The complexity of the modern Web user's experience has made it critical for marketers to track users across mobile and desktop environments—together.

Since 2013, when Google released the third version of Google Analytics, AKA Universal Analytics, it has provided great results for users. But its limitations have become evident, especially in the past two or three years.

Enter Google Analytics 4, the much-anticipated update within the Google Analytics product, announced in October 2020.

With the proliferation of new platforms, such as mobile apps and IoT devices, a massive influx of new data sources has been created; and as powerful as Universal Analytics was, it simply wasn't up to the task. So Google went back to the drawing board.

This article will explain the differences between Universal Analytics and Google Analytics 4, why user-centric reporting and data collection are here to stay, and how advertisers can obtain more innovative insights to improve their marketing decisions and ROI.

Universal Analytics vs. Google Analytics 4

When Universal Analytics (UA) was rolled out in 2013, mobile apps were not as prolific as they are today, so wasn't as important for UA to give marketers a 360-degree view of the customer journey—i.e., across websites as well as apps.

However, as more and more people began to use mobile devices, marketers began clamoring for a way to analyze data across platforms so they could have a more holistic picture of their target audiences and their behaviors. After all, the same person may look at a website on a phone, revisit it later on a laptop, and log in the following day on a tablet. Using UA, it was challenging to combine those datasets and look at customer lifetime value across all devices.

Google began looking for technical changes it could make to the platform to help organizations run cross-platform analytics, and the result was Google Analytics 4 (GA4).

No matter what device a person uses, GA4 can capture that data and provide a big-picture view of how that person is engaging. The product's ability to combine data should be a gamechanger, and it will undoubtedly be one of GA4's most significant selling points.

Built-In Modeling Capabilities in Google Analytics 4

GA4's improved ability to look at user data across all devices provides a much richer data set to run built-in machine-learning models. Those models can therefore help marketers better predict actions their customers may take.

In the past, if you wanted to run models on Universal Analytics data, you needed a data scientist to build the models and data engineers to put the data back in so you could work on it. A small project required a lot of technical, expensive work across multiple teams.

GA4 offers three new built-in modeling capabilities that make it possible to use your organization's resources more efficiently. The three models provide basic but essential predictive metrics:

• Purchase probability helps predict the likelihood that users who have visited your website or app in the past 28 days will purchase in the next 7 days.
• Churn probability predicts how likely it is that recently active users will not visit your website or app in the next 7 days.
• Revenue prediction predicts the revenue expected from all purchase conversions within the past 28 days from an active user in the previous 28 days.

With those models available right on the user interface, your data science team will be free to work on more complex models and solve more advanced problems.

Why User-Centric Reporting and Data Collection Is Here to Stay

Google Analytics 4 is less about creating standard reports and more about analyzing data to find answers to specific questions. Universal Analytics allowed you to layer custom data over the top of your standard report, but GA4 will enable you to focus on analyzing and exploring the data. By reporting users across devices, GA4 can paint a clearer picture of their behavior along the customer journey.

Instead pageviews or sessions, the focus of GA4 is on user-based insights gleaned from events and interactions. As a result, you get a clearer idea of what your users are doing. That's called "intent-based analysis": You learn not only what users are clicking on or viewing but also what they're trying to do.

That shift from "What are people seeing?" to "What are people doing?" potentially introduces a whole new direction for analytics: one focused on user engagement.

Marketers need to know their customers to build relationships with them, but demographics and psychographics won't help predict a customer's next action. Behavioral data about users is significantly better for predicting things such as purchases, upgrades, and churn.

What your customers do paints a better picture of their next action than who they are. Therefore, the key to understanding customers is knowing their actions across channels and showing them what they expect or need at each moment—the ability to answer before they ask!

Smarter Insights to Improve Decision-Making and ROI

The key differentiators of Google Analytics 4—user-centric reporting and built-in modeling—are powerful tools for marketers to understand their customers' journey.

More advanced models will still require heavy lifting from your data team, but another benefit of GA4 is that it also simplifies data extraction. That makes it easier to take your data from GA4 and combine it with other data from your customer relationship management system, order history, or other sources. Then, your team can spend their time building deeper, richer models that will give a more complete picture of your customers' behavior.

Using predictive analytics, marketers can differentiate actions across prospects and customers, leading to higher sales and retention without increasing costs. Customers can be ranked according to those likely to buy and those less likely to buy. Both rankings are a boon to sales teams because it gives them additional insights into the individual buyer's journey.

Using those ranking insights, sales teams can adjust their strategies to optimize sales. It also gives marketers the ability to help sales teams more accurately project their sales pipelines. And what sales team wouldn't want a more accurate sales pipeline?

Google Analytics 4 and You

After a year like 2020, there will be a natural resistance to more change. Google Analytics 4 will never be perfect—it will continually evolve—but those who embrace it will reap the benefits of being an early adopter to new ways of looking at the market.

Take this opportunity to see what others miss by looking at your analytics differently.

More Resources on Google Analytics

How to Marry Offline and Online Attribution Data for a 360 View in Google Analytics

The Small Business Guide to Google Analytics [Infographic]

Marketing ROI: How to Get Actionable Insights From Google Analytics