positioned as the best “source of truth” for critical event-based metrics. Metrics associated with attribution and upper-funnel analysis are best reported via the GA4 reporting interface of making use of the GA4 API.
Important to note that to achieve this additional value, an export of GA4 data to BigQuery is requisite. There are several advantages of native GA4 BigQuery connection. Convenience being one advantage, configuration of a GA4 property is basic and straightforward. Another advantage is the bot filtering provided when configuring the BigQuery data feed from a GA4 property. Google bot filtering uses a proprietary method that is not publicly available. An under-appreciated advantage of native GA4 BigQuery connection is the ability for an organization to own first-party digital analytics data. With ownership, first-party data merged from various sources allows for the surfacing of incredible intelligence.
Business Need Should Drive Data Source and Means of Reporting
The measurement stream event-based model allows different avenues for the use of GA4 data. Furthermore, the data can be made available in different contexts for reporting. Business needs should determine the approach to make use of GA4 data. For purposes of attribution and “top funnel” intelligence, the GA4 reporting UI is best suited. The integration of Google’s product provides insight into the Google ecosystem unavailable outside of Google’s confines. For purposes of raw event engagement and deeper funnel intelligence, making use of the GA4 native BigQuery data feed is best suited. Not only is all user engagement reported regardless of consent, but when the GA4 BigQuery data feed is combined with other first-party data, amazing insight can be provided. This is why directing the GA4 measurement stream via BigQuery and owning GA4 data is so important.
