5 Reasons We Need Google Analytics 4

Google Analytics 4 is now considered a new standard in web analytics for acquiring better and improved opportunities in digital marketing. Nowadays, where technology is expanding at a higher pace, our purchasing behaviors and surfing are also.

Therefore, we need tools like Google analytics 4 to upgrade our digital performance. GA 4 brings a lot of advantages to marketers by engaging a massive audience, providing custom reports, and tweaking setup just for growing their ads and campaigns.

Do you find it challenging switching from UA to GA 4? In the next five minutes, you will know exactly the perks of using GA 4 and why you shouldn’t hesitate anymore.

Here are the five key reasons yoou need Google Analytics 4 to touch up your marketing strategy.

1. Free BigQuery Integration

GA 4 BigQuery is a cloud data warehouse which processes high-volume data at a fast speed and offers you to conduct an in-depth exploration of business performance and visitors’ activities. Moreover, connecting GA 4 with BigQuery is cheaper than Universal analytics, where customers pay for BigQuery integration. 

A few benefits of GA 4 BigQuery connection such as; 

  1. No data sampling ( to access the reliable data sources).
  2. Allowing GA 4 connection to third-party APIs.
  3. Transfer data from BigQuery to other visualization tools like Tableau, Google data studio, Power BI, etc.
  4. Correcting data options and customizing channel grouping.
  5. Exporting custom events parameters and dimensions.

2. Explicit Cross-device Tracking

In universal analytics, visitors’ behavior is recorded as Session. However, Google Analytics 4 is Event-based and captures the complete user’s journey on the web instead of just focusing on what they get there. 

So, for example, you can better investigate page scrolling, site search, file download, video/content engagement, etc. In addition, it will help you fix the points you’re lacking and improve the visitor’s engagement.

Moreover, GA 4 is not limited to just website tracking. You can also track app engagements and cross-device tracking in a single property. In this way, you can plan the campaigns successfully to target potential customers with GA 4. And this takes us to the third reason for using GA 4.

3. Top-level Built-in Reports

GA 4 with enhanced machine learning technology helps marketers to create custom reporting by removing irrelevant data points. In this way, you can upgrade the ROI on ads spent by making data-driven decisions and increasing your website/app effectiveness.

Compared to GA 360, GA 4 provides the “Exploration” option for the advanced data analysis, which includes: 

  1. Free form reports: arrange your data in a dynamic table layout.
  2. Funnel exploration reports: portray the steps visitors take before conversion
  3. Coherent exploration reports: illustrate the common attributes of a group of visitors 
  4. User explorer reports: shows the completion of the segment by users
  5. User lifetime reports: show how users behave on your website after their first visit.
  6. Path exploration reports the looping behavior of customers or the sequence of pages viewed by the users.
  7. Segment overlap reports: this allows you to visualize the relationship between different segments of the visitors.

By auditing these insightful reports, marketers can terminate the campaigns and ads where they are not getting desired response and make investments where the chances of their marketing growth are higher.

4. Analysis Hub

The Google Analytics 4 analysis hub provides additional information regarding visitors’ behaviour that surpass the built-in reports. Moreover, this advanced analysis is available without any cost in GA 4. Below are a few tools accessible in the analysis hub:

  1. The funnel optimization option enables you to set up any specific funnel
  2. Heat maps enable additional dimensions to your analysis
  3. Path analysis identifies the path visitors take across the web ( e.g. from reading a blog post to downloading a form). 
  4. Export data analysis in various formats
  5. Visualization techniques for your analysis

5. Predictive Metrics

The machine learning feature in Google analytics 4 plays a significant role in predictive metrics. The predictive analytics capabilities allow marketers to estimate the conversion rate and revenue in a specific time span. This feature includes:

  1. Purchase Probability 

The probability shows that the visitor who has been active in the previous 28 days will probably purchase in the next seven days.

  1. Revenue Prediction 

This field estimates revenue within the coming 28 days from the user who has been active on the site for the last 28 days.

  1. Churn Prediction

Churn predicts the visitor who was online in the past seven days will sign off in the next seven days.

The above metrics can hand you evaluate the predictive traffic for designing highly profitable campaigns to leverage your business. 

Final Verdict

Google Analytics 4 is continuously counting on its unique features. In the future, it will be the most efficient tool for robust analysis practices. The cookieless tracking and debugging view attribute make it stand out in digital marketing technology. Moreover, universal analytics will sundown entirely in 2023. That’s why you should switch to Google Analytics 4 because it’s better early than late. If you are looking for more information about GA 4 and Google Tag Manager, please visit Involvz.com

Author Bio Scott is a Technical Content Manager & Tagging Specialist at Involvz.com, one of the leading conversion tracking specialist company helping marketers and digital marketing Agencies with web tracking jobs. Scott enjoys his time with his wife and two little kids and loves playing basket ball.

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