A Beginner’s Guide to GA4

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    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?

    User-ID – If your website has a login function where customers can create an account, you can assign anonymous IDs to your users and measure their journeys more accurately. This is done through the admin section in GA4, you can find out how to set it up here.

    Google Signals – This relates to users who are signed into their Google account and have consented to sharing information.

    Device-ID – This one is automatic and comes from 1st-party cookies through the user’s browser, therefore requiring no setup.

    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

    To make your data even more significant, you may have additional data specific to your business that you want to be visible within the GA4 platform. For example, you may have metrics within your CRM or CMS which would be valuable to compare to GA4 data. Alternatively, you might want to widen the amount of data being collected to provide even more in-depth insights. Here are the ways that you can broaden your data:

    Using events

    Take a look at the events you’re currently tracking – you should see things like page views, first visits and similar basic events. These are automatically incorporated when you connect GA4 to your website. To broaden your data visibility, you might want to track specific pages or actions (as previously mentioned in the ‘how does GA4 measure data’ section). We’ve given instructions in this earlier section on how to create your own events.

    Measurement Protocol

    This allows developers to include extra data and collect more interactions from web and app data streams. This then goes through to Google Analytics servers.

    This is useful for larger GA4 properties and those with multiple data streams. The possibilities of joining online and offline behaviour is enticing, but there may be larger developmental costs involved in getting this set up.

    Importing data

    If you have data from things like email marketing campaigns, or item data such as colours and sizes or date of last purchase, these can be added to GA4 and incorporated into your overall data, providing a more in-depth picture of how things are looking. You can do this by:

    1. Go to the admin section
    2. Find data import in the property column
    3. Create a new data source
    4. Select the correct data type
    5. Upload your CSV file containing the additional data
    6. Select where you want the data to be mapped to within GA4. Once you’re happy with the data fields and titles etc, you can hit import.

    If in future you want to add more data into the same import, you can do this by clicking ‘import now’ in the row for an existing data source. Just make sure that your fields are the same as the original file, so it matches up properly.


    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.

    TIP: You can’t edit the rows in this exploration, they’re pre-set to App-instance ID and Stream Name. If you try and amend them, you’ll find the data sheet returns blank.


    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.
    TIP: It’s important to get your head around any new GA4 terminology so you know what to look for when building your reports.


    Using the Explore feature in GA4

    The Explore section allows you to analyse data more flexibly. You can drag, drop, filter, sort and segment dimensions and metrics to build the exact report you want before exporting. It’s designed to help you understand your data better. There are different types of report templates available in this section:

    • Free form exploration – drag and drop the precise metrics and dimensions you’re interested in to visualise the data
    • Funnel exploration – see how your users navigate your site or app to achieve a conversion or key task. See where they enter the funnel and drop off
    • Path exploration – a free-flowing version of funnel exploration – see where users went. Define specific paths you want to explore in more detail
    • Segment overlap – compare user segments, isolate specific audiences, create new segments
    • User exploration – look at individual user behaviour and learn more about their activities
    • Cohort exploration – discover more about the behaviour of groups of users who have something in common (have triggered the same event) and belong to the same ‘cohort’.

    The Explore section is designed to allow you to go beyond the standard reports and dig deeper into your website data. It’s worth noting that a lot of the standard reports from UA are no longer available in GA4, so you’ll need to build them. For example, one we use a lot that’s no longer available is the landing page report.

    TIP: Before building any reports within Explore, it’s a good idea to head to the Configure section and check on your events. If there’s something you want to report on and it’s not already added as an event, now’s a good time to do it so you can include it when you’re ready to build that report.


    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.

    Did you know?

    Bounce rate is also a thing of the past in GA4. Instead, Google is encouraging businesses to look at the opposite – the engaged sessions – users who stayed on a site for longer than 10 seconds, looked at two or more screen views or completed a conversion.

    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.

    TIP: Use the add comparison tool at the top to compare different reports.


    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.

    TIP: you can only have up to 30 conversions on any one property.


    GA4 Reporting overview

    We’re sure you’ll agree that getting your hands on interesting data insights is what it’s all about? So, we thought the best place to start was to just give you a super quick overview of what you can find at a quick glance on the Reporting tab. Don’t worry, much more detail is coming later in this whitepaper.

    We thought you’d like to know upfront that GA4 now provides simplified reporting which is available on summary cards. These provide insight on a single topic such as user demographics, and you can click on the card to drill down into more in-depth reporting in that area. As with UA, the Realtime tab allows you to monitor what’s happening on your site right now, the difference with GA4 being that you can compare users side by side in actual time and create new segments. But more about reporting later on, we want to take it right back to the start and look at GA4 properties first.

    How to create a GA4 property

    As briefly mentioned in the new key features overview, GA4 compares web data with app data, so to get things off to the right start, it’s important to make sure that you set up and structure your GA4 properties properly, to get the most out of the available data.

    How to structure a GA4 property properly

    The below image shows you how best to structure your property. If you have both a website and an app, you’ll want separate data streams for each (as pictured), but they will still sit under the same GA4 property. If your business has both B2C and B2B functions and let’s say has an app for each, you’ll want two properties, one for the B2C function and another for the B2B. This means you can see which data refers to which channel. Essentially, you want a data stream for each way users interact with your business – one for each website, one for an iOS app and one for an android app.

    TIP: If you’re already using UA and want to start with GA4, create a new property under GA4 to start collecting data and your UA account will continue running as normal in the background until switchover day.

    TIP: If your company has different regions or different brands under its parent company (that doesn’t require to be analysed together), you’ll want to set up a separate property for each.


    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.



    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’.

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    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.

    TIP: not all variations of segments, dimensions and metrics work together – if you find the data doesn’t match up properly, no data will pull through, and you’ll need to relook at what you’re trying to pull through.


    Using the Configure section in GA4

    Events and conversions

    We’ve already briefly touched on events and linked to a video on how to create new ones in the previous section. The Configure section is where you’ll find all your existing events, see how they’re performing, and it’s where you’re able to add new ones too. If you’re a UA user, it’s worth noting that ‘goals’ are now called ‘conversions’ in GA4, and there’s no distinction between e-commerce anymore, everything is under the same umbrella.

    Conversions are also found in the Configure section. If you want to set a new conversion, you need to create a new event, and then mark it as a conversion to start tracking this data.

    Google’s definition of Events:

    “An event allows you to measure a distinct user interaction on a website or app. For example, loading a page, clicking a link, and completing a purchase are all interactions you can measure with events.”


    You can also explore your audiences in this area of GA4. Predefined audiences include ‘all users’ and ‘purchasers’, but you can add new ones which will show up in the same list. When you create a new audience, you can choose from a custom audience, a set of templates, or a set of predictive audiences.

    If you choose to set up a custom audience, there’s a few things you’ll need to do:

    • Set the scope conditions, so whether it’s across all sessions or a single session/event.
    • When you choose a condition, you’ll also need to specify whether you want static or dynamic evaluation. Static = if your condition was ever true for the user. Dynamic = users are only included in the audience when the condition is true for them. They’re then removed when it’s no longer true. This can be chosen via the ‘at any point in time’ tick box within the condition. You can also choose time periods if you like.
    • Depending on what sort of audience you’re trying to build will determine how many conditions you add, and whether you need to also think about sequences, namely the order in which your chosen conditions must be met.
    • Once you’ve saved your audience, allow 24-48 hours for Google to collect data.

    Explore more detailed information on how to create an audience.

    TIP: You can use audiences to segment and compare your data. For example, you might want to look at users from a specific location and compare their data to other locations.


    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.

    TIP: when creating a custom dimension, you’ll need to create tags in Google Tag Manager too.

    TIP: don’t set up a custom dimension that would have more than 500 unique values per day, as it may negatively affect your reporting.

    Google defines modeled conversions as: “the use of machine learning to measure the impact of marketing efforts when a subset of conversions can’t connect to ad interactions.”

    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.

    TIP: Use the colour coded data in Debug View, with events in blue, conversions in green and user properties in orange.

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    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.


    TIP: Now that GA4 combines data from both website and apps, the data-driven approach for attribution is more powerful.


    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.

    TIP: when you link your Ads account, you’ll only get data from that day onwards, historical data won’t be available.

    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.


    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.

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