Google has recently announced that it will be deprecating Universal Analytics, the version of Google Analytics that has been used by websites ever since its initial release in 2005. As part of the process, Google will fully retire Universal Analytics on July 1, 2023.
If you own or manage a website this may have an impact on your use of Google Analytics going forward. In order to continue using GA effectively and ensure your data remains accurate and reliable, you will need to migrate to the new version of Google Analytics – GA4 – which is currently being rolled out by Google.
While migrating can seem like a daunting task, particularly if you are unfamiliar with the technical aspects of managing website analytics programs, there are a number of tools and resources available to help you with the transition from UA to GA4.
In this article, we will have a closer look at the key differences between Classic GA and UA, and the changes Google Analytics 4 is going to introduce.
Classic Google Analytics vs. Universal Analytics: What Is the Difference?
Google Analytics and Universal Analytics are quite similar, they both provide users with powerful tools for tracking website data. Universal Analytics (2012) is simply the new version of GA, while Classic Analytics (2005) refers to the old version. All newly created Web Properties in Google Analytics are Universal Analytics properties, so no additional configuration was needed.
However, those who were still using Classic Analytics will need to take some time to update their accounts.
Universal Analytics is a powerful tool that has become an important part of web analytics. In October 2012, Google announced that it would be replacing Google Analytics with Universal Analytics as the next version of Google Analytics. The new tracking code was completely redesigned, providing more informative and analyzable data than ever before. It’s easier than ever to monitor and evaluate website performance thanks to these enhancements.
Google has been working hard to make sure that they can track your web browsing habits on all types of devices, and as such has changed the way their analytics system works. Instead of tracking individual users across different platforms like before (laptop/desktop computer; tablet devices such as iPads or Android phones), it now spans single user sessions. This way, universal data processing techniques will provide more accurate results than ever before.
Universal Analytics is a lot more visitor-centric whereas Classic GA was more focused on sessions/visits. However, understanding how users engage with sites is essential for providing a positive experience that leads to conversions.
The User Engagement feature (User ID) provides insights into how engaged your audience is with your content across different screens and visits. This information can help you identify areas for improvement and build a more tailored experience that meets the needs of your customers. By understanding how users interact with your site, you can improve the overall experience and increase the chances of conversion.
However, keep in mind that, Google is strictly opposed to the use of any personally identifiable information in your user account settings. This includes data such as zip codes and credit card numbers, which could potentially be used to identify a specific individual. Given Google’s commitment to privacy and security, it is essential that you do not include these types of data in your custom dimensions, metrics, or data import settings.
To protect user privacy and prevent potential violations of Google’s terms of service, it is imperative that you adhere to these guidelines at all times. If you have any questions or concerns regarding personal data that you’ve stored in your account, contact Google as soon as possible.
Tracking Code and JS Library
The difference between the JS libraries of Classic Google Analytics (ga.js), UA (analytics.js) and the latest GA4 (gtag.js) lies in how they track visitors’ data. The ga.js implementation, also known as the traditional GA code activated only after the content of the whole page loaded. Later on, analytics.js was introduced in 2012 to offer more precise data tracking and eliminate duplicate entries if a user is on multiple devices for access. However, the gtag.js API allows analysis of events data on Google Analytics, Google Ads, and Google Marketing Platform.
Number of Included Custom Variables
Google Analytics has experienced some major changes with Universal analytics. The most notable is that custom variables have become “dimensions”.
The Free Plan allows up to 20 of these dimensions or custom variables while the Premium Plan gives users, 200. In addition, in UA, you can create your own custom dimensions so that you can collect certain types of data.
The Measurement Protocol
The Google Analytics Measurement Protocol allows developers to make HTTP requests directly to Universal Google Analytics servers. This way, they can measure how users interact with businesses from almost any environment. Developers can then use the Measurement Protocol to:
- Measure user activity in new environments. The Measurement Protocol lets developers extend Google Analytics tracking code to new platforms and devices, giving them the ability to collect user data from anywhere. For example, a developer could use the Measurement Protocol to track how users interact with their business on a mobile app, on a connected device, or in a virtual reality environment.
- Tie online to offline behavior. The Measurement Protocol lets developers unify their data, so they can understand how users interact with their business across all channels. For example, a developer could use the Measurement Protocol to track offline conversions, such as when a user makes a purchase in a brick-and-mortar store after seeing an ad online.
- Send data from both the client and server. The Measurement Protocol lets developers send data from both the client and server for greater accuracy and flexibility.
In today’s digital age, businesses of all sizes need to track and analyze data to improve their products. As the most popular web-based analytics tool in use today, Google Analytics (GA) has been helping companies to do just that for nearly two decades.
Universal Analytics, the latest version of GA, builds on the foundation of earlier versions by using just one cookie called _ga to store user customization settings and tracking data.
Earlier versions relied on four separate cookies to collect data (utmc, utma, utmb, and utmz), _ga collects all this information in a streamlined and efficient way. This makes it easier to implement GA without making any major changes to your existing tracking code. As it allows you to easily segment your users based on their individual interests and needs, Universal Analytics gives you deeper insights into user behavior.
How Is Google Analytics 4 Different?
Unlike the preceding versions, the focus of Google Analytics 4 is events i.e user journey and privacy-first analytics. Another key difference is its user interface.
With the rise of machine-learning methods in the new Google Analytics version, businesses are now able to make accurate inferences about their customer base even in cases where user consent or cookie data is not available. This is due to the fact that advanced algorithms can analyze vast amounts of data and identify patterns and relationships that even human analysts might miss.
In particular, machine learning can fill in gaps where traditional analytics may be unable to gain a complete understanding of a customer base.
For example, internet users might opt out of being tracked by cookies or other forms of data collection, making it difficult for businesses to capture important information about these individuals. However, machine-learning analytics can still identify and track these individuals by analyzing browser data and other signals, thus allowing businesses to better understand their customer base. As such, the power and accuracy of machine learning in analytics represents a crucial trend that will likely revolutionize how businesses operate in both the online and offline worlds.
AI has revolutionized marketing in countless ways, and one of the most important new applications for this groundbreaking technology lies in predictive analytics. By harnessing the power of machine learning, marketers can model and extrapolate from existing data to gain a more complete understanding of site traffic, user behavior, and other key metrics. With this information, they can better tailor their marketing efforts to meet the needs and preferences of their customers.
One particularly useful application of AI-powered predictive analytics is the recently launched Insights feature, which automatically highlights key information to help marketers optimize their campaigns and achieve their goals. Designed to provide a comprehensive view of the customer journey across devices and channels, Insights enables marketers to more effectively target relevant audiences and track engagement with greater accuracy.
Overall, it is clear that AI is a powerful tool that is transforming how brands approach digital marketing.
Data Collection and Cookies
As the digital landscape evolves, so does the need for reliable and adaptable data tracking tools. Google Analytics 4 is designed to meet this need, offering a comprehensive yet flexible solution for measuring website performance. GA4 features “data streams” instead of the views and segments used by old Universal Analytics properties, making it more compatible with future trends.
In GA4, “page views” are converted to “page view” events. While Universal Analytics events are composed of three pieces: a Category, Action, and Label, there is no longer a distinction between hit types in GA4, as every “hit” is an event. The processing platform takes care of all of them equally.
Additionally, there is no “view” level section in GA4; while traditional Universal Analytics has three levels (Account, Property, and View), GA4 only has Account and Property levels. This simplifies the process of data collection and analysis.
Finally, whereas “event tracking” in Universal Analytics required modified Analytics code or migrating to gtag.js, Google Analytics 4 claims to enable editing, tracking and fine-tuning of events within the UI. This means that users can customize their event tracking without needing to code or learn complicated scripts.
Furthermore, new features like data import and cross-domain tracking, marketers can easily integrate data from a variety of different sources into their existing Google Analytics 4 platform. In addition, the new ’Life Cycle’ report allows marketers to visualize and better
understand user behavior across the various stages of the buyer’s journey.
And finally, the ‘eCommerce funnels’ template provides an effective way to display and analyze key metrics for online sales endeavors.
Overall, Google Analytics 4 is a powerful tool for marketers and is well-suited for the ever-changing digital landscape.
Connected Site Tags
The Google Tag Manager (GTM) is a tool that allows you to set up tracking codes on your website without having any coding knowledge. This means it’s easy and convenient.
Although not every site will work with the default configuration of GTM tags and connected site tags are effective only when ALL page URLs are tagged with a gtag.js snippet. Keep in mind that this implementation is also only partial, or if you’ve used an irregular track code or UA custom configurations, the data may not properly translate in GA4.
If you’re feeling a little lost with all of these changes, don’t worry. It’s normal. However, it’s important that you make the switch over as soon as possible to avoid any issues.
Luckily, our team of inbound marketing specialists at DevriX can help make the transition quickly and easily – so you can start seeing all the amazing features that GA4 has to offer.
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