Analytics

6 Google Analytics 4 updates that impact the efficiency of Performance campaigns

· May 8, 2023

On July 1st, all websites that used Universal Analytics must transition to Google Analytics 4. We analyzed with our Performance and Data & Analytics teams the main updates that GA4 brings and their impact on setting up and optimizing PPC campaigns. In a nutshell:

Detailed analysis of user behavior - engagement, conversion, retention ---> creation of ads/targeting of specific keywords/optimized bidding strategies
Improved attribution model ---> better bidding strategies and budget allocation
Machine-learning capabilities ---> forecasting, prediction, planning, strategic thinking, anticipating trends
Tracking on mobile + desktop ---> better estimation of audience and users, insights into user behavior and decisions

1.Cross-device tracking ---> a much clearer picture of user behavior, leading to better algorithm delivery optimization How can this be translated into campaigns? GA4's ability to track user interactions with the brand across multiple devices means a much clearer picture of user behavior, which will impact campaign frequency and help optimize the delivery algorithm. Until now: Universal Analytics had limited capabilities in identifying cross-platform users, resulting in cases where Google Ads campaigns that used audiences from Universal Analytics would end up targeting the same user multiple times. 2.App + web reporting / all data in one place - conclusions, analysis, overview - How can this be translated into campaigns? Unified access to data allows for a more accurate overview and more relevant analysis for the business. Until now: One business, but multiple data collection tools, hard to track and correlate. Now, the data is in the same place. 3.User vs. sessions / now we can better understand the behavior of the audience, as the focus is on the user, not the session How can this be translated into campaigns? The fact that the focus is on the user greatly increases data quality and accuracy in seeing results. Until now: It was difficult to track the number of users who completed transactions because everything was reported on the number of sessions. 4.Data-driven attribution model / compared to the classic model, the data-driven model attributes conversions based on account data (time to conversion, device type, ad interactions, exposure order), which provides more accuracy and a clearer picture of the results. How can this be translated into campaigns? We can see much more clearly which marketing strategy works based on the channels with which a user interacts and thus optimize the settings and budgets invested. Until now: UA used Last Non-Direct Click as the default attribution model, meaning that all channels with which the user interacted before conversion did not receive a value assigned for the contribution they had in completing the conversion. 5.Predictive audiences / GA4 comes with the option of predicting audiences that fit the business based on certain parameters such as lifetime value, recurrence, and frequency of purchases, preference for certain brands. How can this be translated into campaigns? This new feature leads to much more efficient targeting in the prospecting area, discovering new potential customers who can be targeted through campaigns. Until now: audiences were much more general, not built from such detailed and qualitative parameters 6.Audience trigger / GA4 allows the identification of valuable users for the business (engaged users) who can be automatically added to an audience by defining the events they perform on the website. How can this be translated into campaigns? In campaigns, this audience is measured as conversion, making it much easier to understand the volume of users inclined to make a transaction. Until now: Universal Analytics measured audiences in a limited way, and users could be kept in an audience for a much shorter period of time than GA4 allows. If you need help in managing the Google Analytics 4 migration, drop us a line> hello@datarevolt.agency