The term “game-changer” gets thrown around quite easily, often to an underwhelming effect. However, every once in a while, a tool or technology appears on the market that really deserves the title. Such is the case with our today’s subject, Google Analytics 4.

Not only does it introduce a set of radical updates compared to the previous version, but it also anticipates a revision of how digital marketing will be conducted in the future. 

On top of that, it holds a prospect of significant monetary savings, as it offers a free (or near-free) alternative to some of the functionality previously only found in the costly Google Analytics 360, a good example of this being the out-of-the-box integration with Google BigQuery.

About Google Analytics 4

Google Analytics 4, formerly known as App + Web Property, has been introduced in stages since November 2019, and from October 2020 it is made the default when a new Google Analytics property is created.

GA4 is a drastic departure from the previous version (Universal Analytics), with some of the key new features including:

• No volume limits for data collection
• Increased sampling thresholds (and no sampling in default reports)
• Seamless integration with BigQuery (previously only in GA360)
• Advanced Analysis capability, including custom funnels (previously only in GA360)
• Cross-platform user identification with scalable cross-platform analytics based around events
• Focus on maintaining the privacy and minimizing the need to set cookies
• Increased Granular Data Control
• Natural language processing (NLP) and machine learning (ML) functions available to all Google Analytics users
• And more.

About Google BigQuery integration

With Google actively rolling out the updates, we haven’t even seen the final list of improvements yet. However, one of the more notable among the known new features is the out-of-the-box ability to integrate with Google BigQuery – previously only available to Google Analytics 360 (enterprise version) users. 

Google BigQuery is a fully managed data warehouse run by Google. It is powerful enough to analyze terabytes of data in seconds, running simple SQL queries to find insights in your data. It encrypts, replicates, and deploys data across multiple data centers enabling maximum durability and service uptime. Furthermore, it integrates with other Google Cloud Platform products offering great flexibility and vast collaboration opportunities.

The GA4 + BigQuery integration opens up new territory for Google Analytics users. Here are some of the new features it enables:

• Getting raw event data directly into a data warehouse, enabling unsampled data analysis, predictive analytics, machine learning models, and near-endless customization 
• A new streaming export taking seconds, as opposed to the current export for Google Analytics 360 that is updated every 10-15 minutes 
• An option to choose where you want to store your data in order to comply with your data governance policies 
• The export also works with the dedicated BigQuery sandbox, allowing you to get started for free.

All in all, the integration offers a powerful feature set available at a very affordable price point. With this in mind, it has every chance to become the actual game-changer, making us take a fresh look at the ways we approach and conduct web analytics.

Main feature and cost comparison

We already see that in certain areas the GA4 + BigQuery combination gets close, or even exceeds the GA360 levels of performance, for only a fraction of a price. A natural reaction to this is digital marketers and online businesses discarding the costly GA360 in favor of the more affordable option. 

Not only will this result in massive savings, but will most likely reshape the competitive landscape for eCommerce and the related industries.

Understandably, this will not sit well with everybody. Many businesses that have invested in GA360 may feel that they’re losing their advantage. At the same time, not all marketers may be happy with the need to suddenly revise their workflows and business models. Yet, in all fairness, GA360 is still a powerful tool that won’t be replaced so easily or so soon. Besides, for those willing to switch to the new property, migration is a viable and a fairly straightforward option (more on this below).

Saving 135K EUR annually with GA4+BigQuery

Note: The data in this section is based on an estimate for a real-world property migration project. The goal here is not to provide an exhaustive analysis, but to exemplify the potential impact of the new feature.

Assume a website that receives ~15M hits per month (~30GB of data). A comparative estimate may be approximated as follows:

• GA360 (yearly): 135,000 EUR 
• GA4 with BigQuery (monthly): 2 EUR.

GA4 + BigQuery cost breakdown

GA4 is free, and Google BigQuery adopts a pay-as-you-go model. Thus, the overall monthly cost is composed of the following:

• Recording 30GB of data: 15M hits ($0.01 per hit) * 2Kb/hit =  ~1.5 EUR 
• Data storage: $0.02 / 1GB = ~0.6 EUR
• Queries & Processing: 4.5 EUR per 1TB (will vary depending on how extensively you intend to query)
• Additionally, there is a free monthly quota: 10GB of storage, 1TB for ML queries 

Total: 2 EUR per month + additional costs for querying. 

More precise costs can be calculated when the requirements for BigQuery reporting are set, but you get the idea.

Property migration

As mentioned above, starting from October 2020, GA4 is promoted as a default choice when creating a new Google Analytics property. This also standardizes its integration with Google BigQuery.

Adopting the functionality for your existing Google Analytics plan is more elaborate, but certainly can be done. The process of migration from either GA(UA) or GA360 is quite similar, although, in the case of GA360, it is important to note that access to some other paid features will be restricted after the switch to GA4 is done. Thus, we suggest that both the migration and the necessary workarounds are planned in advance.

Note: GA4 still being in its early stages, the following precaution measures are advised:

•  Avoid immediately shutting down the existing GA accounts after switching to GA4,
• Since a number of GA4 components are still in beta, both setups (i.e., GA3 and GA4) should be allowed to run in parallel to enable reliable data cross-referencing.

Our proposed migration roadmap, in simple terms, follows these basic steps:

• Conduct thorough website and property analysis, and develop detailed migration requirements
• Set up and configure GA4 property
• Configure BigQuery project and automatic data import from GA
• Enhanced GTM setup & QA
• Launch tracking & start collecting data.

Voila!

Once again, specific steps may vary depending on the scope and specific business needs. If you need help migrating your project to Google Analytics 4 + Google BigQuery, you can always hit us up for more details and/or migration assistance!

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