Master Google Analytics 4: Essential Tips for Marketers

 Analyzing user activity on your digital offerings, including websites and apps, is an important task for any online marketer. Through Googl...

 Analyzing user activity on your digital offerings, including websites and apps, is an important task for any online marketer. Through Google Analytics 4 (GA4), you can access analytics tools so you can focus on content, campaigns, and activities.

We all move online every day. We read the daily news on our phones; we communicate and watch videos; we order things or look for a hotel for our next trip. Our data is always collected by the providers (sometimes more, sometimes less).

This data helps providers evaluate and improve their content. Is an offer viewed often, or does it generate little interest? How well does the new shopping cart work compared to the old one? Which buttons in an app are rarely clicked?

Most companies also want to assess the success of their marketing measures as accurately as possible. Which campaigns lead to many purchases? Which newsletters generate the most clicks?

An analytics tool like Google Analytics looks at an individual’s online presence as a whole regardless of whether this presence exists on one website or five and then collects and links this data in such a way that complex relationships can be explored, for example, “How many users came to our website/ web 3 via our newsletter, then watched the video, and ended up ordering our package 1?”

Google Analytics has established itself as the standard for analyzing user activities on websites. This comprehensive and stable tool has been free for online users and companies for years.

In this post, you’ll learn more about how GA4 works, where it comes from, and how Google Analytics is embedded in the wider Google ecosystem. In this post we will cover some background information to help you operate Google Analytics successfully.

What Does a Web Analytics System Do?

The latest version of Google’s web analytics platform, Google Analytics 4 (GA4) helps you record, analyze, and evaluate user activities on your websites and in your apps. GA4 reports provide valuable insights into user behaviors and thus help you to further develop your offerings and campaigns based on real data.

As a web analytics system, GA4 covers a range of tasks, such as the following:

Data collection

• Collecting information about your users, such as their location or the device used
• Identifying sources of traffic, for example, whether users find an offering via search engines versus through campaigns
• Tracking user actions on a website or in an app, such as the pages accessed, the links clicked, the forms sent
• Collecting all data within a framework of privacy policies

Presentation as reports

• Offering dashboards with the most important key figures and tables on the collected user data

Data analysis

• Providing tools for in-depth analysis beyond most popular reports
• Recognizing trends and patterns in user behavior
• Identifying weak points and optimization options
• Segmenting users according to specific criteria

Goal setting and conversion tracking

• Measuring specific actions such as sales or leads
• Transferring this data to other marketing systems, such as Google Ads

Google Analytics provides this wide range of functions free of charge and is (relatively) user friendly. You can choose from flexible reporting options and integrate with other marketing tools. GA4 is probably the most widely used analytics tool in the world, so you’ll find many guides, solutions, and support for various issues online.

What Is Google Analytics 4?

GA4 is a stable, data privacy-compliant platform for measuring user activity across devices. As shown in Figure below, a major driver in the development of GA4’s current version was the consolidation of user data from websites and apps, in other words, cross-device measurement. In previous versions of GA4, these data pools could only be recorded separately.

Google Analytics for Websites and Firebase for Apps

The roots of GA4 lie in its app tracking abilities, and thus, user-centricity and cross-platform options were considered right from the start. Especially for stores that offer both a website and an app, a joint view of user data is advantageous since you can then track customers on multiple systems.

Events Take Center Stage

When tracking, GA4 focuses on events, which map all user actions, whether loading a page, clicking a button, or starting a video. Pageviews are an event called page_view; e-commerce sales are an event called purchase. The most important parameter for linking actions together is the user, which always has a unique identifier.

The metrics in a website’s reports, such as page views and sessions, are derived from these events and users each metric is a subset of the user’s activities, so to speak.

With events as its basis, analytics becomes independent of page views (although page views still exist as a report and a metric). But the use of events goes even further: For example, some properties of users are saved as events. The first time a website or an app is loaded, a corresponding event occurs, as does the start of a new session.

Events in GA4 are the only basis for the definition of key events. In previous versions of Google Analytics, you had to choose between pageviews or events when defining goals. GA4 now only offers events for defining conversions. 

In general, GA4 is quite flexible in the use of events and parameters for data collection. The focus on events has several advantages, such as the following:

• Since all user properties and actions are saved as events, Google Analytics only needs to analyze events. Complex calculations on a query are reduced, and results are available more quickly.
• In an event report, you can look “under the hood” of Google Analytics. In this report, you’ll find all the events used by GA4, including events generated for internal calculations.
• To combine the data from a website and from an app, this independence pays off. As soon as an event on a website and an event in an app have the same name, they are shown as a single entry in GA4 and included in the total values.

But this focus on events also has a disadvantage: This data model differs fundamentally from the previous version of Google Analytics, which was in use until summer 2023. As a result, GA4 reports were reinitialized, and no data was transferred from the old version. If you did not implement GA4 yourself and let Google convert an old Universal Analytics property, you will hardly find any data collected before 2023 in your GA4 reports.

Where Is My Old Data?

The previous version of Google Analytics was called Universal Analytics (UA), sometimes referred to as GA3. This version of Google Analytics had been in use since 2012 with a few updates, of course, but by and large on the same technical basis. In March 2022, Google announced that it would stop collecting data with UA in July 2023. The newly developed Google Analytics 4 entered the race as an alternative and successor, as shown in below figure.

The Evolution from Google Analytics to GA4

Google had announced an automatic switchover to the new version for some universal properties. However, “automatic” in this context did not mean that the existing reports were updated to the new frontend as you would expect from a Windows update, for example. Instead, the changeover involved the following conversions:

• A GA4 property was automatically created for existing universal properties.
• Redirects were created for the tracking requests.
• Some settings were adopted but not all.

However, neither the data already collected, nor all the settings, were transferred in their entirety! Therefore, you won’t find any data older than summer 2023 in these automatically converted properties.

The reports of the old universal properties were kept available by Google for another 12 months (i.e., until summer 2024). They have since been deleted by Google. If you have not exported these reports, this data is lost and can no longer be restored.

The New World of Measurement

A good analytics tool should cover many important functions in your online marketing efforts. But a comprehensive setup for your digital marketing efforts requires more components.

Components of a Marketing Technology Setup

The tools and services that revolve around this setup fall under the generic term marketing technology (sometimes shortened to martech). Even for small websites, such a setup can quickly involve a handful of components, as shown in below figure.

Sample Marketing Technology Setup for a Website

On the Landing Page

The first building block that users encounter on your website is the request for their consent to data collection. Various solutions to obtain this consent are available, both external services such as a consent management platform (CMP) and plugins for your content management system (CMS). The more data you want to collect and use on your website, the more important having properly obtained and documented consent is.

Thus, data collection begins with a user’s consent. This consent is acquired via a code from Google that you integrate into the page. You have two options for this step:

You can integrate the Google tag (gtag) tracking code directly into the source code of your page. The Google tag is the basis for all tracking in the most common Google tools.

Alternatively, you can use Google Tag Manager in your website, which in turn loads the Google tag. Google Tag Manager is a free service provided by Google that allows you to manage tracking from Google and other providers.

The second variant is a little more complex to set up for the first time, but you’ll have access to a powerful management tool for all the measurements you may want to include on your website, whether for Google or for other providers.

Inside Tag Manager

Once you want to use more than Google Analytics (for example, tracking tags for Meta/Facebook or Microsoft Bing), we recommend using Google Tag Manager. Within a Google Tag Manager container, you can integrate and control various tools independently of your CMS or store. 

Conversions and Important User Actions

When collecting data, most marketing tools differentiate between general data, which is collected when a script is called, and the user actions that are important to the company, which are called the conversions. GA4 refers to these actions as key events, which are defined in the administration settings. Other services require explicit tracking codes, which you can integrate via Google Tag Manager, for example. 

Extended Conversion Data

So conversions can be even better connected to advertisements and audiences, the Google tag as well as other tracking codes provide the option of transmitting additional user data with a call, for example, an encrypted email address, if that data is available.

GA4 as a Central Database in Online Marketing

Google puts a lot of effort into collecting your users’ data efficiently and comprehensively. Ultimately, the implementation also means a lot of effort for you. Why should you make the necessary adjustments to bring as much data as possible into the analytics tool?

More data is always more meaningful than less data. Of course, a 100% rate of measured access is almost impossible to achieve. In other words, you’ll probably never see all clicks and all purchases in Google Analytics. Nevertheless, finding out as much as possible about your user base is worth the effort.

Increasingly, the data collected online is processed semi-automatically or fully automatically rather than being analyzed manually. Some campaigns in the Google universe only work based on budget and conversions. Google itself decides on the display of ads and where exactly they are advertised and when. This process requires clean data collection, and manual corrections or interventions are no longer possible.

Especially in a campaign service, user actions and data are used for automatic optimization. The biggest challenge now is to provide the service with the necessary data no longer to make manual adjustments to campaigns based on analyses.

GA4 provides interfaces to all the important marketing tools from the Google ecosystem:

• Google Ads for search campaigns
• Google Display & Video 360 (DV360) for programmatic campaigns
• Google Search Console for search engine optimization (SEO)
• Google Search Ads 360 for managing search campaigns

With GA4, you can collect data for all these tools without involving additional tags. Easy enrichment with additional user information and modeling increases the quality of your data.

GA4 continuously monitors your data and alerts you to unusual developments. The user interface will inform you if it senses a sudden drop in the number of users in a channel or an increase in revenue.

Analytics also calculates the probabilities for certain actions. How likely will a user make a purchase or use your app multiple times? Thus, not only can you see what happened on your offers in the past, you can also take a (brief) look into the future.

Building up your own data pool for your company and your offers is therefore of central importance. Google Analytics 4 cannot (and must not) cover all areas of application completely; however, it can serve as a basis for connecting other systems with your own data.

The User’s Path in the Customer Journey

Users use multiple devices to visit an online offering. For many users, the smartphone is the first and always available point of entry. Any website can be accessed via a smartphone browser.

You can also access the website on a PC or Mac using a browser, but both browsers are independent units. An analytics tool cannot initially recognize when the same users are using different devices.

The problem becomes even more fragmented if you also offer an app that a user can install with its own exclusive online offerings. An app is particularly popular for stores, but also for service offerings in addition to the website. These apps in turn use their own identifiers to identify a user, which makes it difficult to track the customer journey of any given user. The customer journey describes the path taken by a user via multiple contact points with an offer. Google Analytics 4 provides a number of modules for the analysis of such distributed journeys, as shown in below figure.

Tracking a User’s Journey Across Devices

GA4 can collect data from different devices and combine them in a report, as shown in Figure above. Within a GA4 property, user activities from both websites and an app can be collected and analyzed in a common user interface, which is referred to as cross-platform. This integration is an important milestone because previous versions of Google Analytics could only collect this data in separate pools and couldn’t mix them. Even the basic design of GA4 is device independent: All methods and all data structures are the same, regardless of the platform from which the data is collected.

To recognize users on different devices, GA4 provides the option of including your own user IDs in the tracking code. For this purpose, you’ll transfer a unique user ID to GA4 in your tracking requests. GA4 usually generates such an identifier automatically and stores it with a user as a cookie. However, if you enter an identifier, this value will be used as the basis for later calculations.

This identifier must, of course, be the same on all devices or offers so that GA4 can link the different activities together with a specific user. For example, a name, an email address, or a customer number that your users must enter when they log in to your website or app is suitable to serve as an identifier.

Note, however, that data privacy and user expectations mean that not every marketing system is allowed to collect all data itself. For more and more activities, you’ll connect ad hoc to different systems, whereby certain legal requirements must be met (e.g., links via encrypted identifiers instead of in plain text).

Data Privacy and Cookies

Maybe you’ve came across European Union (EU)’s General Data Protection Regulation (GDPR) in the past, which has led to a number of new requirements for the measurement of online activities. While the regulation was initially met with opposition, especially outside of Europe, the trend towards more control and protection of user data has now spread worldwide. This trend has led to two developments, as shown in figure below.

Protection of User Data through Regulations and Technology

Legal Regulations

In addition to the GDPR, other regulations worldwide deal with users’ control over their data. One example is the California Customer Privacy Act (CCPA). All these regulations require certain standards for data collection, especially the right to object to the collection of data for profiling purposes.

By now, many users should be familiar with the request to enter user data when visiting a website or starting an app for the first time, as shown in Figure below.

From an analysis perspective, opt-outs (i.e., when a user refuses data collection) can lead to an incomplete picture, as not every user action is collected. In addition, these approval rates sometimes differ massively, depending on the website’s offerings and the channel through which a user arrived.

Request for Consent to Data Collection

With the Digital Markets Act (DMA) of 2024, the EU mandated additional rules and requirements for particularly large providers such as Google. The DMA has thus resulted in several requirements that also relate to the collection and consolidation of user data.

To meet these new requirements, Google has made consent mode version 2 mandatory for data collection with Google tags, among other things. This requirement allows Google to transmit a user’s selected consent for each measurement call instead of generally assuming this consent as before.

Technical Limitations

The protection of personal data has become more important in the public eye. A few years ago, most people were unaware of what was being collected about them online and how this was happening, but interest in controlling one’s own data has grown, especially in the US.

Even if the motivations of the US and the EU differ, strong demand has inspired various suppliers to address this need as an added value for their products.

With the Intelligent Tracking Prevention (ITP) protocol, Apple introduced a technology in its Safari browser that massively restricts or prevents the use of cookies. All major browsers have now introduced privacy functions that more or less restrict the collection of user data.

Apple’s restrictive approach also applies to apps, prohibiting a number of data collection methods that were common practice a few years ago. These technical measures primarily target ad services (i.e., the display of advertisements to users) after they have visited a certain page or content. Nevertheless, analytics tools are also affected because some of the same technology is used. In contrast to the legal regulations, data collection is not completely prevented in these cases, but data of varying quality is available depending on the user’s system.

Based on recent developments, some predictions for the near future with regard to the analysis of user data include the following:

1. Cookies and comparable technical identifiers will continue to become less widespread and less important. Their use will be legally or technically regulated.
2. Companies that collect user data will work more with anonymized and aggregated data.
3. The clear (individual) measurement of actions and conversions will decrease.

These regulations and technical measures mean that your analytics system may receive user data in different quality levels or does not receive data at all. However, Google Analytics was originally developed for a world in which almost all data could be collected for all users. Handling data of different quality levels was less of a problem.

In GA4, Google wants to meet this challenge with modeling. In modeling, “missing” data is extrapolated on the basis of the data from measured users (i.e., the people who have given their consent).

This consent mode represents an additional modified method of data collection. User actions are recorded without cookies or other user identifiers and, according to Google, are therefore compliant with data protection regulations even without the consent of an individual user.

Server-side tagging will be another building block for future data collection. In this context, you’ll operate your own tracking server, which accepts your users’ data and forwards it to various marketing services such as Google Analytics. 

Taking Data Privacy Requirements into Account

Concern over data privacy has accompanied Google Analytics since its launch, and privacy has been the focus of authorities and data protection officers ever since. Regulations like GDPR generally regulate the processing of personal data for both private and public operators.

GA4 implements many legally required settings and specifications by default—that is, without the need for configuration during the setup or operation of a property. First, you should look at the data privacy requirements for the use of Google Analytics, especially the following topics:

1. Obtaining consent
2. Enabling user objections
3. Customizing your privacy policy
4. Anonymizing the IP addresses of users
5. Determining the retention period for data
6. Concluding a contract for order processing
7. Naming a contact person
8. Deleting non-compliant data that has been collected

Obtaining Consent

GA4 collects the individual actions of users on a website or in an app. The tool then links the actions using a unique identifier that each user receives from tracking. For this purpose, GA4 uses cookies or device IDs and combines data to create a user profile. This profiling process is one of the reasons that consent is required to track a user.

When you access almost any website, a window or consent box appears in the middle or at the edge of your browser. Generally, a user can choose between two or more setting options, as shown in figure below. The query window is sometimes also referred to as the cookie box or cookie consent, as cookies can play an important role in data privacy.

Requesting User Consent to Data Collection

A consent manager (such as Usercentrics or Onetrust) is often used for the display and administration of consent notices, handling the display of the consent query, the storage of user selections, and the forwarding of user selections to other services.

Enabling Objection

A consent box asks for permission to use certain cookies for tracking. At the same time, the consent box should give the user the opportunity to object (i.e., to refuse certain services and cookies). Cookies that are essential for the operation of the website are excluded. These cookies are often listed as necessary or required in a consent box.

Informing and Adapting the Privacy Policy

You should inform all users who visit your website that you are collecting interaction data with Google Analytics. Some consent managers provide text modules that you only need to select in the configuration. Users can then view all the information in the consent window, as shown in figure below.

Description of Individual Services in the Consent Box

You should also list all relevant services on a separate page on data privacy. This page must be easy to find and access anywhere on your website. Many websites online can help you create a privacy policy.

Anonymizing the IP Addresses of Users

An IP address is considered personal data and is therefore highly relevant in terms of data privacy. While adjustments to tracking codes were still necessary in UA to shorten and thus anonymize an IP address, IP addresses are always shortened in GA4. On European servers, the IP addresses of users are only used to determine user location down to the city level. Only this location information is transmitted and stored. The full user IP address is not saved by GA4.

Defining the Retention Period of Data

In property management, you can specify how long Google should retain event data linked to cookies, to user IDs, or to advertising IDs, as shown in figure below. In concrete terms, event data is aggregated after the specified time has elapsed, which in turn means you lose the ability to access individual users, which may still be necessary for more complex segmentation, for example.

Setting the Retention Period in Google Analytics

You can choose between 2 and 14 months for data retention. Some online resources recommend a retention period of 2 months, but no requirement mandates that you keep the data for such a short period of time only. You can therefore leave this setting at 14 months.

The most frequently used reports such as pages, sources and more remain available and usable as usual with aggregated data even after this time. However, you’ll be limited when trying to segment your reports.

The retention period for user data is based on the time that has passed since the last collected events and can be assigned in two ways:

• If the Reset user data on new activity setting is selected, and a user returns to your website or opens the app within the set time period (e.g., 14 months), this new visit is considered the new starting point for the retention period. The user data can therefore be stored for as long as the user returns to the website within the retention period.
• If the setting is switched off, the first measured event of a user is used as the starting point. Once the retention period has expired, this user’s data is aggregated, regardless of how often they have opened the website or app.

Concluding a Contract for Order Processing

When creating a new Google Analytics account, you must first agree to the terms of use and thus also to the data processing conditions, You can then view the confirmation and the date of consent at any time in the account.

Appointing a Contact Person

You can also store the primary contact for data privacy issues in your company and the data protection officer in your Google Analytics account settings. For this task, click on Manage details about the Data Processing Amendment.

You’ll then be taken to the administration page within the marketing platform, where you can store contact data centrally for a whole range of Google products.

You can create contacts for different roles:

• Primary contact
• Data protection officer
• Authorized representative for the European Economic Area

You need at least one primary contact that Google can contact in the event of queries or issues. You can enter several people, but one contact person can also take on multiple roles.

Deleting Non-Compliant Collected Data

If you’ve collected usage data without first implementing all requirements, this data is considered incorrectly collected under data protection laws. Thus, this data may not be used and must be deleted.

GA4 provides several options for deleting data from reports. You can delete individual users as well as entire events of a user or only specific parts of these events. The deletion process can also be limited to a specific time period. 

AI in Web Analytics

With the launch of ChatGPT, the term artificial intelligence (AI) has become known on a large scale. Google has long been using machine learning in its tools such as Google Analytics and Google Ads as well as in general search functions to analyze data, discover trends, and make predictions. Added together, these previous operations are now also referred to as AI. Google Analytics 4 already uses AI for some functions.

Detecting Anomalies

GA4 detects unusual fluctuations in traffic or other metrics. Using data collected in the past, the system creates a forecast and compares it with the actual measured data, as shown in figure below.

Anomaly Detected in Daily Traffic

You can use this anomaly detection in your own data analyses in GA4 and also set the sensitivity and the training period.

Forecasts and Predictions

You can define segments or audiences to analyze specific user groups, as shown in figure below. Users can be selected according to specific criteria, such as the source or the content accessed. If your database is large enough, GA4 also provides predictions for specific users. The future behavior of users is based on the data measured to date. These predictions can be particularly useful for online stores.

User Groups with Purchase and Revenue Probability

Modeling Traffic and Conversions

Due to data privacy requirements and the various privacy functions, for example, from Apple, you may no longer receive any data for mist users on your website. These users are still active and, for example, carry out registrations or buy products.

Google Analytics uses AI-supported modeling to make these “lost” users visible. Based on the behaviors of fully measured users and other signals, GA4 can try to reconstruct the lost data.

AI as a Natural Language Interface

An impressive feature of services like ChatGPT or Gemini is the ability for users to interact in a natural language. You can freely formulate questions and instructions through speech, as if you were talking to a colleague. The system then responds in a kind of “spoken” text. Users don’t need to learn how to interact with an often complex user interface.

Microsoft is already a step ahead with its analytics service called Clarity: The Microsoft AI service Copilot is already integrated into the interface. You can ask the AI about the collected data and receive additional analyses and explanations, as shown in bigure below.

Chatting with AI about Analytics Data in Clarity

That Google integrates a comparable feature into GA4 is only a matter of time 

Analyzing Data Exports Using ChatGPT

You can also analyze analytics data without direct integration. For example, ChatGPT allows you to load tables exported as comma-separated values (CSV) files and then processes them further, as shown in figure below. You can then make queries on this data.

Analyzing Exported GA4 Data in ChatGPT

In addition, you can also create charts from this uploaded data.

This procedure with exports still has some limitations with ChatGPT, both in terms of the amount of data and the scope of the queries that are processed. However, developments in this area are ongoing, and other services do not necessarily operate under the same framework conditions.

When using ChatGPT or a comparable AI for your analyses, note the use of data for training purposes! With ChatGPT, for example, you must deactivate the use of data to improve the models yourself. For this reason, you should consider in advance what data you want to make available to an AI.

AI as a Future Component

AI systems provide great potential in analytics systems to facilitate the application and interpretation of data. AI can improve the quality of analyses and simplify interactions with large datasets. Further developments are certainly forthcoming.

However, even machine learning and artificial intelligence cannot create analyses out of thin air. A certain amount of clean data must first be available before these capabilities can play to their strengths. You’re therefore still required to first get a system like Google Analytics up and running and feed it data so that an AI system can work on the data.

Creating a Tracking Concept

Prior to installing and setting up an analytics tool such as GA4, you should first consider what you want to analyze in your offering, regardless of whether your focus is on websites or apps. You can set out this objective in a tracking concept, which will subsequently also include individual tracking and settings. Once implemented, the tracking concept becomes your tracking documentation, which can be continuously adapted and supplemented.

Start with two questions to identify items that belong in your concept:

1. What can users do on my website?
2. What should users do on my website?

The two approaches complement each other, and the order in which you tackle these questions is up to you.

Recording Action Items

For the first item, “What can users do on my website?” you should describe at which points exactly users can perform certain actions while on your website or app: perhaps, when a specific page is viewed, when specific elements are clicked, or when a form is submitted. You should list these action items without regard to how they can be technically implemented.

Let’s use an agency website as an example. As summarized below, users can perform the following actions on this site:

• Retrieve information on benefits and services
• Contact us via a form
• Contact us by clicking on an email address or phone number
• Subscribe to the newsletter
• Register for a webinar
• Play a recorded webinar in the video player
• Read blog posts
• Download PDF files
• Apply for a job

Action Items on the Agency Website

In the next step, you must record what exactly happens during each action. In the “getting into contact” example, users submit a form. Do they see an overlay? Do they land on a new page? Is this page only accessible to users who have submitted the contact form? As shown below, this description will later help you recognize whether these actions are already recorded by GA4 in reports or whether you need individual solutions.

Definition of Action Items

Finally, for each action item, you must consider whether users provide the information that you want to include in the report as well, for example, the value of a form field or the name of a link. You should specify which data from the user action you want to find in the tracking concept.

Defining Conversions

For the second question, you should list the actions users should perform on your website. These actions are referred to as conversions in many tools, especially when marketing measures are evaluated.

Conversions are the desired actions that a user performs on your website or in your app. Conversions are crucial for measuring the success of online marketing campaigns and exist as two main types:

• Macro conversions are the big, final actions you expect from your users, such as a purchase or lead generation. These conversions are often targets towards which marketing efforts are directed and are considered the most important indicators of a campaign’s success.
• Micro conversions, on the other hand, are smaller actions that can later result in a macro conversion. A smaller action can include, for example, watching a product video, adding an item to the shopping cart, or subscribing to a newsletter. Although often overlooked, micro conversions are extremely valuable because they provide insights into user behavior and help you better understand the customer journey.

Many companies focus exclusively on macroconversions to the detriment of micro conversions. However, imbalance can lead to an incomplete picture of user actions. Micro conversions provide valuable data for optimizing marketing strategies and increasing the efficiency of campaigns. They enable you to better understand your audience and your target content more effectively.

Some examples of the interplay of micro and macro conversions from different industries include the following:

E-commerce

A user visits a product page, looks at the product images, reads the reviews, and finally adds the item to the shopping cart. These steps are all micro conversions that result in the final macro conversion, the purchase.

Business-to-business (B2B)

Users visit a company’s website, read blog articles, watch webinars, and download white papers. These micro conversions show the users’ interest and ultimately lead to a macro conversion such as a contact request or a purchase.

Tourism

A user visits a travel website, looks at various travel offers, reads customer reviews, and finally books a trip. The individual steps, such as viewing the offers and reading the reviews, are micro conversions that result in the final booking (the macro conversion).

Automotive industry

A user visits a car website, configures a car, looks at technical data, and finally arranges a test drive. These steps are micro conversions that lead to the final macro conversion, the test drive booking.

You should consider both types of conversions in your tracking concept from the start. Likely, you’ll notice overlaps among the action items from the first question. Conversions are often important actions users can perform on your website.

In the past, Google Analytics used the term conversion in reports but has since replaced it with key term.

Documentation and Online Help

We hope this post provides you comprehensive insights into Google Analytics. To further deepen this knowledge, we want to recommend some additional resources.

Official Online Documentation

You can access the official developer documentation for GA4 at https://developers.google.com/analytics. At this site, you’ll find the technical descriptions of tracking codes and integrations.

Even if you’re not a developer, this website is worth stopping by: From here, Google will direct you to various resources and support articles that also describe the use of GA4 and various application scenarios.

Skillshop from Google

At https://skillshop.withgoogle.com, you’ll find courses and content provided by Google on the various marketing tools. You need to register once (free of charge) and can then choose from various subject areas.

In Skillshop, for example, you’ll find content on the following solutions:

• Google Analytics
• Google Ads
• Google My Business (business profiles for businesses, for example, in Google Maps)

Multiple courses are available for each tool, consisting of texts, videos, and questions.

You can broadcast your Google Analytics skills through certification. The exam consists of multiple-choice questions that you must answer within a given timeframe.

In this first post of the series, you learned about the basic principles and structure of Google Analytics. GA4 focuses on user actions and measures them as events. Users can be measured in websites and apps, and their movements can be brought into a coherent customer journey. By implementing a tracking concept, you can determine measuring points and define important actions for additional settings.

We also briefly covered other components that are part of a digital marketing setup and explored data privacy requirements you must consider when using Google Analytics.

In future posts, you’ll create and configure your own Google Analytics properties to measure.