A Beginner’s Guide to GA4

Building custom report cards

If you want to have quick access to specific data reports, you can create custom report cards that are accessible from the left-hand navigation. To do this, go to ‘Library’ at the bottom, and choose the report topic you want to focus on. You can then make edits to the report card so it’s showing what you want to see and save the report to make it easily accessible.
You can also create new collections in this section too, which can house all your custom report cards.

Identity spaces

Identity spaces are how Google maps user journeys. By using multiple identity spaces, Google can de-duplicate users and get a more accurate account of each particular user’s journey, even if multiple devices have been utilised on different days.
A single identity space means that one user would come up as two separate users if visiting your site on mobile, then desktop, even though it’s the same person. By utilising multiple identity spaces, you get more accurate data around how many new users your site received, or how many events or conversions were triggered. So, whilst we’re on this, what are the identity spaces that Google now uses?

Using the search tool

Did you know you can use the search bar to look for instant answers as well as reports, insights, and property configuration information? As well as help of course.
Try typing something like ‘conversions last week from the United Kingdom’, and GA4 will provide instant answers, saving you the time of going through a report to find the data.
You can also compare data, try ‘new users in September 2022 compared to last year’.

Integrating business data with GA4 data to add even more insight

Path exploration

The path exploration template shows you your users’ journeys after they landed on your website. The session_start column indicates how many users landed somewhere on your site within the selected date range. The second column shows you how many of those went on to view another page. If in Step+2 you click the dropdown and select page title and screen name, you’ll start to see a breakdown of the number of users who went to certain pages within your site. By clicking on these pages, you can drill down further to progress the user journeys.

Segment overlap

The segment overlap template allows you to compare user segments and see how they overlap with whatever breakdown data you choose. You can choose up to three comparisons. For example, if you’re an e-commerce site, you may want to look at organic traffic against purchasers to see how the audience data compares. You can explore specific channels or look at data such as age ranges. We recommend having a play around with different data sets, or if you already know what you want to see, get stuck in!

Funnel exploration

Funnels are most useful for e-commerce businesses, as essentially this report is showing you what percentage of customers made it through the funnel and how many abandoned. It can also be useful for looking at other conversion metrics you may have such as downloading a pdf. You’ll need to have these set up in your conversions before you build this report.

User explorer

If you’re acquainted with UA, this report is likely to be familiar. The table shows you which individual users generated how much revenue, and if you click on the user, you can explore their journey at a top level. You can play around with the different values and can see which users have the highest average order value within a selected time frame.

So, we’ve mentioned the landing page report, but how can you use Explore to create it?

Free-form reports

We recommend using the free-form report template for a landing page report. This is because this template is a custom report and allows you to create dynamic tables, applying your chosen dimensions and metrics to showcase your data. Each report has the same basic set up in this section, so once you’ve got the hang of one, you’re all set. You have two columns on the left, the first, titled ‘variables’ gives you options to change the name of the report, date range, segments, dimensions, parameters and metrics. You’ll need to look at these first before moving onto the second column, titled ‘tab settings’. This one gives you various techniques fields, alongside segment comparisons, breakdowns, values and filters. You can add as many tabs as you like to create your data table. You can drag and drop the variables from the first column into the second.

How to create a landing page report

1. Firstly, within the ‘variables’ column on the left, clear the dimensions section and add in ‘landing page’ (you can use the search at the top to look for it) and import. Drag and drop the dimension from the variables column (column 1), to and add it to the row in the tab settings column (column 2).
2. Under metrics, add ‘sessions’ and ‘active users’. Drag and drop to pop them in the metrics section of column 2.
3. If you want to separate the traffic sources, for example you just want to look at organic traffic, you need to add a new segment. In column 1, click the + button>select user segment>traffic source>first user medium>add filter>contains ‘organic’. You can do the same for things like paid traffic etc. Before you click apply, name your segment so you know what you’ve chosen.

Using the Explore feature in GA4

Using reports in GA4

To access your business’ reports, it’s as simple as navigating to the reports tab. Here, you’ll be able to quickly check metrics, or dive deeper into specific reports you want to know more about.
You have an overview report, which is a snapshot of a larger report. You can amend things like the date range, and the dimensions and metrics, or click on the card for more information.

There’s a Realtime report too, the same as UA. GA4 has also got a selection of default reports which you can access via the left-hand panel, and these cover things like retention and engagement. If you want to look at data like page views and the number of users etc, you need to go to
engagement > pages and screens.

Step-by-step GA4 property creation

You can follow these steps below to create a property:

• Create a Google account or sign in and go to account settings
• Enter the info for a new property – it will automatically be a GA4 one from now on
• Choose which platforms you have for your data streams and enter the relevant information. For website data, keep ‘enhanced measurement’ on so you’ll still collect data such as pageviews, scrolling and outbound link clicks – you can turn it off if you like once you’re set up
• To enable data collection for your website, it will need to have the correct tags added. Google has guides on how to do this for websites and apps here.

What if I already have tags added from my UA property?

You can set it up to run alongside UA, but it will depend on how you’ve already tagged your site as to what you do next. You’ll want this guide if you’ve used Google Tag Manager, gtag.js, or analytics.js.

Once you’ve set up your new GA4 property, login and check everything is working – a good place to check this is through the Realtime function.

How does GA4 measure data?

In UA, data is measured through user sessions. In GA4, it’s measured via events instead. Don’t worry, you can still report on sessions, it’s only changed as GA4 is able to collect data from both your apps and websites and combine it. It’s worth noting though that because the basis of reporting in GA4 is through events and not sessions, you can no longer create session-scoped dimensions and metrics in GA4. You can still create custom dimensions and metrics though if you want and scope by user or event. Learn how to do this here.

Any user action on your website is recorded as an event, and GA4 has pre-selected several events which are automatically collected, such as the first time someone visits your website or downloads your app. You can also use the enhanced measurement feature to track more events without having to change any code. If you have certain events you want to record which aren’t already applied, such as visits to a particular page on your site, you can create new events through the ‘all events’ tab. This video gives you a handy walkthrough on how to create a new event.

Alongside events, you can access data around specific user properties, such as location, or age; you can set specific event parameters to allow a deeper dive into the actions users took on your website, and you can set certain events as conversions too. You may want to set an event as a conversion if you have pdfs available to download on your website, or if a user makes a purchase. We recommend only setting conversions on the more important events.

GA4 Reporting overview

A Beginner’s Guide to GA4

Google has/is rolling out a new version of Google Analytics, called GA4. With plans to discontinue Universal Analytics (UA) in June 2023, it’s a good idea to get up to speed with all the new features. We’ve created this whitepaper to give you a basic understanding of how it works, what it does and where you can find everything you need, so that when it does come to changeover day, you’re in the best position possible to continue with effective reporting on your website.

Overview of the new key features of GA4

• It collects both website and app data at the same time on the same platform, as opposed to having UA and Firebase
• It now incorporates machine learning to make predictions
• It de-duplicates interactions from users (for example a user visits from a mobile and then from their desktop), to better understand the customer journey
• It meets the updated restrictions around user privacy without sacrificing the quality of data and reports
• It works to an event-based data model as opposed to a session-based one, processing each user interaction as a standalone event. This means you can see more specific information about what a user did – such as the title of a page they visited
• User identifiers are used to map journeys more effectively
• There are more options for creating audiences and therefore better segmenting
• New exploration tool allows for more discovery around funnels and user paths
• You can export data and save it in the cloud and combine it with other data on BigQuery.

What other programs can you connect to GA4?

• Google Ads
• BigQuery Export
• Display & Video 360
• Firebase
• Google Ad Manager
• Google Merchant Center
• Google Optimize
• Salesforce Marketing Cloud reporting
• Search Console
• Play
• Analytics Search Ads 360

You can find out how to set up integration for all these programs here.

Summary

We’ve come to the end of our Beginner’s Guide to GA4, and we hope you’ve found it a useful tool. We’ve been through the four main sections you can find in GA4: Reports, Explore, Advertising and Configure, but with lots of new features and functionalities, it’s a big learning curve even for seasoned Google Analytics users. It’s also worth noting that GA4 is still undergoing various updates, so certain reports or naming conventions may change as we get closer to June 2023. You can keep an eye on all updates using this link. If you have any unanswered questions or need further help with certain areas, pay a visit to our Koozai TV to browse various GA4 quick videos, or feel free to get in contact with us, we’d be more than happy to help.

Managing data collection in GA4

You’ll be aware that in recent years there have been some considerable changes as to how businesses use and store customer data. The 2018 Data Protection Act introduced a specific set of guidelines which companies were required to adhere to when it came to personal data. Due to these new(ish) regulations, many companies had to revisit how they were managing data.

It's important to ensure you’re meeting your customers’ privacy expectations, so GA4 has a number of controls in place so you can do just that:

• Disable user data – partially or completely
• IP addresses – GA4 doesn’t log or store IP addresses as standard
• Data retention period – set timers as to how long data is stored for
• Consent mode – dynamic adaptation as to the consent status of users.

For more information on how to set these privacy controls, go here.

Another option in GA4 is to request data deletion. This can be done on an individual user basis or a whole load of data in one go. There are options to request data to be removed from the servers, or you can delete a single user’s data or a property if you have editorial access to the account.

How to delete single user data

Head to the Explore section and select the User Explorer template. Create a report, find the user you wish to delete, click on them and then select the trash can.

How to delete a property

Go to the admin section and find the property you want to delete. Open property settings and then it’s as easy as selecting it and then clicking ‘move to trash can’.

Cohort exploration

Another report which is currently available in UA, the cohorts report allows you to look at the behaviour of groups of users over certain time periods. The below example shows cohorts across various date ranges who after the first touch went on to view web pages across 4 weeks. We’ve then added a comparison to see the difference between direct traffic and Google traffic.

User lifetime

The user lifetime report is only useful if you have your e-commerce tracking set up properly. This is because without it, Google isn’t able to access the right data to calculate the lifetime values of customers. This report allows you to analyse behaviour over time, seeing what medium or campaign drove the highest value customers, and when these users last engaged with your site or made a purchase.

Using the Configure section in GA4

Custom definitions

Custom definitions are also available in the Configure section. This is where you can set up/find any custom metrics and dimensions you’ve already set up. Although the pre-defined dimensions and metrics GA4 already has usually include most of what you’ll need (there are 159 currently), you may want to track something specific which does require a custom definition. For example, if you want to track a product ID, or perhaps the keywords being typed into your search bar, you’ll need to set these up.

Debug view

This is similar to the preview mode in Google Tag Manager in that you can view the events as they fire from a test user, helping you see what is and isn't working.

Depending on your overall setup you may have to download a chrome extension or set up a custom parameter, but if you’re using GTM, the preview mode automatically adds a parameter to send the browser info to the Debug mode. There can be a slight delay in the data coming through, similar to the Realtime views, but this method of debugging is much more reliable and user friendly than previous Analytics methods.

Using the Advertising feature

The advertising section in GA4 is where you’ll get your hands on the channels that drive the most events and conversions. We’ve previously explained what events and conversions are, but to add to this, GA4 also applies ‘modeled conversions’, which uses machine learning to predict online conversions in a more privacy-protected online world. Applying modeled conversions means you can still access accurate reporting on conversions, just that users aren’t identified, and Google uses historical data and other factors to predict the likelihood of a conversion.

If you’re concerned about Google using machine learning to predict conversions, you’re not alone. If it can’t directly track conversions, how can this data still be reliable? Google’s answer to this is through the following:

• Checking for accuracy and communicating changes – uses machine learning best practices to inform and tune the models
• Maintaining rigorous reporting – if there isn’t enough traffic or a high enough confidence of quality, modeled conversions aren’t reported
• Customised for your business – the more general modeling algorithm is applied separately to reflect your unique business and customer behaviour
• Individual users – Google makes no attempt to identify users, instead aggregating data from things like device type, historical data and the like, to predict how likely a conversion is.

Model comparison reports

These reports allow you to directly compare how different attribution models are performing. All you need to do is choose your date range, select the models you want to look at from the top left to see where credit is being attributed across each one. A good set to compare is first vs last click to see which campaigns need to work a bit harder.

Conversion path reports

Conversion path reports allow you to explore the different touchpoints users go through on their path to conversion. The report automatically shows early, mid, and late touchpoints, and whether the traffic came from organic, direct, paid etc. channels. The table also allows you to explore how many days and touchpoints there were to conversion, so you can see how effective each channel is. For example, the below screenshot shows that paid search contributed to 73 conversions, which took an average of 2.5 days to achieve, but there was only a single touchpoint to conversion. Knowing the most effective paths to conversion can help you decide how to shape elements of your future digital marketing strategy.

Attributing conversions – you decide!

When a customer completes a conversion, whether that’s purchasing a product or service, downloading a pdf or filling in a contact form, it can be an important aspect for many businesses to determine where credit for that conversion should be attributed to. Historically, credit has been attributed to the last interaction your customer had with your site, but what if there was another way?

GA4 allows for multiple attribution options, so you can choose where credit is given, depending on what works best for your business. Here are the different options that GA4 has available:

• Last click – where 100% of the credit goes to the last channel where the customer clicked through from. So, this could be direct, organic search, or an ad.
• First click – 100% of the credit goes to the first channel.
• Linear – all channels get equal credit for a conversion.
• Position-based - 40% credit to the first and last interaction, remaining 20% credit is allocated evenly to channels in between.
• Time decay – channels used closer in time to the conversion get more credit than ones at the start of the customer’s journey.
• Data-driven – your account data is used to calculate where credit is best allocated.
• Ads-preferred – you can choose to favour ads and give 100% credit to the ad if it was part of the user’s journey to conversion.

Connecting GA4 with Google Ads

If you’re already an accomplished Google Ads user, we imagine you understand the benefits of connecting your account to Google Analytics. However, if you’re relatively new to the world of Google Ads and want to know more about what sort of insights you can gather by connecting the two, keep reading.

Although you can get decent reporting for your ads through the Google Ads platform, if you want more in-depth data or have some different conversions, it’s time to connect with GA4. You can do this through the admin section, choosing Google Ads linking. Once you’ve linked your account, give it roughly a day and then you’ll be able to see data pulling through in GA4.

How to view Google Ads data

Head into reports, and on the ‘what are your top campaigns?’ card you’ll be able to see your Google Ads traffic listed as CPC (when you change ‘session default channel grouping’ to ‘sessions medium’. If you go to acquisition>overview you can see a report titled ‘sessions by session Google Ads campaign’. This report is dedicated to your Google Ads campaigns. You can click this for further information and change up the dimension too (click session campaign in the top left corner of the table underneath the search bar) so you can look at things like keywords, query, and network type.

Google Ads conversions

It's highly recommended to import Google Analytics conversions into your Google Ads account. This means you can track events, such as sales, and see which of your Google Ads campaigns contributed to that event. You can even import the revenue generated from a sale and optimise towards this. The same process applies with GA4 and UA, you'll need to link your accounts and import the conversion goals from GA4 into Google Ads.

Bidding

Once you’ve imported your goals into Google Ads, you can optimise your campaigns towards driving more of what matters to your business. If you're still using manual bidding, you can review metrics such as CPA/ROAS and optimise keyword/audience bids to drive more traffic through the areas with good performance. If you're using automated bidding, Google Ads' algorithm will aim to get the most from your campaigns. Choosing the maximise conversions bidding strategy will tell Google to get more of your conversion goal within your budget. You can also tell Google to maximise conversion value (revenue) if you have this data.