Welcome to the Google Analytics 4 revolution

NEWS / INSIGHTS

21 January 2020
To implement GA4 successfully, companies first need to implement a dual setup with their current Universal Analytics property and upskill their digital marketing teams accordingly. Cyril Calvet, Senior Data Analyst at Artefact France, explains how.

Back in October 2020, Google officially released Google Analytics 4 (GA4), to help companies understand their customer preferences and create better experiences for them. The release ended the beta phase of Google’s App + Web property and marked a turning point in Google’s drive to accelerate the implementation of GA4 as the successor to Universal Analytics.

GA4 brings with it major structuring changes which will benefit marketers and analysts, and, as we enter 2021, they’ll be able to use this new model to better refine cross-device insights, and make better marketing decisions with increased automated activation strategies — all within a framework designed for e-privacy. 

To succeed with GA4, though, companies first need to work out how to deploy it correctly. That begins by evaluating their current levels of digital maturity.

The benefits of deploying GA4

For marketers, GA4 leverages machine learning to create audiences based on purchase or revenue predictions, generate truly engaged user audiences (as opposed to the bounce rate that’s no longer as relevant in an app and web logic), and retarget audiences to User IDs. 

Campaign attribution is also cross-platform, with the capacity to create audiences and activate them, whatever the device (mobile or web). Additionally, GA4 is a data model that can be adapted to e-privacy and legal frameworks (GDPR, CCPA) and enhanced with key predictive features to anticipate the consequences of foreseeable increases in future opt-outs.

For analysts, GA4 makes it possible to reconcile web and mobile under a single property, and under the same underlying data schema, with advanced analytics capabilities under the Hub Analysis hood. This greatly simplifies the work and analyses that can be derived from GA4 (and can also be enriched with the activation of BigQuery raw data).

When using BigQuery activation, without necessarily a GA360 license, infinite fields of analysis and use cases can be pushed in targeting and machine learning. Therefore, it is more important than ever to ensure consistent and harmonised data collection between the different domains of web and mobile.

GA4 also has the advantage of embedding automated insights with pre-embedded machine learning modules. The analytics modules go further than Universal Analytics in identifying key metrics by easily comparing multiple audience segments, analysing paths and routes taken by users or building conversion funnels.

Three levels of maturity

To deploy GA4, companies will need to give access to their web analysts and their marketing teams — not one or the other. But successful deployment depends on the organisational maturity and level of data understanding these teams have. 

There are typically three levels of users: ‘uninformed latecomers’, ‘vigilant fence-sitters’ and ‘mature, well-armed competitors’.  Their profiles — and challenges for onboarding — look like this:

1. Uninformed latecomers

‘Uniformed latecomers’ may have heard about App + Web or GA4, but they likely won’t be clued into the latest changes or the new Google Analytics 4 model. This group is most at risk of starting their deployment phase late and losing competitive edge.

To help these teams onboard to GA4 quickly, they should start by creating a GA4 property that will receive existing web feeds and applications. This will allow them to collect their data based on user interactions with the web or the app. Tracking and analyst teams will then be able to use the tool to anticipate the technical impact that deploying GA4 will have on their web and application developments.

2. Vigilant fence-sitters

‘Fence-sitters’ will likely have begun anticipating the arrival of GA4 with their web analytics teams and most will have already activated a web feed to GA4. They might also have carried out the dual setup recommended by Google. But while they may have evangelised on the subject, GA4 probably isn’t a priority in their 2021 roadmap.

Their web analytics teams will likely only ensure “minimum service” with GA4 and will be waiting for more information (e.g. key features under GA360 license) before really accelerating or making structuring decisions.

In 2021, ‘Fence-sitters’ must accelerate their GA4 implementation, challenge their data collection strategy, verify that it’s in line with their company’s business strategy, and take maximum advantage of the features it offers. Teams can also start archiving their data by enabling data exports to a data warehouse, like BigQuery.

3. Mature, well-armed competitors

‘Well-armed competitors’ will most likely have already implemented GA4 properties with a GTM setup or via the optimised GA4 UI. These users typically follow Google’s announcements and will likely be aware of key features as they’re added in 2021. In short, they will have already made headway on the subject and are taking full advantage of the additional analytics provided by GA4 versus Universal Analytics. They’re ready to transition from Universal Analytics to GA4 seamlessly and easily.

For these players, their transition to GA4 will likely be complete when they have reviewed their data collection strategy and implemented harmonised tracking plans between app & web. Only then can they start exploring the most advanced features of GA4 (like predictive metrics, connection to the advertising ecosystem, User ID connected to app and web, exclusion of advertising audiences concerning a given parameter, etc.). 

Maturity breeds success

In the modern world, data is power, and with GA4, companies have an opportunity to harvest more than ever before. In 2021, GA4 will become an indispensable companion for companies of any size, as long as they know how to take advantage of the data it provides. 

Companies at the latter stages of deployment — likely, those that work with Data Analysts and Data Scientists — are already gaining advantages. That’s because they have the right experts to take charge of their raw data exports on BigQuery, show creativity in the insights they can be gained from them, and bring value by activating advanced marketing automation use cases (e.g. automated campaign launch for a given audience, synchronised with the generation of a given event or page view resulting from web or app user behaviour). 

To enjoy similar advantages, everyone else can do one thing to join them: accelerate deployment… now!