How GA4 improves with other Google products

You’re a smart digital marketer. Which means you already have your Google Analytics 4 account up and running already, right? Of course! 

One of the first actions that you likely took was to connect it to your Google Ads account, allowing you to start measuring the impact of your advertising on website traffic. That initial connection is simply scratching the surface of GA4’s potential power when paired with other products in Google’s portfolio of tools. 

As part of our ongoing series with Romina Henritzi of Bluebird Media, we wanted to get her take on how you can make the most of GA4 within the broader Google ecosystem. 

Google Ads

For any stragglers that are still out there, it’s hugely important and impactful to connect your Google Ads data to GA4. First of all, it gives you the opportunity to join the conversion events on your website to your marketing platform. This will allow you to start mapping attribution of conversion to your different ad campaigns and ad groups. 

Just like in Universal Analytics, you’ll also have access to specific reporting functionality. Meanwhile, in the advertising tab, you can quickly compare each advertising channel at a glance. Plus, by activating the search console, you’ll discover a new report collection within your library. 

You’ll also find a new set of dimensions and metrics for your Explores. 

“[It’s] all pretty neat, but nothing fancy or new,” said Romina. “Personally, I do hope that Google will add some more advanced and detailed reporting features.”

This is why connecting Google Ads to GA4 is merely a first step to unlocking the full power of the analytics tool. 

Related reading: 9 effective Google ads optimization tips

Connecting BigQuery

You want fancy and powerful? We’ve got something for you. 

According to Romina, the really impressive change is GA4’s BigQuery connector. First, it’s now available to free GA users. However, even paying Google 360 users can see some new benefits thanks to the GA4’s new data model. 

As a data warehouse, BigQuery can be used to store massive amounts of data (we’re talking petabytes). Data within the warehouse can be cleaned and transformed by writing and applying SQL code. 

Flexible yet powerful

Plus, like most Google products, it can be pretty flexible to your needs. Even if your data source doesn’t have a pre-existing connector to BigQuery, it’s easy for a developer to create one. For those that prefer not to code, you can also use Funnel to facilitate the connection, combination, and cleaning of data. 

Thanks to its ability to handle massive amounts of data, BigQuery can also provide machine learning capabilities. This is particularly useful for GA4 users if you’d like to achieve some improved predictive metrics that are more closely catered to your specific business needs rather than the tools embedded in GA4. With BigQuery, you (with the help of an SQL developer) can create your own. 

Power comes at a cost

While the BigQuery pricing structure can become quite complex, it essentially comes down to the volume of data that you are storing as well as the amount of times you are accessing it. This means that, if your APIs are constantly calling on 4 terabytes of data, you’re likely going to need some serious budget allotted to your BigQuery account. 

More Google, more power

Setting aside Google Ads and BigQuery connections, there are some unique things that start to happen within GA4 when you start connecting it to more Google products. 

GA4 Audiences

That’s right, the audiences are back. While you may be familiar with the concept from working with Google Ads in the past, GA4 audiences push things to a whole new level. By employing machine learning, these audiences can help track activity across devices and even predict future engagement. 

When you start connecting this feature to other Google products you already use, you’re giving GA4 access to more data that is also more applicable. Plus, with GA4, you can inform the audiences with information like refunds, user demographics, and much more. And with any machine learning tool, the higher quality and greater volume of data you can provide, the better the final output is. 

These improved audiences can also be shared back to the individual tools, allowing you to achieve greater performance. This also improves your ability to track users across devices. 

Why are advanced audiences useful?

It’s a good question actually. After all, we hear all the time about how Google’s algorithms are hyper advanced. They can almost define and target the ideal audience themselves, right? You may wonder how your own advanced audience can compete. 

While they are very advanced, new laws and shifts in data privacy may constrain these powerful algorithms. The GA4 audiences can help supplement the algorithms. 

Let’s imagine we are a hiking apparel company that uses the classic SEE-THINK-DO-CARE model for customer acquisition and retention. While you may be great at attracting and converting customers (SEE, THINK, and DO), you may find it difficult to retain those customers over time (i.e. the CARE phase). 

Let’s also imagine that you have a new range of premium cutter shell jackets coming out soon. You can use GA4 to create an audience with customers that have been purchasing other premium products and have also been browsing online for hiking gear recently. 

With a little machine learning magic and information from your CRM, you can target users who are likely to churn (those customers who drop off at the CARE phase). You can further refine this audience into male and female, then target them with specific models. 

Audience triggers

You also have a new feature for audiences in GA4 called audience triggers. This is an event that is, well, “triggered” when a user has been sorted into one of your existing audiences. Almost like a digital sorting hat that lets your further target users. According to Romina, audience triggers can be particularly useful for websites without e-commerce functionality. 

Don’t forget about testing!

If you have the volume of data required to implement machine learning effectively, that also means you have enough data to test your audiences. As we always say: test, test, and test some more. 

Your GA4 audiences can be tested via experiments in Google Ads or DV 360, allowing you to further hone and refine them for greater effectiveness. You can also compare two specific audiences by running them on a single campaign. 

“But wait,” you say. “My audience is fine just as it is.”

Great! That means you can test different messages targeting the audience. 

Make time to explore

The important thing to remember is that GA4 becomes more valuable and powerful as you feed it more data. You can quickly ramp up that effort by quickly connecting it to the other Google products you already use. Plus, the two-way improvements mean that your Google ecosystem becomes more accurate and more efficient. 

It’s also beneficial to let engineers and data analysts into a connected BigQuery account and explore all of the raw data. Here, they can help you create more accurate predictions and patterns to better serve your marketing efforts. 

Just remember to start small with those delicious low-hanging fruit and work your way up.