Will GA4 Impact My Lead Generation?

Google Analytics 4’s Impact on Lead Generation

In digital marketing, lead generation is among the most important metrics to pay close and constant attention to. When a company generates leads, they are capturing the attention of potential clients and customers that express interest in the goods and/or services that they offer.

So begins the customer journey because now they are aware of the goods and/or services that could be solutions to their problems.

Data analytics is invaluable in improving lead generation because the data that is collected helps to narrow down where and how leads are being generated. With that information, marketing teams can generate high-quality leads that are more likely to be converted into paying customers with much less guesswork, thus improving return on investment.

So how will the new GA4 platform affect lead generation?

Data Collection Will Improve

In Universal Analytics, the standard way data is collected is based on “sessions.” Within a session, many specific “events” or actions may be occurring during the user journey on a webpage, but within universal analytics properties, those events will essentially go unnoticed unless a Google Tag Manager is properly set up to track them.

Being able to track specific events greatly improves data collection because it allows a marketing team to more accurately analyze what users are doing when they are interacting with a webpage or app. When you’re able to know the frequency and duration of a variety of specific events, more focused marketing strategies can be created to generate higher quality leads by improving the user experience.

While this functionality is not impossible with UA, it’s not as intuitive as it is with GA4.

Google Analytics 4 makes event tracking simpler because with it the standard method of data collection is through events, not sessions. In GA4 data can be collected through:

• Automatic Events–automatically tracked events when a user visits a webpage or app.
• Enhanced Measurement Events–additional, more specific data that can be collected with the push of a button.
• Recommended Events–events that Google recommends for all and certain properties that capture more customized data.
• Custom Events–create your events from scratch to gather the data that you want.

The improved flexibility of Google Analytics 4 compared to Universal Analytics is apparent. To take it a step further, when tracking an event, you’re able to create custom parameters to better understand what is happening when a user triggers an event. Even though there are limits to how many parameters can be created, GA4 is more robust than UA and promises to be a much more efficient analytics tool.

Machine Learning Will Predict User Behavior

As we get closer and closer to having robot overlords, we’ll begin to see advances in technology that seem like the stuff of science fiction. Our computers will soon know us better than we know ourselves, and Google Analytics 4 will bring us closer to that reality.

Machine learning on the web is a combination of artificial intelligence and computer science that discovers patterns of activity in user behavior and uses it to come up with almighty algorithms that create startlingly accurate predictions of how users will behave and what they will interact with most.

We’ve all seen this at work. Just log on to your Netflix account and look at your feed. Then go on someone else’s account and look at their feed. They’ll most likely look completely different because predictions of what Netflix’s algorithm thinks you’ll watch will be shown to you based on your previous behavior on the platform, and the same goes for the other person.

With GA4, predictions of what users will interact with and how based on their behavior will open the door for improved and tailored marketing campaigns focused on generating high-quality leads.

Tracking and predicting user behavior is essential to creating relevant content and publishing them where it will garner high engagement. Within GA4’s new platform digital marketers will be able to use predictive metrics that can measure the progress to a conversion.

As of now, there are three specific predictive metrics that GA4 supports:

• Purchase probability
• Churn probability
• Revenue prediction

This data is invaluable to not only generating leads but nurturing them as well.

With Google Analytics 4’s machine learning capabilities, you’ll be able to understand the user journey and user behavior with much more clarity, generating leads that will potentially have much higher rates of conversion. Along with that, nurturing leads will become a much more intuitive process, further increasing the chances of conversion. This could have a huge impact on the success of eCommerce companies.

Enhanced Engagement Metrics Provide More Clarity

Spending money on tons of Google ads won’t mean a thing if users aren’t engaging with them and subsequently your website. Understanding the data behind user engagement is critical to ensuring that leads are being generated and marketing dollars aren’t going to waste.

With this new version of Google Analytics, new engagement metrics replace the “bounce rate” and “pageviews” metrics that were standard in Universal Analytics. What’s important about this new feature is that now digital marketers analyzing data will be able to see who is staying on and interacting with a webpage/app.

Bounce rate is essentially the opposite of engagement, showing the percentage of users who did not engage with a webpage/app.

Google Analytics 4’s engagement metrics not only show the percentage of users who did engage with a webpage/app (These are called “engaged sessions”), they show engagement rate percentage, engaged sessions per user, and average engagement time.

These new ways of measuring engagement help to provide a better idea of how users are engaging with a webpage/app. This will help digital marketers improve the content and its organization on pages to increase engagement, generate more leads, and produce more sales.