Google Analytics: The Backbone of Website Data Tracking
If you have a role in making a business successful, you probably know how important it is to have accurate and timely data. It’s the roadmap that guides your sales and marketing for a profitable business that can survive and thrive.
When it comes to monitoring website data, Google Analytics has been the trusted tool for marketers and website owners for almost 20 years.
Currently, Google Analytics is being used by a whopping 4.5 million websites in the US alone! But that’s not all; globally, you can find GA on over 60% of the top 100,000 websites and over 50% of all sites online, according to BuiltWith Data.
It’s safe to say that Google Universal Analytics (GA3) has completely transformed how we track website data and gain insights since its launch in 2005.
Thanks to its advanced tracking abilities and user-friendly interface, businesses have gained valuable knowledge about their web visitors’ behaviors. This, in turn, has allowed them to customize their marketing campaigns to suit their audience better. It’s been a game-changer, no doubt about it.
But, like with most digital things, nothing sticks around forever. So the days of GA3 and Universal Analytics are numbered. By the time you read this, they might already be ancient history, thanks to the new Google Analytics 4 (GA4).
Key Takeaways – What’s going away?
GA3 Sunset: Safeguard Your Data Before It’s Gone Forever – July 1st, 2023
Let me be crystal clear: losing years’ worth of data is a business owner’s worst nightmare. And if you’re relying on any of these vanishing features and methods to track your website data, it’s absolutely crucial that you take action immediately.
Here’s the truth: these features and the historical data they provide are not just nice extras – they are vital elements for any successful marketing campaign and overall business strategy.
Figuring out how to effectively utilize the new methods and tools in Google’s updated interface will significantly impact your ability to navigate the upcoming months and years.
Without access to the invaluable data these tools have given us over the years, businesses will miss crucial insights into their customers’ behaviors and preferences.
Don’t procrastinate until your data disappears entirely. It’s time to take immediate action with the information in this post to safeguard your historical data and position your business to effectively capture all the new data coming your way.
Migrating from GA3 Features to GA4: What They’re Not Telling You
You might think that the worst-case scenario is letting Google handle the update for you and preserving your data for future filtering. But, unfortunately, it’s not as simple as that, and there’s an even scarier aspect to consider.
When migrating from GA3 to GA4, the new Google software, interface, and data collection tools require significant effort to set up correctly. We want to assist you by highlighting the most crucial things being phased out and what steps you need to take to obtain similar data now that Google has transformed its legendary data tool.
Speaking of the scary part, while setting up all the new tools is undeniably vital, it’s equally essential to understand how to safeguard the years of historical data still stored in GA3. Spoiler alert: you won’t be able to retain it. However, we’ll discuss how to navigate this challenge later on.
Without any further ado, let’s jump into the top 10 disappearing Google Analytics features, why they hold significant importance for your business, and explore the new alternative solutions.
Farewell to Reporting Views – It’s been fun, RAW, MAIN, TEST.
One of the initial changes you’ll notice is removing reporting views in GA4. Setting up reporting views was always the first step for many experienced GA users who manage business analytics.
Reporting views allowed you to create different perspectives of your data for generating reports. My usual setup involved having a “RAW” view encompassing everything – every user, bot, and employee involved in the project – with no filters, aka all the data.
The second view, “Main,” was the one I used to pull reports. It filtered out bots and internal traffic, typically through IP address-based filters. However, I’ve had some creative filtering solutions over the years.
The final view was the testing view, acting as a sandbox for experimenting with new filters without worrying about unintentionally excluding essential data, like accidentally filtering out North America. Yes, that actually happened.
This feature holds great significance to me because of my past experiences and the mistakes I made with data before I adopted the multiple-views approach.
Now, let’s examine the differences between GA3 Reporting views and GA4.
In GA4, the approach is to provide easily accessible filters that can be applied to your primary dataset. With this method, you always maintain your raw data and use different filters.
While this approach seems promising, it’s important to consider the costs associated with filtering data (running queries) against your raw dataset.
It can become quite expensive compared to starting with a smaller data set, like the “Main” view in GA3.
We’ll delve into the costs of queries and filtering later when we discuss BigQuery.
Advantages of GA4’s Filtering Approach
Flexible Analysis: GA4’s dynamic filtering replaces the need for separate views. This offers enhanced flexibility within a single view but requires initial filtering to be set up. It allows you to analyze all data while applying filters based on your specific needs.
Streamlined Configuration: GA4’s single view with multiple filters simplifies management by eliminating the requirement for multiple views with different filters. This reduces administrative overhead and ensures consistency across data views.
Continuous Data Retention: With GA4, data retention remains constant since you’re always filtering the raw data. You can refer back to any previously filtered data sets whenever needed.
However, (and this is a big however), it’s important to note that reporting on large, unfiltered data sets may incur additional costs compared to working with pre-segmented data.
We’ll provide more detailed information on BigQuery and its pricing structure later in this article.
This should provide you a general understanding of the potential advantages, and possible disadvantages of GA4’s filtering approach, let’s keep going.
Saying Goodbye to Native User ID Tracking in GA3: How GA4 Measures Differently
User ID tracking has played a pivotal role in Google Analytics, and its absence without some replacement will negatively impact businesses. Personalized experiences for users, leading to higher engagement rates, will be compromised without this feature or something similar.
User ID tracking allowed businesses to offer targeted promotions based on individual customer behavior. For instance, a travel website can offer special rates on hotels in Hawaii to customers who have searched for flights to that destination. Losing User ID tracking means potentially missing out on this level of personalization.
Exploring GA4’s New Measurement Approaches: Are They an Improvement?
In GA4, Google takes a fresh approach to tracking user IDs compared to the older GA3 system. GA4 introduces a more privacy-centric strategy, enabling businesses to track user interactions across multiple devices and sessions.
Instead of solely relying on user IDs, GA4 combines various identifiers such as device IDs (think: phone, desktop, tablet), cookies, and Google signals to monitor user activity across devices and sessions. This allows Google to understand user behavior without explicitly revealing their identities.
GA4 leverages events to track specific user actions and user properties to provide additional information to user profiles. This flexibility enables businesses to gather valuable insights while respecting user privacy and adapting to the evolving privacy regulations of different regions and countries.
Additionally, GA4 introduces a useful feature called “Measurement Protocol.” This feature allows developers to set up tracking via http requests to track user interaction outside of your website for other connected interfaces.
This can be used to track interactions at kiosks, other applications, retail point-of-sale systems, or any other non-traditional interface for cross-device tracking that was not readily available in GA3.
GA4 prioritizes privacy-friendliness while monitoring user engagement with websites and apps. By utilizing different identifiers and allowing customization in data collection, GA4 aims to achieve the best of both worlds: valuable insights and privacy protection.
The Good News – You Can Still Create Your Own User IDs
Although Google has removed the default functionality of User IDs to preserve privacy, if you comply with your local privacy laws and have provided your users with the proper opt-in options, you can still create, collect, store, and track your own internal first-party user IDs. Our preferred method is Google Tag Manager.
Rethinking Remarketing in the Age of GA4: The End of GA3’s Era
Remarketing audiences based on user behavior is an essential feature that’s evolving in Google Analytics as we transition to GA4.
Regarded as one of the most effective forms of advertising in terms of return on investment, remarketing empowers businesses to precisely target their ads towards users who have taken specific actions on their websites. These actions can range from simple site visits to adding items to the cart or completing various forms.
For instance, an online retailer could use these audiences to show tailored ads promoting products viewed by users but not yet purchased. Without this capability, businesses lose significant opportunities for increased revenue through targeted advertising efforts.
With the disappearance of this traditional form of remarketing, businesses can no longer leverage user behavior to target specific audiences similarly.
Companies may struggle to optimize ad targeting and achieve lower conversion rates without remarketing audiences based on user behavior.
Needless to say, businesses must adapt to Google’s “New” approach; the alternative is guaranteed to waste valuable ad dollars.
Replacing Remarketing Functionality in GA4
In GA4, remarketing functionality is no longer directly integrated within the platform itself. Instead, GA4 integrates with Google Ads and Google Marketing Platform to manage remarketing campaigns and audience targeting.
How GA4 Remarketing Differs from GA3
- Separation of Platforms: In GA4, remarketing is managed separately through Google Ads and Google Marketing Platform. This means that website owners will need to set up and manage their remarketing campaigns on these platforms rather than within the GA4 interface itself.
- Event-Based Audience Creation: GA4 focuses on event-based audience creation for remarketing purposes. Events, such as specific user actions or interactions, can be used to create customized audience segments for targeting in remarketing campaigns. This allows for more precise audience segmentation based on user behavior.
- Enhanced Privacy Measures: GA4 places a greater emphasis on user privacy and data protection. The event-based approach and separate remarketing platforms help ensure compliance with privacy regulations. It gives users more control over their data and the ability to manage their ad personalization preferences.
- Expanded Integration Options: GA4 provides enhanced integration options with Google Ads and Google Marketing Platform. This integration allows for better data sharing and remarketing capabilities. It enables website owners to leverage the full power of Google’s advertising ecosystem while utilizing the insights gained from GA4.
It’s important to note that remarketing in GA4 is tightly integrated with Google Ads, so users will need to have an active Google Ads account and familiarity with Google Ads remarketing features.
By linking GA4 and Google Ads, enabling advertising features, creating audiences, exporting them to Google Ads, and setting up remarketing campaigns, users can effectively utilize remarketing capabilities in GA4 to target their ads to specific audiences based on user behavior and interactions.
Steps to Setup Retargeting in GA4
- Link Google Analytics 4 and Google Ads: Start by linking your GA4 property to your Google Ads account. This can be done by selecting the “Data Streams” section in GA4 and selecting the relevant data stream. Then, click “Google Ads linking” and follow the prompts to connect your GA4 property to your Google Ads account.
- Enable Advertising Features: Within GA4, navigate to the “Admin” section, and select the GA4 property you want to enable remarketing. From there, click “Data Settings” and toggle the “Enable advertising features” option. This will enable the necessary data collection for remarketing purposes.
- Set up Audiences: In GA4: Audiences are used for remarketing. To create audiences, go to the “Audiences” section under “Configure” in the GA4 interface. Click “New audience” and define the audience criteria based on your targeting needs. You can create audiences based on user interactions, events, or specific user properties.
- Export Audiences to Google Ads: Once your audiences are set up in GA4, export them to your linked Google Ads account. To do this, select the audience you want to export, click “Actions,” and choose “Export to Google Ads.” This will make the audience available for targeting in your Google Ads remarketing campaigns.
- Create Remarketing Campaigns in Google Ads: With your audiences now available in Google Ads, you can create remarketing campaigns using the familiar Google Ads interface. Set up your campaign goals, targeting options, ad creatives, and budget within Google Ads. Choose the appropriate audience(s) exported from GA4 to target your ads to users who meet the defined criteria.
Demographics and Interests Reports – A new method for unlocking audience insights
The Demographics and Interests reports have always been valuable for businesses, offering essential insights into their audience’s age, gender, interests, and location. By leveraging these reports, businesses have gained a deeper understanding of their target audience, allowing them to craft more effective and personalized marketing campaigns.
However, with the imminent disappearance of Demographics and Interests reports as we’ve known them in Google Analytics, businesses will face challenges in personalizing content and adapting messaging strategies based on specific demographic group preferences.
Understanding the Significance of Demographics and Interests Reports
The demographics and interest reports generated from Google Analytics have been a cornerstone of a successful digital marketing strategy. They provide valuable insights into visitor characteristics crucial for optimizing content and advertising campaigns targeted at specific groups.
Businesses have utilized these reports to boost product sales by identifying their most loyal customers and tailoring marketing campaigns to align with their preferences. Losing total access to this feature would significantly hinder businesses’ ability to obtain these vital insights effectively.
GA4’s Approach to Demographics: Privacy and Enhanced Insights
In GA4, Google again takes a privacy-centric stance by shifting away from relying on third-party data and cookies. Instead, they leverage machine learning to gain insights into user demographics and interests to maintain privacy.
Significant changes have been made in GA4 to understand website visitors and their interests with four key additions:
- Modeled Audiences: GA4 uses “modeled audiences” to estimate information about website visitors. By analyzing user behavior patterns and interactions through machine learning algorithms, GA4 can make educated guesses about their age, gender, and interests.
This method gives businesses a general understanding of their audience without relying on personal data.
- Event Tracking and User Properties: GA4 emphasizes “event” tracking of specific user actions on the website to capture data on events such as button clicks, form submissions, video plays, and other significant interactions.
Additionally, businesses can attach custom attributes to user profiles using user properties, allowing for more detailed audience segmentation.
- Enhanced Insights with Exploration: GA4 introduces the “Exploration” feature, providing advanced analysis capabilities.
Businesses can delve deeper into their data, apply filters, and create custom segments based on various dimensions, including estimated demographics and interests. This empowers businesses to uncover meaningful insights about their audience’s characteristics and preferences, aiding in informed decision-making.
- Privacy and User Control: Maintaining user privacy and data protection commitment. GA4 adheres to privacy regulations by focusing on consent and granting users control over their data.
Users can manage their ad personalization settings and exercise control over data usage. This approach ensures businesses can obtain valuable insights while respecting user privacy preferences.
By incorporating modeled audiences, event tracking, user properties, enhanced insights through Exploration, and prioritizing privacy, GA4 provides business and website owners with a privacy-conscious and customizable approach to understanding their audience.
The new methods enable data-driven decision-making while upholding user privacy and data protection throughout the process.
Revamped Tracking: Custom Dimensions and Events Take Center Stage Over Custom Variables And Metrics
In the transition from Google Analytics 3 to GA4, the concept of custom variables and metrics has undergone significant changes. GA4 introduces a more flexible and powerful way of tracking and analyzing custom data points.
But you may wonder, “I’ve been using custom dimensions for years; what’s the difference?” We will take a look at the changes to dimensions shortly. Hang tight.
The Necessity of Custom Variables and Metrics (Or something like them)
Custom variables in Google Analytics have been instrumental in tracking unique data elements such as user types or geographical locations.
Similarly, custom metrics have allowed businesses to define specific KPIs (key performance indicators) not covered in standard analytics reports.
However, with the disappearance of custom variables and metrics, businesses may lose a crucial tool for effectively monitoring website performance.
Imagine an online retailer that relies on custom variables to track the number of users who add items to their cart but fail to complete the checkout process.
Armed with this information, they can create personalized campaigns with compelling offers, targeting those hesitant buyers and encouraging them to finalize their purchases.
Without this valuable insight and segmentation of specific user behavior, the business would struggle to target users who abandon carts frequently.
GA4 Dimensions vs. GA3 Custom Dimensions: What Sets Them Apart?
So how do they differ? A few ways…
- Scope: In GA3, custom dimensions have hit-level scope, meaning they are to individual data points within a session. In contrast, GA4’s custom dimensions have event-level or user-level scope.
Event-level custom dimensions are associated with specific events, and user-level custom dimensions are tied to user profiles. This provides more flexibility in capturing and analyzing data.
- Flexibility: In GA3, custom dimensions were restricted by predetermined “slots” where data could be stored. GA4 breaks free from these limitations by allowing users to create custom dimensions whenever they want without being constrained by limitations. This allows users to define their own data categories based on their specific needs.
- Event-Driven Data Model: Events are the primary data points in GA4. Custom dimensions in GA4 are associated with events, allowing for more granular analysis and segmentation.
- Enhanced Parameter Reporting: GA4 introduces the concept of parameters, which can be used within events to capture supplementary data.
Parameters enable businesses to pass dynamic values alongside events, offering more detailed insights and contextual information. This feature enhances the capabilities of custom dimensions, allowing for nuanced tracking and analysis.
Saying Goodbye to Goals and Funnel Visualization in GA3: Comparing Funnels and “Goals” between GA3 and GA4
The transition from goals and funnel visualization in GA3 to GA4’s new approach may not surprise many. For many of us, our goals were already intertwined with specific event data, making it a logical evolution to roll them up into GA4’s events and conversions. Let’s delve into the differences between these two methods.
Goals in GA3:
In GA3, goals served the purpose of tracking specific actions or conversions on a website. They allowed us to define and measure significant activities, such as completing a purchase, submitting a form, or reaching a specific page.
Events and Conversions in GA4:
In GA4, the traditional concept of goals has been replaced with standard events and conversions.
Events are interactions or actions initiated by users that administrators define, such as button clicks, video plays, purchases, add-to-cart actions, downloads, and more.
These events can be tracked and analyzed to gain valuable insights. On the other hand, conversions in GA4 are specific events that businesses identify as crucial to their objectives, akin to the goals set in GA3.
With this transition, GA4 introduces a more comprehensive and flexible framework for tracking user actions and measuring conversions.
It empowers businesses to define and analyze events that align with their specific goals and objectives, allowing for a more customized and granular understanding of user behavior.
Comparing Funnel Visualization and Funnel Analysis: GA3 vs. GA4
GA3 includes the Funnel Visualization report, designed to analyze the conversion process or steps leading up to goal completion.
It lets you visually represent a conversion funnel by defining specific steps or pages users should go through. This provides insights into the drop-off rates at each step, allowing you to identify potential bottlenecks or areas for optimization within your conversion process.
GA4 introduces the Funnel Analysis report as a replacement for funnel visualization.
This report provides a more flexible and customizable approach to analyzing user journeys and conversion funnels.
With Funnel Analysis, you can define specific events or steps in a funnel, segment your data, and analyze user behavior at each stage. It offers advanced features like drop-offs, flow visualization, and conversion rates, allowing you to gain insights into user behavior patterns and identify areas for improvement within your conversion process.
Saying Farewell to Enhanced E-commerce Tracking and Data Layers in GA3: What’s Next in GA4?
Introducing new e-commerce data tracking methods in GA4 excites many marketers and business owners.
In that case, it’s understandable if this change initially feels disheartening. However, fear not. You still can have plenty of areas where using advanced customized incorporations of data layers will be an advantage.
And it’s important to remember that your previous experience will undoubtedly prove valuable and contribute to your success with the new tracking methods.
In GA3, and in some advanced ways in GA4, the data layer is essential for transmitting relevant data such as order numbers, SKUs, order value, and so on to GA3 for reporting and analysis.
The good news is that tracking e-commerce data in GA4 should, theoretically, become much more straightforward.
GA4 relies on event tracking to capture e-commerce data. Businesses can incorporate event tracking code into their website or app, enabling the sending of specific events associated with various e-commerce actions.
Events include crucial parameters such as product details, transaction information, and user interactions.
While this transition may feel like a departure from the familiarity of Data Layers, embracing event tracking in GA4 opens up new possibilities. It simplifies tracking e-commerce data, making it easier to gain valuable insights and optimize your e-commerce strategies.
Key Differences in e-commerce Tracking from GA3 to GA4:
- Flexibility and Customization: GA4 offers customizable event tracking for specific e-commerce actions, providing businesses with tailored insights.
- Simplified Implementation: GA4 simplifies implementation with direct event tracking, eliminating the need for a separate data layer.
- Data Analysis: GA4’s event-driven approach allows for more detailed e-commerce data analysis, including custom events for deeper insights into user behavior and conversions.
- Transition and Migration: Migrating to GA4 requires adjustments to align with the event-driven approach, offering opportunities to leverage advanced features and gain valuable e-commerce insights.
It’s important to note that while GA4 offers a more flexible and event-driven approach to tracking e-commerce data, the transition from GA3 to GA4 will involve some initial setup and configuration to ensure a smooth migration and alignment with business-specific e-commerce requirements.
Historical Data, A.K.A. The Money Grab
Ok, so we’ve all benefited from GA for years for free, some of us grey beard types maybe a little longer than others, but as one of the worlds premiere tools, it was only a matter of time before Google found an effective way to monetize it to the little guys that couldn’t afford the massive six-figure price tag of GA 360.
“What do we have to pay?” you ask. Enter Google BigQuery, a tool promoted as a means to use, view, and manipulate large volumes of data at a relatively affordable cost.
If you store less than 10GB of data and process less than 1TB of data, BigQuery is free. You are probably in this category if you get fewer than 100,000 monthly visitors.
*Tip – If you’re concerned about unexpected charges, there is also the BigQuery “Sandbox,” which functions just like the paid version with the same free limits but without requiring you to enter your credit card information.
However, it’s crucial to note that BigQuery charges are based on the number of searches and queries performed. Connecting your BigQuery data to platforms like custom reports in Looker Studio is possible but costly. Each page refresh or filtered request may trigger multiple new queries, leading to potential expenses.
Another significant change in GA4 is the limited historical data availability. Unlike in the past, where you could reference data even if it wasn’t updating, GA4 restricts historical data to only 14 months. If you want to analyze the performance of past events, such as a Black Friday sale over the last two years, you’ll need to rely on BigQuery or a similar tool.
BTW: Say Goodbye To your GA3 Data
had always hoped to keep my GA3 data accessible in the GA interface for future reference, even if it stopped updating. Unfortunately, that’s not the case.
Google has made it clear that access to historical GA3 data will be available for at least six months, but there are no guarantees beyond that. This means it’s time to take action, migrate your GA3 data, and prepare for the next steps in your data management journey.
The Consequences of Data Loss: Are You Ready to Lose Years of Insights?
The disappearance of historical Analytics would be a catastrophe for most companies. Imagine being in the dark about your best customers’ behaviors, preferences, and actions on your website over the past five years.
The absence of this vital information will pose significant challenges when making informed decisions about your marketing strategies.
Optimizing your marketing efforts becomes an uphill battle without clearly understanding your customers.
This puts your business at a considerable disadvantage compared to competitors on top of their game.
Potential Business Losses
We don’t want to sound alarmist, but the severity of the situation cannot be overstated. Losing valuable insights into customer behavior means missed growth and revenue generation opportunities. The implications go beyond mere inconvenience. Like most companies, businesses that heavily rely on data risk substantial long-term financial decline if they fail to take proactive steps to protect their data.
Some Additional Tips on Making the Switch Yourself
You might encounter a few challenges when you start moving to custom dimensions and events in Google Analytics 4.
Challenges to be aware of when completing a migration
- Data Structure Changes: Custom variables and metrics in GA3 have a different structure than custom dimensions and events in GA4. You will need to reconfigure their data structure and mapping to align with the new event-driven model of GA4. This may require updates to your tracking code and data collection methods.
- Migration Effort: Moving existing custom variables and metrics to custom dimensions and events is a manual process, you will need to identify the equivalent events in GA4 and update them accordingly. This could be time-consuming for websites with complex tracking setups and numerous custom variables/metrics.
- Reporting and Analysis Adjustments: You must adapt your reporting and analysis workflows to leverage custom dimensions and events’ capabilities effectively. This may require learning new tools and techniques for extracting insights from the event-driven data structure of GA4.
- Metric Calculation Limitations: Unlike custom metrics in GA3, GA4 does not have a direct equivalent for custom metrics. However, you can explore exporting data to BigQuery and perform advanced calculations as a workaround.
- Training: You must become familiar with the concepts and implementation of custom dimensions and events in GA4. This may take a while to fully understand the event-driven data model, scope limitations, and best practices for effectively utilizing custom dimensions and events.
Concluding Thoughts on GA4 Migration: Safeguarding Your Data
As crucial features of Google Analytics undergo changes or disappear altogether, it becomes the responsibility of every business and website owner to take proactive steps in protecting their valuable data from being lost in the abyss.
By following these essential measures we’ve outlined, you can ensure the security of your historical data while effectively utilizing new data for years to come.
There may be unfamiliar concepts and challenges to navigate during the transition to GA4, even for seasoned GA professionals. However, it is crucial to configure and accurately collect all your data without delay.
If you prefer a streamlined and efficient process, consider partnering with a GA specialist with extensive experience implementing custom GA4 setups tailored to various scenarios.
At CWdynamic, our team can swiftly configure and integrate your website with GA4 and BigQuery’s sandbox in a few days, safeguarding your data from potential loss.
Taking swift action is paramount, as these valuable features may soon be gone forever. It is vital not to be complacent but rather act decisively to secure your data and unlock the full potential of GA4.
Protecting your data is valuable; it should be a top priority. Act now to ensure a seamless transition and continued success in the evolving data analytics landscape.