The Most In-Depth Google Analytics 4 (GA4) Course for 2023 With Real-world Examples

1. Introduction to The Course: Hi and thank you for joining me on a journey to expand your knowledge of Google Analytics 4 I'm Ziga and I'll be your instructor for the next couple of hours. By the end of this course, you will have a deep understanding on how to use your Google Analytics 4 and how to set up custom and advanced reports based on your business needs. We'll start with the basics like getting to know Google Analytics 4 and its limitations and setting it up on different platforms like WordPress or Shopify. Then we'll dive straight into the ready made reports that answer common questions about how your users. We're interacting with your app or website will also check how to create custom reports and collections. Then we'll talk about advanced reports you can create yourself in the exploration section. This way you'll be able to uncover deep insights in your customers engagement. Along the way I will show you real world examples so you can build your own reports as the course progresses. By the end of the course you will understand all the GA4 reports and how to use them effectively. OK, so who am I and why am I teaching you all this? Well, I've been in digital marketing for over 8 years, and in this time I've launched, managed and mentored over 30 successful crowdfunding campaigns and helped them raise over $7 million. I've spoken at various conferences and marketing events and lectured multiple generations of small business owners on different topics of digital marketing. Currently I'm the head of marketing at the fast growing startup where I use data and analytics daily in my decision making. I've been actively using Google Analytics my whole marketing career and taught multiple people on how to use it effectively. This leaves me in a good position to teach you everything I know. I'm super excited to share my knowledge with you. So let's get started. 2. What Is Google Analytics 4 (GA4) and Why Do You Need It: Imagine going on a well deserved vacation with your family. You decide to drive there in a car as it's only a couple of hours away. But after a few minutes you realise none of your gauges and indicator lights are working. You have no idea how much gas you have left in the tank, how far you have driven, or even how fast you are going. I bet this would make you very anxious and you would stop your car immediately, maybe even cancel your vacation. Yet a lot of online businesses run their operations with poor or nonexisting reporting and analytics strategies. And usually they don't even think about it until it's too late. If you are a business owner or a marketing manager, then data should play a vital role in your day-to-day operations and having the right tool in place to track this data is crucial for the success of your online marketing activities. In this course, we'll talk about one of these tools called Google Analytics 4. This is a web and analytics tool that provides in-depth insights into the performance of your website or app. It allows you to track and understand your customer's behaviour, user experience and measure your marketing activities and business objectives Understanding. how users, visitors and customers use your website or app is essential. Without behaviour data, optimizing your business performance is almost impossible. The key benefit of behavioural metrics is that they provide you with valuable information on what pages get the most traction. And engagement. And if you can understand how users interact with your website or app, you can optimise their journey and make it more sticky. One of the most important insights you can get as a marketing manager is to understand where your users come from. Pinpointing different traffic sources and understanding why and how much traffic comes from each will allow you to plan your budgets and modify your acquisition tactics. It will also help you with the optimization of individual channels like SEO, advertising, or content marketing. A key cornerstone of any analytics tool is reporting. Without reports, you basically fly in the dark and what Google Analytics is really good at is giving you the tools to create custom reports, dashboards and alerts. This way you can track and analyse data based on your company's specific needs. And the best part of all this is that Google Analytics is free, so you can benefit from using it. All this is just scratching the surface, and you'll learn much more in the upcoming course. 3. How to Get The Most Out of This Course: Before we begin, I'd like to share some tips on how to get the most out of this course. 1st it's important to understand the course is divided into various sections, each covering a different topic. This sections include initial GA for setup and installation, best practises and interface overview, pre-made reports and dashboards, advanced custom reports in the Explore section and so on. Each section builds upon the previous one, so it's best to start from the beginning and work your way through the course. However, if you feel that you understand the particular section well, feel free to move on to the next one. If you are new to Google Analytics 4, I strongly suggest you start from the beginning and work your way all the way to the end. This will ensure that you have all the necessary knowledge for more advanced topics. At the end of each section, there's an optional quiz designed to test your understanding of the most important concepts. These quizzes are a great way to solidify your knowledge, so I recommend taking them even if they are optional. Let me just give you a few general study tips to help you get the most out of this course. Set a schedule and stick to it. Try to compete lessons and sections in a timely manner to avoid forgetting what you've learned once you start the course. Don't let days or weeks pass between lessons. Trust me, having to go back and sit through the same lectures you've already watched is a drag. Find the quiet and distraction free study space. This can be as simple as a desk with a chair and some background music. If you have any questions or issues during the course, don't hesitate to ask me in the QA section or contact me directly. I'm here to help you. One more important tip. Take notes. If possible, write them down in a physical notebook. The act of writing can help you better retain the information. Finally, try to have fun and enjoy your learning experience. 4. Create a Google Analytics 4 Account: The first thing we'll take a look at is how to create your Google Analytics account. What you want to do is go to analytics.google.com and log in to your Google account. If you don't have a Google account yet, you should create one. After you successfully log in, you will see this screen. To create another account, simply go to admin and click create account. If this is your first time creating the analytics account, this is the screen you will see after logging in. To start, you should give your account and name. This is typically the name of your business. Or if you have multiple legal entities in different regions, you might name it after the entity you're creating the account for. Next, go through the account data sharing settings, which Google uses to improve its services and possibly your account. So read through them and choose the ones you feel comfortable with. Next you'll need to name your property and add some initial settings like time zone and currency. You can have multiple properties depending on how you structure your account, and we'll talk about this in a later episode. I'll just use the website URL because I'll be testing this on a website. In this step you can select properties that pass describe your business, but don't worry, they are not that important and you can later change them if you like. Then just click create. You also need to agree on the terms of service, so read through them and then click agree. Now our account is set up. And we can continue, but we still need to create a data stream to start collecting our data As you can see, you can gather data from various sources such as iOS and Android apps or websites. And you can consolidate them in a single property. This allows you to track the customer journey across different devices, if that's applicable to your case. For our purposes, let's just create a website stream. You'll need to write your website URL here as well as name it here. I'll just name it website stream. Below you have some additional settings called and enhance measurement. Here you can see what Google Analytics measures automatically. Let's just quickly see what can Google automatically track. You see, you have your scroll tracking. Click tracking, video engagement. And so on. If you want to disable any of this, just click here. It's worth noting that while we discuss the effectiveness of different automatic trackers in later lessons, for now it is recommended that you leave all of these options enabled. Let's just create our stream then. And after doing so, you will be taken to the summary page that displays details such as your stream name, URL and measurement ID which you'll need when we will be setting things up on your website. There are other settings on the summary page that we will cover in later lessons. For now, this concludes the process of creating your account property and your first datastream. 5. Property Migration and Settings Overview: If you're coming from Universal analytics, then in this lesson you'll learn how to quickly and effectively migrate to Google Analytics 4. Migrating from Universal analytics property with the help of Google Analytics 4 setup assistant is Super Easy. Before we start, you should know that the setup Assistant Wizard does not change or modify your Universal Analytics account at all. So don't worry about your existing data. It also does not backfill your new Google Analytics 4 property with historical data and your GA 4 property will only collect data going from this point. Forward. OK, let's now take a look at how to migrate your property. First you need to make sure you have at least an edit role for the account. Then in your UA interface, click on admin, then under the property column, select the property you'd like to migrate and click the convenient button GA 4 setup assistant. If you're doing this for the first time, you want to create a new GA 4 analytics property, but there is also the option to connect your UA property to existing GA 4 property. If you'd want to do so, you can find it here below. Next you'll see what setup assistant will do. Next click create property and you are done and you also get the option of enabling data collection. You can only enable this if you have implemented the data collection using Gtag JS or your CMS supports this. If you are implemented to your data collection any other way, for example through Google Tag manager, then you'll need to do this manually before your GA 4 property will start collecting data. Below you can see the new property name and property ID. Now let's go to your newly created GA4 property. The first thing you'll see in the setup assistant is the overview of what you have already done and what needs your attention. Because we haven't enabled the data collection yet, the data isn't flowing in. If for example, we look at another property that has this setup already, you can see that here the data is flowing in. Let's take a look at how you can set up your data collection first. As mentioned before, GA4 uses data streams to push the data to your property. So let's go to data streams. You'll see that the setup assistant already created a web data stream for you. I'm not going to go into too much detail on this screen, but all you need to know is that you can easily add multiple data streams here for different sources. Let's open now this data stream. The first thing you'll notice if you haven't set up the data collection is that you get the instructions on how to do that. You can get to this screen also here at the bottom. Google will give you detailed instructions for the few most popular CMS here, but they have detailed instructions for even more CMS in their help centre. I left the link to those in the lessons notes. But if you prefer, you can also install it manually similarly as you could with universal analytics. If you use Google Tag manager, you'll need measurement ID which is this code and you can also get it back here. Once you set it up, it might take up to 30 minutes before data starts to pour in. If you need to set up your cross domain tracking as well then you can do this here. One thing I want to mention really quickly is at this stage you can also set up enhance measurements. These are all the things GA4 automatically tracks on your website, and if for some reason you don't want to track something from this list, you can simply disable it like so. Let's now quickly go through some of the most common settings and where you can find them in the new interface. In the property settings you can now find some of the settings previously found in views like time zone and currency. In data settings you can find your data collection and retention settings. Also, the filters have been moved here so you can exclude the traffic you don't want in your reports. Their functionality stays the same as in universal analytics, but you are limited to 10 filters per property. You won't find both filtering settings anymore as GA 4 now automatically excludes them. There's also no need to enable ecommerce reporting as they will be generated automatically. Basically, these are all the essential steps you need to take to set up your GA4 account. You can cheque all the changes in the GA4 Help Centre and I left the link in the lessons notes. If you want to go deeper into the migration process and learn how to migrate your audiences, goals, ecommerce data and so on, then I have a dedicated course just for that. You can find it in my profile. 6. Setup GA4 Manually on Your Website or Store: Before we begin, I would strongly suggest you use Google Tag manager for setting up Google Analytics on any website. It simplifies the process of installing tracking code on your website and provides enhance tracking capabilities, greater control and flexibility, and improved efficiency. If you want to learn more about Google Tag manager and how to use it, I have a separate course on the topic. Let's get back to installing Google Analytics 4 manually on your website. The first thing you'll need is access to the files on your server. This can typically be achieved through FTP or through your hosting providers File Manager if they have one. Once you have access to your server files, you will need to find the correct files to insert the Google Analytics code. From any websites this will be the index file, which is usually the first file that loads and contains the header and footer of the page. However, if your website is custom built or users certain themes, the process might be slightly different. After you find the file, you want to open it, but before you can do anything, we must first get our GT4 pixel code. You'll go under datastreams and click on view tag instructions. Here Google gives you instructions and plugin suggestions for your specific platform. But we'll talk about this in the following lessons. For now, let's just go under the install manually tab. And we'll copy this code. You'll also get instructions on where to put this code, and you should always put just one instance of code on your website. Now let's go back to our file. If we open it, you'll see there is a bunch of HTML code inside and what we need to do is find where the head tag is located. You can also search for it if you want. Google suggests putting this code as high as possible, so let's just do this. Once you've added the code, be sure to save your changes and refresh the page to check if it's working properly. You can also use a tool like TAG Explorer to verify that the Google Analytics code is running properly. If you don't have this plugin installed, you can also check the source code of the page by right clicking on the website and selecting view page source. This will allow you to browse through the code and as you can see we have GA4 code here added correctly. One less thing, it may take up to 24 hours for data to start appearing in your GTA4 account, so be patient. 7. Set it up on WordPress: Let's now take a look at how you can set up GA4 on your WordPress site. There are actually multiple ways you can do this. The first one is doing it manually, very similar to how we have done it in the previous lesson. The only difference is that you would need to know in which WordPress file the header part of the HTML is located. Usually this file is in the theme folder and its name header, but this may vary from theme to theme. Next you could install it with the help of Google Tag manager, which I strongly recommend as this will greatly improve the ability to add or modify all your other tracking tags. I won't go into details on how to do it here as you need a bit more background information on how to set up Google Tag manager. I do have a detailed course on Google Tag Manager which I recommend you take a look at if this is something you would like to learn what we will take a look at. It's how to install your GA 4 by using a WordPress plugin. If you've already set up a plugin with GA 4 support then I suggest you use that one, but for our example we'll use a plugin called GA Google Analytics. Let's first install this plugin. Go to your WordPress admin section and under plugins click add new and search for this specific plugin. You'll want to install the one by Jeff Star. After it's installed, you still need to activate it and then we'll be able to set everything up After its activated you can find the settings for it here under the plugins and set up. Or by going under settings and clicking on Google Analytics. Now just click on plugin settings. What we need to do first is get our measurement ID from Google Analytics 4 let's go to our GA4 account. And under your appropriate web stream, copy the measurement ID. All we want to do now is just copy it back to the plugin. If you click on the info you'll see all the ID formats this plugin supports. As you can see, they support everything from the legacy Google Analytics to the new GA4. You want to leave everything else in this plugin as it is. If you don't know what you're doing, you might use the custom Tracker object section to add extra parameters during the config phase, like Google Adwords setup. Or if you don't want to track your activities when you're logged into your WordPress as admin, you can enable this option. After you're done setting everything up, we can test if everything works as it should. First go to your website and refresh it. If you have any pixel tracking plugins, you should be able to see your new GA4 load. You can also go back to your Google Analytics and in the report section click real time report. You should be able to see the heats coming from your website. If you have disabled the option to load GA4 for admins in the WordPress plugin, then make sure you're either logged out of WordPress or you open website in the Incognito window. Otherwise the GA 4 won't load and you won't see any activity on your website. 8. Set it up on Shopify: In this lesson we'll take a look at how you can set up your GA4 pixel on Shopify. There are three ways you can do this and I'll show you all. Then you can decide which one is most suitable for you. The 1st way is very simple and I would recommend it for most beginners. What you need to do is go under the online store then preferences. Here you will scroll a bit lower and under Google Analytics section you will get this notification. If you don't see the notification, you can always install the free Google Channel app through Shopify App Store. I've left the link in the lesson resources. After you install the Google app you will see a link here in the site menu. So just click it. The first thing you'll need to do is connect your Google account and give it all permissions. After you do that you will see this section which allows you to connect to GA4 Analytics property. Just create a new connexion and select the one you wish to connect to. Then click connect. And you're basically done. This will install GA4 pixel on all your shop pages and it will trigger most of the ecommerce events. The purchase event for example will be triggered so you will be able to track conversions and their value in your GA4 analytics. But events like add to cart or removed from carts unfortunately are not triggered I think. This is still the easiest way to set up your GA4 pixel, but I'll disable it for now so I can show you some other ways. You can also set it up without using this plugin. The 2nd way is to edit the theme files and add GA4 code there, which is similar to the manual installation we've covered before. For this you want to go under the online store. Then teams. And under your current team, click on edit code. On your left side you'll see all the files you can edit and you'll need to look for two files. First theme.liquid and second one checkout.liquid. You can see the theme.liquid file here. But if you have a basic plan like I do, you won't see I'll be able to modify the checkout file. Next what you want to do is open the theme.liquid file and then paste the GA4 code inside. You can get your GA4 code in the usual place in the data streams. And under the view tag instructions. Then go into the install manually tab and copy your code. You want to paste this code as high in the head section as possible, and I would usually paste it somewhere here. Then save the file. If you see the checkout.liquid file here on the left, then do the same thing there as well. This way you will also install the GA4 at the checkout process. If you don't have the access to checkout.liquid file then GA4 will be installed on all pages except the checkout process and you won't be able to track the purchase conversions. The other way you can install GA 4 to your Shopify store is a bit more complicated, but it will install GA4 across the whole page, including the checkout process. So let's take a look at how to set this up. First, let's go back to the store and click on preferences. If you scroll a little bit lower, you'll see the Google Analytics setting where you can paste your Google tracking ID. Unfortunately if you try and paste your G A4 measurement ID here, it won't work. So what we need to do is paste your existing universal analytics code here instead. If you don't have it or just don't want to track anything in the UA anymore, you can simply fake this number by entering UA then 9 numbers. And another dash and one more number I just make it as such UA 123456789-1. After you do this, additional Google Analytics JavaScript section will appear. Now what you want to do is go to the resources and copy the script I've provided for you and paste it here. Then all we need to do is replace this part called measurement ID in all caps with your actual measurement ID from G A4. So let's just quickly get our ID and paste it in both places. Then save everything and let's test it out. Let's open our store first. If you have a tag assistant plugin installed, you should already see the GA 4 script running. But no worries if you don't because we'll doublecheck it in the GA4 real time reports as well. So let's go here now. And. You can see we have our first hit. Let's just quickly check if GA4 is also installed during the checkout process. OK, let's add something to the cart. Then go to the checkout. And we can see the GA4 is loading in the tag assistant. If we wanted to we could also double check it in the GA4 realtime reports, but I'm not going to do this at this moment. 9. Connect Search Console: In this lesson, we'll be diving into how to integrate Google Analytics 4 with Search Console. This integration will allow you to analyse your site's organic search data in more detailed manner. By doing so, you'll be able to see where your site ranks in search results. You'll be able to track which queries lead to clicks and understand user behaviour such as which landing pages engage users more and how many of them convert. With this integration, you'll also have access to two new reports, Google organic search queries and Google organic search traffic. Connecting the search console to GA4 is pretty straightforward, so let's just jump right into it. First, go under the admin section. And scroll almost to the bottom of the properties section where you'll find the search console links. Then click on it. And click next on the link button. Next, click on choose Accounts where you'll see all the search console accounts connected to your current Google account. If you don't see anything here, please make sure that you are a verified owner of the Search console property. Next, simply select the account you wish to connect and click confirm. Then click next and then select the web stream you wish to connect it to. In my case I only have one web stream, so I'll select this one. Then click next again and verify your connection. If everything is OK, click submit. And after this is done you will see the link created message and you can now close this window. If for some reason you want to remove the link, you'll have to go into your search console and do it from there. Let me quickly show you how. First go to the search console and under settings you'll find associations. Here you'll see the connexion to GA4, which you can remove by clicking on these three dots. And then clicking remove the association. We're almost done. There's one less thing we need to do. Since the search console report collection is not published by default, you won't see the reports. So let's add them to the report section. First, go under the reports. And here at the bottom click on library. Then simply find the search console collection and under the three dots. Click on the publish button. And you'll see your search console here. Sometimes, for some reason, you'll get two search consoles published automatically. If this happens, just delete one of them from the library like so. Now you're ready to see your search console reports in GA. There are some limits to the integration you should know about. First, you can only link one web data stream to the search console property and vice versa. Additionally, a GA 4 analytics property can only have one data stream linked to a search console property. The search console reports currently do not support time series charts, and search console metrics are only compatible with search console dimensions and certain analytics dimensions like the landing page, device and country. 10. Connect Google Ads: In this lesson, we'll take a look at how to connect Google ads to GA4 and all the benefits this brings. By connecting ads to GA 4, the data will flow both ways between the products. This way, you'll be able to see your Google ads campaigns in the acquisition Overview report, access new Google ads dimensions in the user acquisition report, import analytics conversions into your Google ads account, and enhance your Google ads remarketing with analytics audience data. Additionally, you'll be able to see your Google ads campaigns in the advertising workspace, including the attribution reports. The process of linking Google ads to property it's very similar to connecting search console. First, go under the admin section and Scroll down in the properties section where you'll find the Google ads links. Click on it and when the screen opens. Click on the link button. Next, click on choose Google add accounts. And here you'll see all the add accounts connected to your current Google account. If you don't see anything here, please make sure that you have administrative access to Google ads with your current Google account. Just to think, you should know, if you link to a Google ads manager account, any data that you import from analytics will be available available to you. And to you all of your client accounts. Next, select the account and click confirm. Then click next and at this point you can choose to disable personalised advertising. Basically if you disable this, then GA4 audience list and remarketing event parameters will not be shared with connected Google Ads account. If you disable auto tagging, Google Analytics will not associate Google ads data with customer clicks and the reports will have less data to show you. I would suggest you leave both settings on unless you know exactly what you're doing and know that you don't need this data. After you click next you will see the summary and if everything looks OK, just click submit. When you are done linking both accounts, you'll automatically start seeing Google ads data in your Google Analytics reports. Note that this may take up to 24 hours before this data is actually visible. So you can only make around 400 connexion per GA4 property, but that should be enough for most cases. But to be able to take action on this data in your Google ads, you will need to also import conversions or add audiences or do both. So let's take a look at this and how you can do this. Go to your Google ads account and we'll start by importing the conversions. If you haven't created any conversions yet in your G A4 account, you should do that first. Then in the tools. And settings menu, under the measurement section, click on conversions. In the left corner, click on the new conversion action, then click import. Here you'll select the GA for property and select whether you're importing from Firebase or Web data streams. After that, select all the conversions you wish to import and click import. Then click continue. And finally. Done. When you do this, you'll be able to see GA4 conversion data in Google ads. But give Google ads smart bidding access to the data that will help its optimise your bids. Just a small warning, if you have your UA conversion actions already imported, then Google will by default set your GA 4 conversions as secondary to prevent counting the same event twice, and you'll want to make them primary. Before Universal Analytics goes away. Next thing we'll do is set up the audience source to use in your remarketing campaigns. You want to click the tools again and settings menu, and under the shared library section, click on the audience manager. Then in the left menu, click on your data sources. And in the GA4 and firebase cards, click link to Google Analytics and Firebase button. Next, click Link next to each property or project that you want to add to your Google ads account. And you are basically done. Once you do this, you will be able to expand your reach, manage, monitor, and troubleshoot your audience sources, as well as view tag hits, active parameters, and data lists created for each audience source. This is it for this lecture. And I'll see you in the next one. 11. Introduction to Common Marketing Terms and GA4 Properties: Let's first explore some commonly used marketing terms and concepts in Google Analytics 4 We'll quickly go through some common terms we'll use in later lessons, and we'll break everything down into easy to understand language. If you're already familiar with them, feel free to skip this lesson. First off, let's talk about conversions. Imagine you have a shop and people coming to browse, and conversion is like someone coming into your shop and buying something. Instead of just looking in the online world, it could be signing up for newsletter, making a purchase, downloading an ebook, or registering on your website. Basically, a conversion occurs when a visitor completes a desired action or does something beneficial for your business. In web analytics, a session is a group of interactions that the user has with your website within a given timeframe, like page views, social interactions or ecommerce transactions. Think of a session as a single visit to your website, where a visitor might look at different pages, maybe put something into a shopping cart, and so on. It's all the activities they do before leaving or taking a break. In GA4, a session lasts until there is 30 minutes of inactivity. Impression is our third term. This refers to the number of times an ad or a piece of content is displayed or seen, regardless of whether it was clicked or not. It's like seeing a billboard on the side of the road. Even if you don't stop and look at it, the billboard has made an impression on you. In digital marketing, it's how many times an ad or a page has been displayed on someone's screen. A touch point is an interaction between your brand and your customers. This could be an ad, a social media post, an e-mail or a face to face interaction. Imagine a series of stepping stones leading to your front door. Each stone is a different way someone can interact with your business. This interactions or touch points guide people toward becoming users or customers. Understanding touch points is key to improving customer experience and increase conversions.. Now let's talk a little bit about GA4 terms. First we have parameters. A parameter is an extra piece of information that could be included in an event. This could be something like the value of a purchase, the content of a page or the name of a clicked button. It provides the context for the events that you are tracking. For example if an event is "bought_a_shirt". Then the parameters could be the color, size and price of that shirt. Basically. It helps you understand more about what's happening on your website. Next, we have a variable. A variable refers to a named placeholder for a value that can change. Imagine having a container that can hold different things. A variable is like that container and depending on the situation it can hold pieces of information or values. It's a flexible way to work with data. Value is another straightforward term. A value is the actual information of measurement that is stored in a variable or passed in a parameter. It could be numerical like the quantity quantity of the item purchased, or it could be a string like a page title. In Google Analytics. A dimension is a descriptive attribute of characteristics of an event that can be given different values and can be used to, sort, or categorize data. Think of them as labels on different drawers in a file cabinet. Each label tells you something specific about the information inside, helping you organize and analyze it. For example, browser, screen resolution, city, and session duration are all dimensions that appear by default in your reports. On the other hand, metrics are like the ruler scales and measuring cups of the digital world. They provide quantifiable measurements of specific activities or trends. Imagine you want to know how many people visited your website or clicked on an ad. Those numbers are your metrics. Metrics help you understand the how many or how much of what is happening on your site. Understanding metrics is like having a thermometer for your business that allow you to gouge how well you're doing, identify areas of improvement, and make informed decision to help you grow your business. Our last term is audience. And audience refers to a group of individuals who share a specific characteristic or behavior. Think of a garden with different type of flowers. Each type represents a group of people that you want to reach with your marketing. Understanding your audience helps you tailor your message, just like you would care for different flowers in different ways. In GA4, you can define audiences based on a variety of factors such as demographics, behavior, and conversion events. This allows you to customize the user experience for different audience segments and optimize your marketing strategies. We've covered a range of terms from both marketing and GA4 that will be crucial as we move forward in our journey to master GA4. In the following lectures, we'll see how these concepts are applied in practical scenarios. 12. How to Set up Your Account Structure in GA4: Depending on your current setup, migrating to Google Analytics 4 can be super easy or a bit more complicated. It all depends on the complexity of your current universal analytics setup and your business requirements. Let's first explain the concepts behind the GA4 structure. Then we'll take a look at a few real world examples you can take inspiration from. If you're coming from Universal analytics, you're familiar with the concept of views. You use views to create separate collections of data, such as geographical separation, line of business separation, and so on. And GA4, you don't have views, but you can accomplish this kind of data separation. In different ways. The granularity to which you separate your data and how you control access to it depends upon your needs. You will need to set up your Google Analytics account differently if you have a small business with a single website or a large enterprise with multiple brands and thousands of products. Before we explain how the setup each of those cases, let's explain in detail the three pillars of your analytic structure, account, property and data streams. The account holds a collection of properties whose data is owned by a single linked entity and governed by a region specific terms of service. If you can centralise your data in one region, you will need just one account. If the data is owned by different regional entities, then create. Account for each region. A property which leaves within an account represents data for one user base like product, line, brand or application. For each user base whose data should generally be analysed together, use one property. This is also the level at which GA4 processes data and you can create links to other products. The last level are data streams. They live within a property. They are the source of data from your app or website. Create a data stream for each of the ways users interact with your business. At this level. You can also control the data collection features through the SDK or global site tag. OK, now let's take a look at a few examples of different businesses. We'll start with John. He has a small side project for bee lovers and he created a simple website to share his passion. Because he only has one website, he only needs one data stream. So his structure should look something like this. One analytics account, one property and one data stream for his website. Mary on the other hand is building a SaaS startup. Their main product is a web app for which they also have a marketing website and they have just launched their first mobile app on iOS. Because Mary's data is on different platforms, she needs three data streams and her structure should look like this. One analytics account, one property and then three data streams, one for Web app, one for her iOS app and one for her marketing. Website. Since she has all of her data in one property, it will be possible to see the whole customer journey of a user from the first touch point to the usage of her web and final mobile app. Let's now look at Ram. He runs the news media website with over 10 million monthly visitors and he also has a mobile app for iOS and Android. Since he wants to monetise all this traffic, he also created a dedicated portal for advertisers who want to promote businesses to his audience. Because Ram's business has two distinct user bases, he needs two properties. This is why here's analytics account should look something like this. He would have one analytics account with two properties. The first property would be for his readers and since they can consume the news either on the website or on the mobile app, he would need three data streams. One for his website, one for iOS app and one for the Android app. Then he also needs a property for advertisers, but since he only has one portal for them to manage their ads, he will only need one data stream for this property. Let's now look at the big ecommerce store from Julia. Her company owns three different brands, each having hundreds of products, and all of them are present in seven European countries. Her account structure would look something like this. She would need three properties, one for each of her brands. Then each property would need to have seven data streams. One data stream for each country that they address. This will allow them to have all their brand data in one place while separating audiences by country for advertising purposes. There are many more ways you can set up your structure, and it will greatly depend on your business needs. In general, you should set one account per company and one property per brand or business unit, assuming your brand's and business units are distinct operating entities with separate stakeholders or analyst groups, and then as many data streams as you need to capture all the ways users interact with each property. 13. Limits you Should Know About: Like all free versions of software, there are some limitations to what you can do with the free version of Google Analytics 4. In this lecture, we'll explore some of these limitations and discuss how they might impact your use of the platform. One of the main limitations of the free version of Google Analytics 4 is the retention of data. The maximum time period you can set is 14 months compared to UA where you could set it to 26 months. Keep in mind though, that the data retention setting only affects explorations and does not affect standard aggregated reports. Talking about explorations, there is also a limit of 200 per user or 500 shared within the same property. Another limitation is the number of conversions you can create and manage. With the free version you can only create up to 30 conversions. This means you will have to think a bit differently about what you consider a conversion. Luckily, GA4 now has a powerful funnel exploration builder, so you can focus on tagging macro events as conversions and add micro conversions as steps in the finals. In addition, GA4 also limits the number of custom metrics and conversions to 50 each, and you can have up to 100 custom audiences defined. Which should be enough for most use cases. Since GA4 is event driven, there is no limit on the number of distinct name events for web data streams. But keep in mind that there is a limit of 500 events per app instance. Finally, to compensate for ditching third party cookies, GA4. more heavily relies on sample data and machine learning to fill the gaps in reports. On the other hand, when looking at the reports, unlike in UA, all the standard reports will show unsampled data, no matter if you apply comparisons, secondary dimensions, or filters Advanced reports might get sampled when data exceeds 10 million in counts. Overall, the free version of Google Analytics offers a lot of powerful tools and capabilities. It's important to be aware of its limitations and how they might impact your use of the platform. If you have a large website or need access to advanced features and support, you might want to consider upgrading to analytics 360, but the pricing is quite steep. I hope you now have a better understanding of what you can and can't do with GA4. 14. Practicing on the Demo Account: In this lesson we'll be learning how to access and use Google Analytics 4 demo accounts to practise with real business data. This will come in handy if you don't have enough data in your property. The demo account is a great way to experiment with Google Analytics 4 features and learn how to use the platform. You can use the demo account to explore different reports and tools in GA4. And to see how you can use them to analyse your website traffic and performance. First, let's talk about what the demo account is and where the data comes from. The demo account is fully functional Google Analytics account that any Google user can access. It contains two Google Analytics 4 properties. The data in the demo account is from the Google Merchandise store and flood it app and contains real information about traffic sources, user behaviour and transactions. To access the demo account, simply click on one of the links provided in the lesson resources. You will be prompted to log into your Google account, or to create one if you don't already have one. Once you're logged in, Google will either add the demo account to your existing Google Analytics account, or create a new one for you and add a demo account to it. There are some limitations to the demo account you should be aware of. First, all users have the view role, which means your activities are mostly limited to viewing the data. The Google Analytics Pro 4 properties do not include reports or exploration, export functionality, or the ability to see the device ID dimensions. Additionally, the demo account cannot be used with the analytics reporting API. If at any point in time you no longer want to have access to the demo account, you can easily remove it the same way you would any other account. 15. Event Naming Best Pratices: In this lecture we'll discuss some considerations to keep in mind when creating your analytics strategy and structuring custom events in GA4 properties. In GA4 we define an event name and it carries with it up to 25 parameters. These parameters are additional pieces of information that describe the event. A common stride starting point is to set the event name to general category and add specific actions and details parameters. For example, if you are tracking video events, you could have an event named videos that carries parameters for the specific action taken such as play or pause, and the video details such as title and time. However, a more granular approach would be to create separate events for the each possible action. This would allow you to more easily track and analyse specific actions such as play or pause. Using the same example, your event names could be play video or pause video or even progress video and so on. The video details could then be added as parameters to each event. This would give you more flexibility and clarity in your reporting and analysis. In addition to granularity, it's also important to use clear and descriptive names for your events and parameters. This will make it easier to understand the data and to create meaningful reports and analysis. Instead of using a generic names like event action or event label, try to use names that reflect the actual meaning of the data. From the previous video example, you could use video title and video time as names for the event parameters respectively. This would make it immediately clear what information is being tracked by those parameters. Another important consideration is to ensure consistency in your event structure. This means using the same structure for similar events and using similar names for similar parameters. This will make it easier to compare and analyse data across different events and parameters. Finally, it's also important to document your event and parameter names. This will help you and other members of your team understand the data and avoid confusion or mistakes. You can use a tool like Google Analytics annotations to add notes and descriptions to your events and parameters, or create a document that outlines your event structure and how it should be used. In summary, best practises for structuring custom events in Google Analytics properties include. Favour granularity in your event naming conventions. Use clear and descriptive names for events and parameters. Ensure consistency in your naming conventions and document your event and parameter names. By following these guidelines, you can create a more effective measurement strategy and generate more meaningful insights and analysis from your GA4 data. 16. Top Level Interface Overview: In this lecture we will be taking a look at the main features and components of the GA4 interface and how you can use them to track and analyse your website's traffic. At the top of the screen you will see the main menu, which contains several tabs and options that allow you to navigate through different reports and tools in GA4. The main menu is divided into 5 main sections, home, reports, explore. Advertising and admin. The Home tab is the default tab that appears when you first log in into GA4. It contains a quick overview of your website traffic and performance, including the number of users. Sessions and conversions. You can also see recently accessed reports. Some suggested ones and insights. The report steps contained the premade reports and tools that you can use to track and analyse your website traffic. They are organised into different categories and each of these categories contains several reports then you can use to learn more about your website traffic, user behaviour and performance. Each report also has some extra settings you can change. In the top left you can see the ads comparison button, which enables you to evaluate subsets of your data side by side. You can compare data by creating multiple conditions based on dimensions and their values. If you use multiple dimensions and values, they will be evaluated with an or statement, for example the United States or India. If you add multiple conditions, they will be evaluated with ends. Remember that based on your report, some dimension values may not be available or be allowed to be excluded. One very useful feature to know about is. Is this button below called explore? With it you can simply recreate any standard report in the explorations view and then modify it to your liking. This can significantly speed up the process of creating custom exploration reports. You also have your standard date section drop down with some preset date ranges and you can also select a custom date range. Below it you have a few shortcut icons like the share button and inside shortcut. There is also an edit icon that looks like a pen to modify the report, but since we are currently in Google's demo account we don't see it. Don't worry. I'll show you how to modify your reports in another lesson. Each report card also has an indicator that tells it if the data is sampled or if the threshold has been applied. Data thresholds are a safeguard to prevent anyone from inferring the identity of the individual user based on demographics, interest, or other data. Data in a report or exploration may be withheld when Google Signal is enabled, if reports include demographic or search query information, or if you are viewing the data in a narrow date range. In some cases, Google can also use data sampling to speed the report generation. If we are exploring data through unmodified standard reports then the data won't be sampled. But if you create an ad hoc report or go deeper in the explorations then data can be sampled at approximately 500 K sessions at the property level for the date range you are using. But this number may differ based on the complexity of your analytics implementation. The use a view filters query complexity for segmentation or some combination of those vectors. One option to avoid sampling is to shorten the date range, if you can do that. The Explore Tab provides a powerful and flexible way to explore and analyse your website's data and gain deeper insights and understanding about your websites traffic, user behaviour and performance. The advertising section provides a comprehensive and powerful set of tools and reports that you can use to track and optimise your advertising campaigns and to drive growth and success for your business. Finally, the admin tab is where you can manage and configure your GA4 account and properties. This includes setting up user permissions, creating custom dimension and metrics, and configuring the data collection and processing settings for your GA4 accounts. In conclusion, the GA4 interface is designed to be user friendly and intuitive with a clean and modern design, but since Google is still. Working on improving GA4 It may still change in the future. 17. Where in GA4 can I Find my UA Reports : In this lesson, we'll take a look at some of the most commonly used UA reports and where you can find them in GA4. I'm not going to go into details of each report, I'm just going to show you where you can find most of your old reports in the new GA4 interface. Let's start with the customization section. The closest thing to this in GTA4 is the exploration section where you can create custom reports and dashboards by. The reports you can create here are much more advanced and you can get deeper insights. The next section is real time, which you can find by going to reports and clicking real time. Again, the dashboard is a bit different, but you'll get all the information you're used to in one place. You can also compare different user segments or philtre this data by any dimension you wish and thus get a more granular overview of what is going on right now on your website. There's also a new section called Debug View which you can find under configure and this will help you see what is going on on your website at a more granular level in real time. The first thing you'll notice in the audience overview is that a lot of reports that you see in the UA are missing in the GA4. Some of them can be found elsewhere and some you can add or create by yourself if you need them. Adding new cards is super simple. Let's say you'd like to have a new card on this report. What you do is simply click customise report, then click add cards and select the card you wish to add. If we want to see how many new or returning users you have on your site, you will now find this report under the retention section. You also have here a cohort report as well as user engagement and lifetime value. The demographics and geographic section from the audience section has been moved to the user section below. You have your country, city, gender, age, language and interest segmentation all in one place and if you want you can go even deeper with the detailed report. The same goes for the technology section which is right here below where you will find all the reports regarding devices, browsers, screen resolution and so forth. If you're looking for the user flow alternative in GTA4, you won't find. There is no predefined report for this, but it's super easy to create in the Explore section. So let me quickly show you how you can do it. Go under Explore section, then select the path exploration template. I won't go into all the details of variables and depth settings as we will discuss this in another topic. But if you'd like to have same report as in UA, you just set the country to the breakdown section and now you have a very similar report as to default one. In UA you can click on a country and have the traffic from the country highlighted. You can change the event to the page title so it's clear on the path of the user. Then you can drill down to explore other steps as they have taken. If you want, you can save this report and return to it when you need it. I won't do this now, so let's go on. Next thing I want to show you is the acquisition section. You will see that in UA you have a lot of subsections, whereas GA4 you only have the default overview. But don't worry, it's super easy to get to most of these reports once you understand where to look. By default you can see two cards, users and sessions per channel grouping and under sessions you see the engage sessions. As we discussed in the previous lesson, there is no bounce rate in GA4 so you will use this instead. Then if you want to see the data based on source, medium, platform, campaign and so on, you can simply change it here. This corresponds to most of the subsections in the UA like source, medium, Google ads, campaigns, keywords and so on. If you have connected the search console to GA4 then you will be able to see all their corresponding reports like queries under the organic search traffic. You will also find groupings by landing page, country and device category. To get to the social data equivalent in UA, you would basically create a filter in GA4 that includes only social channels, then go to a report that you want this data for. For example, if you'd like to see landing pages from social, just go under engagement. Then pages and screens. Then click add filter. Select session default channel grouping. And choose the channels you wish to filter. In our case, we want to see, let's say, organic social, so I'll select this. Then you simply apply the filter and you will get this specific report. Let's go now to behaviour section. To get data for behaviour flow you would do the same as we did for user flow and create a report under the exploration. But instead of users you would do the breakdown by page name. Almost all the side content reports you can find under engagement and then pages and screens. You just click here and change by which dimension you wish to group data. The exception is exit pages, which you'll find under Explorer. What you want to do is select free form, then add a new dimension called page path. Then add this dimension to rows. Next search exits under the metric. And add it to report. Then simply drag it to value section. Unfortunately GTA4 doesn't measure side speed, so there are no reports for this section. You can however use some other third party tools to track your site performance. Site searches are a bit hidden and if you don't know where to look you would have a hard time figuring it out. If you have enabled site search under the enhanced measurements in the data streams, this event will be automatically generated. Otherwise you'll have to trigger it by yourself. To get these reports you can go under the events. And find the view search results event. After you click on it, you will get all the details regarding this event and if you scroll to the bottom you also see search terms. The last thing in this section are events. You can find them under engagement and then click on events. Since everything in GA4 is now an event, we will see a lot more events here, not just the ones you created. In UA events had multiple levels like category, action and label. In GA4 there is only an event name and whatever parameters you attach to it. So you could keep the structure from UA or change it completely, or even add multiple parameters depending on the events and so on. But this is a totally different topic. Now the last section I want to talk about are conversions. They have also been changed quite a lot and the most important thing, they have been unified and simplified. Basically what was called goals in UA is now called conversions. So you won't have separate conversions for goals and ecommerce, but instead we will find them all under engagement and then conversions. There are some events that are automatically marked as conversion. But you can mark any event as conversion if you wish. Simply by clicking on each event you will also get a detailed report. If you wish to create a funnel for your conversion, you can do so under the explorer. This time we would select funnel exploration. Then you simply define all your steps. And you will get a custom panel overview. This concludes this top level report comparison between UA and GA4. As you can see, you can find almost everything from UA in GA4, but most importantly you can create many more advanced reports more relevant to your specific business needs. 18. Real time Report: In this course we will explore what real time reports are, when and how to use them and what are their limitations. Real time reports in Google Analytics 4 allow you to monitor the performance of your website or app in real time. You can see how many people are currently on your site or app, where they're located, which pages or screens they're viewing, and more. Real time reports are especially useful in situations where you need to monitor the impact of changes made to your website or app in real time, such as during live events, a product launch, or a website redesign. Real time reports are at the top of the reports menu. Here you can see the total number of users in the last 30 minutes with a history graph and users split by device. On the map you can zoom in and out and you can click on a specific city to get the detailed performance of that location. You can see that by default it will open in a comparison mode, so you can quickly see the difference between this location and all users on the site. Let's go back now to the real time report. At the bottom of the map you can find a lot more reports. The first one breaks down the traffic by user and channel. You can view the breakdown by sources, medium or campaign by simply selecting linked here. This way you'll be able to see exactly which activities and channels generate you the most traffic. Right now, the second card shows you users by the audience. If you didn't create any audiences yet, you will only see two audiences or users and purchasers. If you want to track specific audiences, just create them in GA4 and they will show up here as well. If you want to know which pages are getting the most traffic, you can see that in this card. You can also see top performing events and which events were responsible for the conversions. What you can also see is that each card shows you the best performers here in the upper left side of each card. For example, you can see the name of top performing page, the number of visits and the percentage compared to all other pages that were visited in the last 30 minutes. One thing that's really amazing in GA4 is the ability to see a snapshot of random users activity on your site. You can simply click this button for that. Here you'll be able to see the location of these users as well as the app version if you have a mobile app. You'll also see the action history of this user on your website, and you can even get more information about each triggered event simply by clicking it. Then you'll be able to dig deeper into the parameters and user properties. You can do the same by clicking individual events here on the list of top of events. But here all of the events will be grouped together. You'll also notice that each event type is coloured differently to give you a quick overview. General events are coloured blue, conversion events green and error events red. And you can philtre them out by clicking on the individual icon. Once you've done with the research, you can simply exit the snapshot here. While real time reports provide valuable insights into your website or apps performance, there are some limitations to keep in mind. For example, realtime reports only show data for the last 30 minutes and certain types of data such as conversion tracking are not available in real time reports. 19. Acquisition Reports: Let's now dive into understanding the acquisition reports in Google Analytics 4 and how they can help you to measure the effectiveness of your marketing campaigns and make data-driven decisions. Acquisition reports provide insights into how your website or app acquires users, where they come from, and how they engage with your site or app. In GA4, acquisition reports are divided into 3 main sections, overview, user acquisition and traffic acquisition. The overview section summarises your website or apps performance, including the total number of users, new users, sessions and page views. You can also group data by different dimensions in these cards where it applies. Now let's go to acquisition. This section provides data on how users are acquired on your website or app. Such as through organic search, paid search, social media, e-mail marketing and other sources. These channels are the first touch point through which users have access your website. For example, if a user has found you through a search, that would be marked here in the organic search. Even if they come back to your website later from your paid advertising. You can differentiate this type of dimensions by the word first in the name. For example first user medium. If you'd like to see campaigns for the medium, you can add a secondary dimension and make your reports even more granular. You can do this by clicking on this plus button. And going under traffic source. Just make sure you use the dimension first user campaign. If you use any other dimensions that don't have first user in the name, you might be getting weird results. You can also use the search to find the specific dimension you're interested in. Let's now take a look at the metrics you have at your disposal. In GA4, we don't have a bounce rate anymore, but instead we have engaged sessions. Each session is considered engaged if there are at least two or more page view events in a session, if there is at least one conversion event, or if the session lasts for more than 10 seconds. Though you can change this last part to up to 60 seconds in the admin section. Engagement rate here is basically the percentage of sessions that were engaged sessions, sort of the inverse of bounce rate. All the other metrics are pretty self-explanatory, except maybe the average engagement, which is just the whole engagement time divided by the number of users. At the end here you can find the convergence and revenue. You can also select a specific conversion action and see how it breaks down by your channels. OK. Let's take a look now at the traffic acquisition. This section provides detailed information on traffic sources that are driving users to your website or app. Such as search engines, social media and referral websites. The difference to the user acquisition report is that here all the channels from different sessions are counted, not just the initial ones. So if a user has returned to your site through multiple channels, all of them will be recorded here. So one visit might be recorded under organic search, but the second visit for example, would count towards e-mail. You can also see the dimension names start with session, not first user. Everything else is basically the same. You will find similar metrics, but instead of new users, you have only users and you have a few extra metrics related to sessions. 20. Engagement Reports: Engagement reports are a new feature in Google Analytics 4 that allows you to track user behaviour and engagement on your website. They provide a detailed view of how users interact with your site, including which pages they visit, how long they spent on each page, and which buttons and links they click. Engagement reports are crucial for understanding how users engage with your content and can help you make informed decisions about your website design, content and marketing strategy. For example, you may want to identify top performing content. And by analysing engagement reports, you can identify which pages and pieces of content on your website are the most engaging and attracting the most user attention. This information can help you optimise your website's content strategy and focus on producing more content that resonates with your audience. Or you could monitor user retention. By tracking user stickiness you can monitor how frequently users are returning to your website. This can help you identify areas for improvement and focus on building long term relationships with your audience. Here in the engagement overview you can find the summary of user's behaviour and some of the important user metrics. Like average engagement time, engage sessions per user, views, events and user stickiness. This is a metric used to measure how often users return to your website after their initial visit. It's a key indicator of user engagement and loyalty, and can provide valuable insights into the effectiveness of your website and marketing strategy. In the events report you can quickly view all the events that have been triggered in the selected time period. Here on top you can see top five events through time and on the right side the total number of each events for the same time period. These two graphs change based on the metrics sorted or page selected. Below you have a list of all the events and some basic metrics. If you want to see the parameters of a specific event, you can simply click on the event. And you'll be able to view all the events properties. Some events have extra parameters. If we take purchase parameter for example, you can see. That we also get information about payment type, shipping tier and so on. In the conversion report you will find all your conversion events. Some like purchases that have been automatically marked as conversions and all other events that you might have defined as a conversion. Like in the event report, you have your top five conversions plotted on a time graph, and you can isolate a specific conversion by hovering over its name. You can also get some more insights by clicking on a conversion event name. This time, however, you will see a breakdown of selected conversion by default channel group. On top you have all your top five channels showing the conversions through time, and below that you have a list of all the channels with conversions and their value. You can also change the breakdown to source, medium or campaign and see in more detail which channel drove the most conversions. If you wish to switch to a different conversion, you can simply do this up here. If at anytime you'd like to further narrow down this report, for example if you'd like to know a specific campaign performs on mobile devices, you can easily do this by adding a filter to the reports. Remember that on all of the standard reports you can filter out traffic this way by any dimension you have here. In the pages and screen report, you are able to see valuable insights into how users are interacting with all the pages and screens on your website or app. By comparing the number of page views for different pages. You can identify which pages are the most popular and which pages may need improvement. The same applies for screens if you're tracking your apps. If you want to see which pages are visited the most, you would sort by views. But if you'd like to know which pages got the most unique users, then sort by users. Sorting by the average engagement time will show you which pages get the most engagement or where people spend the most time on your website. If you'd like to see more rows on your table, you can simply do this here. You can also move from page to page by clicking this arrow. By default, pages are shown by page title. This can be a problem if you have multiple pages with the same title. Because all the metrics for different pages will be bunched together under the same name, which might be misleading. If you want to solve this or want to see the pages as you've seen them in their universal analytics, you can simply change it to page path. This will show each page's URL which is unique for each page. The last report in this section is for landing pages. These are the entry pages where your traffic lands first before they start moving through your website. This report shows session scope dimensions, which means that if the same person visits your website twice through different landing pages in two different sessions. Both of these pages will be listed here. But if the same person, this is 2 pages in the same session. Only the first page will be shown here. You can use this report to see which pages dragged the most traffic and if you'd like to dig deeper and understand from which channel or country visitors are coming, or even which devices people use to come to your website. You can do that with the help of a secondary dimension. You can add the secondary dimension here, then select the dimension you'd like to add. So let's just add for example device model. Now you can see a breakdown by landing page and the device from which this landing page was viewed. You can do this for any other dimensions that you have at your disposal. And depending on the insights you'd like to gain. One last thing. The difference between users and new users is that users is a primary metric that shows the total number of unique users who logged an event, while new users is a metric that shows you only users who interacted with your site or launched your app for the first time. 21. Monetization Reports: Monetization reports in Google Analytics 4 provide valuable insights into how users s 4 00:00:08.625 --> 00:00:10.917 are generating revenue for your business by tracking metrics such as revenue, transactions and average order value. If you set up your ecommerce events correctly in your web store, you will start seeing all your sales data here. I have left the link to Google documentation on how to properly set up your events in the lessons resources. Like in previous sections, the first report is an overview of all the most important metrics. Here you can find an overview of your total revenue. Purchase revenue. And add revenue through time. On the right side you can see your total purchases and new purchases. This will tell you if you are bringing in new clients or if existing clients are making repurchases. There are other interesting metrics below, such as how much revenue you are making per user, which items have been purchased, how much revenue did you make with your coupons, and so on. In the ecommerce purchase report, you will see a more in depth report for each individual item sold. On top you can see the number of views of individual items through time. And if it looks a bit cluttered, you can simply click on an item and it will get highlighted. On the right you have your two-dimensional graph showing views and add to cards on the same graph. This way you can easily see which items get a better ratio between them. This item for example, has lots of views but almost no end to cards, while this one is totally the opposite. You might want to drive more traffic to these type of items as people tend to add them to cart more often. Below both graphs you have a detailed report from which you can simply see which of your products get the most views, which are most popular and which make you the most revenue. This way you can plan and improve your sales activities, price changes and promotions accordingly. For example, this first item has the most views. But not the most revenue, so you might first want to focus on this other item. Seems to be performing very well, but doesn't get as much traffic. You can also change the breakdown options in GA4 now gives you six levels of custom categories you can use if you need to. This way you can group your products in any way you'd like and get reports for them. A similar report but for apps is an in app purchase. At this point it's still a bit in the early stages and will only give you a basic overview of which products have you sold, how many of them and how much revenue you've generated. The publisher ads, on the other hand, show you how much revenue you've generated within app ads. You have your metrics like ad impressions, how much exposure time ad unit got, how many clicks and total revenue. You can also break down this data by where in the app the ads were shown. The ad format and even the source of the ads. In conclusion, monetization reports in Google Analytics 4 are essential for tracking and optimising your revenue generation strategies. By regularly analysing these reports, you can identify areas for improvement and make data-driven decisions to improve the overall profitability of your web store and mobile apps. 22. Demographics & Tech Reports: In this lecture, we'll be discussing how we can use Google Analytics 4 to gain insights into the demographics and technology of your website visitors. Let's start with the demographics report. This report provides insights into the age, gender and interests of your visitors. By analysing this report, you can identify which demographics are the most engaged with your website or app and adjust your marketing strategies accordingly. In the overview section you can quickly check which countries your users are coming from as well as from which city. You can also have a real time report showing top five countries. If your company is preasent globally, then this card can show you which countries are most active at which time of the day. You can also have your audience's gender split and most popular age groups. This way, if you find that a particular age group is more interested in your products or services, you can tailor your marketing campaigns to target that age group specifically. In each of these reports, you can dig deeper and get more insights simply by clicking here. This will take you to the demographics detail report. If we now go here, you can see that you get more detailed information about each individual country and users from it. You have your engagement metrics here, as well as conversion and monetization. This way you can quickly check which audiences you should focus on. You can easily change the dimension grouping by clicking here. And then selecting the appropriate dimension, if we take a look at the age breakdown, we can quickly see the two age groups specifically spend more than the rest, so we could focus more of our marketing efforts on them. The second report is the technology report. This report provides insights into devices, browsers, and operating systems used by your users and visitors. By analysing this report, you can identify which devices and browsers are most popular and optimise your app or website accordingly. In the case of this app, there are much more users that use it on Android than on iPhone, as you can see from this platform breakdown. Again, here you have your real time report as the different regions of the world might prefer different platforms. You also have a breakdown by browser, device category and screen resolution. If you have an app connected to G A4 then you will also see these reports. The first report shows you the app versions popularity through time. Stability report and device models. Again, the tag details report show you more information about each technical dimension. Demographics and technology reports in Google Analytics 4 provide valuable insights into characteristics of your visitors and users and the technologies they use. This will help you easier define your target persona as well as optimise your technology stack to support the most used devices. 23. Advertising Reports: Google Analytics for Advertising reports provide you with a comprehensive view of your advertising performance across all channels, including search, social media, display and video advertising. Before you can use these reports, there are a couple of things that you have to set up first. The first thing you'll need to do is connect your Google Ads account to your GA4 property, and we showed this in one of the previous lessons. If you don't do this, then GA4 won't get any data from ads and the reports here will stay blank. The second thing you need to do is make sure you have at least one conversion event defined. You can quickly check if you do here. If you have an ecommerce website and you've set up your ecommerce events, then a purchase event will be set as a conversion event automatically. If you want to track any other conversions like lead generation or signups. You can do this. Just make sure you can mark those events as conversions. You can mark any event as a conversion in the admin section. And under the events. Then just click on this switch to make a specific event into a conversion event. After you do both of these things, you should start seeing data in your reports. In the overview report you will again see just your basic reports that give you an overview of what is going on. If you want to get these reports for a specific conversion or set of conversions, you can simply select them here and you will get filter data for those conversions only. This is super useful as you probably aren't interested in how all your conversions are performing at the same time as they may not be equally important. So you can just select one conversion like purchase and look at the reports for it. This setting will persist through all the reports will take a look at, so keep that in mind. Let's now check all channels reports. As you can see, we are still looking only at the purchase conversion. And now we can dig a bit deeper into the attribution for this conversion. The first thing you'll notice is the GA4 groups channels into what they call the Default Channel groups. This is their way of grouping sources that drive traffic to our website based on a preset of rules. If you want to know how GA4 groups channels, I've left the link in the lessons resources. However, what you can do is change the default grouping. To either source, platform, source, or medium, or even the campaign. And this can be very useful if you are UTM-ing all your marketing campaigns. And this way you'll know exactly where the traffic is coming from. After you select your grouping you can now analyse the performance and here in the table you have some useful metrics for that. You can quickly see how much you've spent overall, how much it costs per conversion, how much revenue you generate and what the ratio between the two is, otherwise known as ROAS. This can give you a good indication on which channels or campaigns are performing well, so you can double down on them or just see which ones you should optimise. The model comparison report allows you to compare how different attribution models impact the credit given to different channels for conversions. This can help you better understand the effectiveness of your marketing channels and how they contribute to your overall conversion goals. For example. We have here last click channel and we are comparing it to the data-driven model which is the default model GA4 uses. You can see that they are pretty similar and don't differ a lot except in the cross network and our organic social. By comparing these models, you may find that certain channel is given more credit for conversions under a particular attribution model. Which may indicate that this channel is more effective at driving conversions than previously thought. This can help you make more informed decisions about where to allocate your advertising budget and how to optimise your marketing strategies for maximum impact. Let's now check the conversion paths report. Understanding your users conversion paths can help you identify which marketing channels, campaigns, or pages are most effective at driving conversions. By analysing the touch points that led to conversion, you can optimise your marketing strategies and use experience to better guide users toward completing your desired goals. In this upper section you can track how different data models attribute conversions by a different channel. This time you can see the attribution is split into 3 sections. Early touch point, mid touch point and late touch points. The early and late segments both have the first and last 25% of touch points. While the middle section gets the remaining 50% of touch points. Then depending on the attribution model, you will see a different amount of credits assigned to each step. If for example we switch to less click model. You can now see that only the late touch points get credit for the conversions. This way you can identify patterns or trends in user behaviour that might be impacting your conversion rates. For example, you may find that users who visit a specific page on your website are more likely to convert, or that users who interact with the particular ad campaign are more likely to complete your desired goal. Here in the data table you get even more data for each conversion path. How many conversions and revenue you got? But more interesting is how much time and touch points it took someone to make a conversion through this conversion path. Simply put, a conversion path is the sequence of steps or interactions that the user takes before completing a desired conversion or goal. A conversion path can include a variety of the same or different touch points. Here you can see that conversion happen after three consecutive visits from organic search. And if we expand the list a bit. We will see a bit more complex conversion paths. For example, this one has three different touchpoints before the conversion happens. Now these are all the different ways your customers found you and what actions they took before converting. This can give you some good insights on where to focus your marketing efforts or you can even discover that people coming from a specific channel like organic search social media might later on come back multiple times before converting and this might mean that you might not be doing a good job of communicating your values on that specific channel. In conclusion, by regularly analyzing advertising reports, you can optimise your advertising strategies, improve your marketing performance and drive more conversions. 24. Editing and Creating Standard Reports: Now we're going to take a look at how you can customise premade reports to fit your analytics needs. The first thing I want to mention is that you have to have the right permissions if you want to edit the reports. Since we don't have those permissions in the Google demo account, I will show you how this works in another account. You can customise and report that has this pencil icon here. After you click it, you'll see a menu with settings on the right side. And let's just go through them one by one. The first group is called report data and it relates to the data being shown in this report. Let's click on the dimension first. As you can see, these are all the dimensions you can breakdown this report by. If I click on this dropdown here, you will see all the corresponding dimensions. You can set any dimension as the default dimension. Or remove a specific dimension by clicking here. You can also add new dimensions to the report. We can Scroll down and you will see all the dimensions you can add. The ones that can't be added to this specific report will be disabled and you won't be able to add them. Since we are looking at the pages report, we could for example add a host name to the list of our dimensions. Let's click apply. And you should already see your dimension here. You can do the same with metrics and add remove them as you wish. For example, let's just said. Views per session metric to our report. And click apply. And there you go. This metric has been added to the report. Next we have our filter section where you can add filters similarly. To what you would filter the data on the report itself? The difference is that this filter will be applied every time you open up the report. This might be more useful if you are making a specific report from scratch and want to have it filtered by specific dimensions. Similarly how Google Search Console reports use it? Next we come to the chart section. You can hide one or both charts and just have the table view if you don't find these charts useful. Since these charts only show top five dimension values, then can be useless in some reports, so it's good to have the option to turn them off. You can, however, change the type of the chart and change it either to a bar chart or line chart or even a scatter plot if you'd like to see the data in two dimensions. The scatter plot actually shows you all the data, so depending on your situation you might prefer this chart type. The scatter plot chart type takes the first two metrics as an axis and if you want to have different comparisons. You can simply do this by going to metrics. And putting some other metrics in the top two spots. Though for some reason if you do this and click apply. It won't update this chart here. You can refresh the page. Or just save the report to see it in action. The last section is called summary cards. Here you can create cards that can be shown on the overview report. You can add any dimension you have in this report, as well as any metric. If you add more than one then you'll be able to pick and choose them in the overview screen as well. Then just select representation of this data. Which can be any of these. And you're good to go. If you want, you can also filter the data specifically for discard. You can create as many cards as you wish for your overviews. After you click the save, you'll get two options. And they'll save the current report, or make a new report and save it there. If you're doing minor changes to the existing reports, you need these changes in the existing report. Just save it as such. But if you created a complementary report to the existing one, then you can save it as a new report and look at them both when you need to. You will need to click back to get back to your reports. If you want to create a brand new report from scratch, you can do so under the library. Then click on create new report. And select create detailed reports. You will be presented with an option to create your report from existing templates. Or you can start from scratch. Starting from a template is basically the same as modifying an existing standard report and saving it as a new report. Modifying standard reports is a great way to tailor them to your specific business needs and goals, and it can save you time and effort as you don't have to create a new report from scratch every time you want to see more details. 25. Editing and Creating Report Overviews: Let's now take a look at how we can modify the reports overview and make them more useful for your businesses. This way you can focus on specific metrics and dimensions that are most relevant to your business. By removing or adding sections. In cards, you can create an overview that provides a quick snapshot of the most important data. Let's go now to the engagement overview and click on the edit icon. You can see now that you don't have that many options here. You can move the cards around or remove them, but unfortunately at this time there is no way you can change size of the cards. You can, however, add new cards if you'd like. And after you click on the add cards, you will be presented with a bunch of pre-made cards. The cards are split into collections in which they appear. We can see the card that we created in our previous lesson here. And if you want to add it to the report, we can just select it. By selecting multiple cards you can quickly create your custom dashboard. There are also some other premade cards that don't fall into any of the existing collections yet, and you can find them here. If you create your own custom report with custom cards, they will appear here. After you've modified the overview report. You can save it or create a new one by clicking save as new reports. To create a new report overview from scratch. You can simply go again under library. Then click on create new reports and this time select Create Overview report. You will be presented with a black canvas onto which you can add any cards that you'd like. The ideas of report overviews is really good, but right now they're very basic. Still, modifying the standard report overviews in GA4 can help you create a more focused, clear and relevant overview of your business performance. This can improve your ability to make data-driven decisions, communicate insights to different stakeholders, and ultimately achieve your business goals. 26. Adding Custom Reports and Overviews to the Collection: If you start creating multiple custom reports, you will soon realise that constantly searching for them in the library is both time-consuming and annoying. Especially if you have a few reports that you use regularly. Thankfully you can add them to the same menu as you have your other standard reports, and in this lesson we'll take a look at how you can do that. For this, you'll need to go to your library. And here you can see that on top you have collections. And if you look carefully, you'll notice that they correspond to the sections in the reports menu. You have your life cycle search console and user. And each of those has sub menus like acquisition, engagement and so on. So there are two ways you can add your custom report to the menu on the left. If your report fits well in one of the existing collections and subcategories, you can simply edit that collection and add your report to it. Simply click on the edit and you will get a screen when you can modify this collection. You can add new reports to a specific section by dragging and dropping them. You can rearrange existing reports, or you can even remove the reports that you don't use. After you're all done, just save the collection and you will have your customer reports where you want them. If however you have created custom reports that don't fit any of the existing collections, or if you want to make your own custom company collection with reports that are important to you and don't want to change the existing GA4 structure. Then you can create a new collection. Let us quickly go through this process to show you how you can do this. First, you'll need to create a new collection. Again, GA4 offers you some predefined templates you can use, but we'll just start from scratch. The first thing you want to do is name your collection something that makes sense not only to you, but to everyone looking at the reports. Think about what connects all these reports together. It can be a specific project use case or maybe even for who the reports are for. Like management. Keep in mind that collections are displayed in alphabetical order based on the collection name in the report navigation. Let's just name our test first collection. Next. You can create a topic. The topics are meant to hold a group of similar reports, and each topic will hold up to 10 reports and one overview report. Let's name our topic ecommerce. Since the overview report functions as the topic dashboard, you can only add one such report to each topic. You can select the appropriate overview report here and drag it to this topic. Next, you can drag all the reports that you want to the detailed report section. Let's for example just add 2. Right now. We could create more topics and add more reports, but for now we'll just save this collection. After you save the collection, there is one more thing you need to do before it will get visible in the reporting menu. So let's go back and you can see our collection hasn't been added yet. What we need to do is find it among our collections and publish it. We can do this here. And after we do that. It will appear in the menu. You can always unpublish the collection or even delete it if you don't need it anymore. Managing collections is super straightforward, so you have a lot of custom reports. I suggest you use it to group them together. 27. Explorations Interface Overview: In this section we will get to know the tools to create more advanced reports in GA4. The section where you can create these reports is called explore and you can access it here. The first thing you'll see is that you get different exploration techniques you can use to gain deeper insights into your users and their behaviours. You can start from a blank exploration and make everything from scratch or you can pick up one of the preselected ones. You have your freeform exploration with different visualisations, your funnel exploration, exploration and so on. You can also go into the template gallery where you get even more premade templates. Underneath you will see all your created reports which you can revisit anytime you need them. We'll go through individual exploration techniques in later lessons, but for now let's just click on one of the templates and create one. As you can see. The interface is split into two parts. On the left side you have all the settings for the report and on the right side you have the output of those settings, basically meaning your reports. Let's first look at the settings part of the interface. This is split into two sections, variables and depth settings. Variables will stay the same across multiple different reporting styles, while the tab settings will change depending on the technique you will use. In the variables column. You can modify the exploration name here. And choose the date range with the standard G A4 date picker. Then you can add or modify your segments dimensions and metrics here. In your exploration report you can only use those segments, dimensions or metrics that you have available here and you can add more by clicking on this plus icon if you want to add a new segment. You can do it here. You will be able to create a custom segment or choose one from the suggested list. You have different templates that help you create segments in Ga4. And it has a predictive segment that they feel based on the behaviour of your visitors. Once you select the template, you can then modify it as you wish. You can have more conditions based on AND or OR. You can simply select a condition based on a specific event or dimension value. Then just choose the condition and all the values you'd like. As soon as you modify the segment, you will see here on the right a short summary of how many users in this case have been included in this segment. You can also add additional conditional groups. Or even sequences of steps that must happen for users to enter this segment. If there are some specific cases you want to exclude from this segment, you can also do this here. Basically the same rules apply to the exclusion group and you will see it as a cut out here on the right. After you are done with your segment, just name it and save it. Then you can use it in your reports. Adding dimensions and metrics is a bit simpler as you can just select all that you'd like to use and click import. The same goes for the metrics. Keep in mind though that you can only add 10 segments, 20 dimensions and 20 metrics to each exploration. You can also remove any of them by clicking on this X button. The second column is step settings. And as I mentioned, the options here will vary based on the exploration you have selected. You can switch between different explorations here. One more thing to note is that you can have multiple tabs for different techniques in the same exploration. All you need to do is click this plus button and select the technique you wish to use. Then you can personalise that specific tab within the tab settings. You can also remove the tab or duplicate it if you'd like. Here on the right you also have a share icon and an overview of data sampling icon. That's it for the general overview of the exploration interface. Next we'll go deeper into each exploration. 28. Free Form Exploration: With freeform exploration in GA4, you can analyse data with a high degree of flexibility and customization. You can create tables or graphs, rearange range, rows and columns, compare metrics and group data. Additionally, you can apply segments and filters to refine your analysis and create segments and audiences from your selected data. First we'll take a look and explain all the different options the freeform exploration offers. Then we'll create a real life ecommerce example. Let's create a free form by clicking this template. Here we have all the different visualisations we can use in the freeform exploration. Let's go through each one and explain all the different settings you can use. We'll start with the table visualisation. Here at the top you can build different segment comparisons within the table and see how they stack against each other. You can add a segment by dragging and dropping it. Clicking on this empty cell and selecting it from the list or just double clicking it here on the list. In the same way you can also add dimensions and metrics. As soon as we start adding different segments, you see that they show in our table, and the colour of the segment corresponds to the colour of the bar in the table. So you can easily distinguish between different segments. The pivot option here allows you to choose the first grouping of data. Right now you can see the segments as first column up here. If we change it to the last column, the data will first be grouped by the city and then by segment. The same goes for the first and last rows, just that segments get moved to the row instead of columns. Like so. You can see that the segment is now the first grouping factor. In the row section, we can control how rows are represented. Let's first remove the dimension from the columns. And add a country to the rows part. I'll add it above the cities just to easier show some other grouping functionalities. The start row setting basically defines from which row the table starts. For example, if you want to start from the 5th row, you could do so by changing this to five. Show rows basically sets the number of the rows that will be visible in the report. And you can select this to be up to 500. The nested row option gives you the ability to group or nest rows based on the previous dimension. Right now all the combinations of both dimensions are shown one after another, sorted by the total active users. But if you'd like to see how each country breaks down by cities, you can see set this to yes and you will have all your cities grouped under the same country. And the sorting will be done on a country level then within that country. Per city. If you have more dimensions this will go even deeper, but it can get pretty unreadable if you have lots of dimensions with lots of values. Now, even though this visualisation is useful, you might prefer to see your top countries paired with top cities without the need to Scroll down too much. You can do this by creating a 2 dimensional table where you move the cities to the column section. Now you can see that it becomes a bit easier to read. Let me just remove the segments for now so it will become even more obvious. Now you can easily see which cities and which countries pair together. Though this might not be the best example as each city can be present only in one country. That is why there are almost all zeros everywhere else. Before I show you another dimension that makes more sense, I just want to show you this last option. If the dimension you have selected for columns has a lot of values and you want to see more than five here up top, then you can simply increase this number and you'll have more value shown. Now let's switch City dimension with device category. And now you can see which countries use which devices more often. Here in the value section you can add your metrics. Currently we have our active users, but we could add any metric that we have at our disposal. We could for example a transaction in the mix. If you're making one-dimensional table, you could add more metrics and make a 2 dimensional table this way. But if you already use rows and columns, don't add too many metrics as this will become very confusing. To represent the data in the cells, you have three different options. You can show it as numbers. And a bar chart what we are seeing right now. If you just want to see the numbers, do so by changing to plain text option or if you change to the hit maps, you'll see these cells. Coloured which? They get progressively darker with higher values. In this example, the US is dominating by such a big margin that there is no gradient, basically just two colours. The last part is filters. Here you can define which data you wish to show in the table. You can filter either by dimensions or metrics, and they work similarly as we've shown in the standard reports. OK, that's it for the table view. Now let's go to some other simpler visualisations. The first one is the donut chart, which is particularly effective when displaying data with a limited number of categories or when comparing a subset of data to a larger group. If we add multiple segments, you will get multiple doughnuts which you can compare side-by-side. In the breakdowns, you can select the dimension that you wish to break down by and a number of slices that should be shown. The rest of the dimension values will be grouped under the name other. Let's now move to the line chart. With this visualisation you can easily follow trends and patterns overtime, and it's very useful for analysing data that changes frequently or data that has a continuous range of values. In all the following visualisations, the segment comparison is visualised in a side-by-side manner, so I'll just remove them now for simplicity sake. In the granularity setting you can choose by what time period your data should be grouped. By default this is the day, but you can change it to an hour, week or month if your date range is big enough. In the breakdown you can choose how many dimension values get shown on the graph by changing this number. The most interesting part of this visualisation is anomaly detection. This is where GA4 tries to identify outliers in your data using a line chart. You can change 2 settings. Training period and sensitivity. The training period lets you set the number of days prior to the selected date range to be used by the anomaly detection model to calculate the expected values if you have your date range set to the first week of the current month and a training period of seven days. Then the data will be pulled from the last week of the previous month. Sensitivity, on the other hand, sets the probability threshold below which anomalous data will be reported. A higher sensitivity means that more outliers will be shown, while lower sensitivity will show fewer of them. If you click on a line you will actually see how the model predicts the values and which ones fall out of range and get marked. You can also zoom in on the graph by selecting a region. And you can reset the zoom up here. The next visualisation is scatterplot. It will help you identify correlations between data points, such as identifying whether there is a positive or negative collaboration between 2 metrics and identifying patterns in data. You need to choose two metrics that you want to compare and put them on X&Y axis. It works similar to the Scatterplots we've talked about in the standard reports, but here you also have the option to add third metric to the graph by using the bubble size option. These points will then grow in size by the amount of this third metric. The next visualisation is a simple bar chart that shows you the summarization of specific metric broken down by a dimension. And the last one is Geo map which can show you selected metrics broken down by different geographical locations such as city, country, continent and so on. That's it for the different visualisation options. Now let's go to our example. Let's say we want to know which items get sold by which channel. For example, if we are doing an item specific marketing campaign like connecting with influencers or doing advertising, this will give us insights if we're doing this well. First, let's go back to the table visualisation and add a new dimension called the Item name. We also want to add 2 new metrics called item purchased and item revenue. Now let's add the item name to the rows and let's substitute the columns dimensions with the first user medium, since we want to know which initial marketing activities drove the buyers. Now let's replace the metrics with item revenue, and this is what we get. If you want to exclude a specific channel, you can quickly filter it out by right clicking on any cell and then choosing to exclude this section. This will create a filter for you. In conclusion, freeform exploration is a very powerful tool that allows you to dig deeper in your data and pull out some interesting insights. 29. Funnel Exploration: Let's now check the final exploration. This exploration lets you visualise the steps your visitors take to complete a specific goal. It allows you to quickly see how well they are succeeding or failing at each step. Along the way, there are multiple funnels you can create. The most common one for ecommerce is the checkout funnel, where you track each step of the checkout process. The since you can build custom funnels in GA4. You could also make one for your lead generation per processes, or if you're building a SAAS, you might be interested in registration funnel or even the onboarding funnel. Since GA4 is super adaptable, you can make almost any funnel you'd like to track. Let's first show how to create a generic funnel and explain all the settings. Then I'll show you a real life example. To create funnel from the template you can click here and as you can see AG4 already created a test funnel for you. That has all the steps and basically tracks everything from the first engagement to the purchase. The first option you can change is whether you want to see a classical funnel visualisation or if you want to see trend lines through time for each step. The second one would be useful if you'd like to track how your final performs overtime, but for general purposes you'd mostly be using the standard funnel. The next option helps you visualise funnels, where people often do some actions in between steps or enter funnels at different stages. By default, GA4 only tracks users entering the funnel at the first step. So in this example, if you completed the first visit you will enter the funnel. But if this isn't your first visit, then you won't be counted in this specific funnel. In the open funnel you can enter at any step and you can see. If we turn it on now, other steps get much more traffic. This usually doesn't happen, but in this specific case, because the first step is only for first time visitors, this makes sense. OK, so let me explain what is going on. As you can see, this amount of people entered the first tab and the bottom part shows how many of those continue to the second step, while the top part shows all the visitors that enter this funnel at this second step. In this case, those might be all the users that came back in another session. Then in the third step you can see that there is some visitors that didn't complete the third step from all the previous ones that were presented in Step 2. But at the top we also have some new visitors entering this step. Then out of all these, only a fraction completed the purchase. If it looks confusing now, I'll click quickly explain it again at the end with a real life example. For now let's just turn it off so it's not distracting. Then you again have your segments which you can compare side-by-side. So let's just add two to see how it works. If one of the segments is a bit low and you can't quite see the conversions, you can just scroll over the funnel and you will be able to zoom in. This wavy line indicates that this pillar should be much higher, but was cut off. The next section is called Steps, which will come back in just a second. Then you have your breakdown by dimension that you can see here in a table. If you don't care about that, you can simply remove it or replace it with any other dimension. Next, you can enable the elapsed time, which shows you the time it took on average for all users to complete individual steps. This time is applied in the step and shows the time it took to come from the previous step. In the next action you can add any event or all the page dimensions and this will basically show you all the actions that users completed right after a specific funnel. This way you can see where people are going after that step. If we add an event name just to showcase it. You can see that after the first step some people continued to the next step or session starts event, some go to page view, some go to view item and so on. At the end you have your filter section to filter a specific subset of traffic if you wish so. Now let's go back to steps section and let's create our real life funnel. What we'll be doing is creating a checkout process funnel to track what visitors are doing from the time they view a product to the time they purchase it. Let's now edit the steps. What you'll get is an interface where you can define each individual step. So let's first remove all the steps. And then we can get started. Let's also name our event view product. And thankfully, Google has a set of recommended ecommerce events we can use for this purpose. Have left the link to the list of these events in the resources part of the lesson. For this first step, we'll use the view_item event. If you want to you can add multiple conditions either with or or end conditions and you can even filter down specific conditions with extra parameters. As you're adding conditions and step, you will see here on the right a realtime summary of how many users would complete this funnel in a given time frame. To add a next step just click on add step. We will name this step add to cart and send the condition where the event equals. add_to_cart. After you add the second step, you get some extra options you can set. You have an option that this step needs to be followed indirectly or directly. Indirectly basically means that some other actions can happen between these two events. But directly means that this step has to be absolutely next action after the previous one. Be careful with this setting as sometimes some events might trigger in between and your funnel will have a huge drop off at this specific step. Another thing you can enable is the maximum time it can take between these two steps before someone is considered a drop off. As you can see, you can choose multiple time periods. For now, let's just make this funnel as simple as possible, so I'll just disable this option. Next we want to add a new step called started_checkout. And for the last step let's add. A purchase completed event. Called Purchase. OK. We can already see that in this specific time period, this amount of people completed the funnel we've created and this can be an indicator that our funnel actually works. If you'll get here a 0, but you know people are completing your funnel, then double check all the steps. Now let's save the steps and check the whole funnel. In this are example you can see that we get a bunch of item views but the barely any add to carts. What you could do are two things. First you can zoom in the funnel or you can remove this first step called item step and focus only on the checkouts part of the funnel. This is just one way they can enter the funnel at this step by I hope it makes more sense now. In conclusion, funnels are a great tool to optimise your user journeys through your website or web app in easy and. Visual way. 30. Path Exploration: Path exploration in GA4 helps you analyse the paths that users take on your website or app. This can help you identify popular pages or screens, as well as potential bottlenecks in the user journey. For example, you might discover that many users drop off at a particular step in the conversion process, indicating a need for improvement in that area. Let's now create a path exploration and go through the settings. If you are in the exploration section, you can create the path exploration either from scratch by clicking this blank template or by clicking on a premade one. Let's click on this one. In the settings part. Of the path exploration, there aren't that many options you can change. You can add one segment if you'd like. But you can't compare multiple segments like in some other explorations. You can define different node types here, but be aware that you can only use the event name or screen name dimensions for the note types. In the view unique nodes only switch is enabled. Then only changing values of your nodes will be shown. If there are multiple events tracked for each page or screen, this option will display only one note for each consecutive event. For example if I disable it. You will see that under page view events. Another page view_event has appeared. However, if the user performs the same event after they've done another event. That specific event will be visible in the path. The breakdown dimension setting will help further breakdown the traffic. Let's for example add the device category here. And now you can see a detailed breakdown by device category. If you hover your mouse over here or if you look here at the bottom. The whole path for that value will become visible. To apply the metrics you can add them here in the values. The only thing that is different here compared to other explorations is that currently only two metrics are supported and those are event counts and total users. You can also add your regular custom filters here at the bottom to filter out only the traffic you wish to track. But you can also filter out specific pages or events simply by right clicking on the path node and selecting exclude node. If you want to exclude this node only from this specific path you can do so with selected only. But if you click from all paths it will be removed altogether from the whole path tree. You can also remove this filter by clicking this X here. One more interesting thing you can do with path exploration is you can look in reverse. So for example, you want to know how people are completing purchases and how they're entering this specific funnel. You can do this by going here and clicking start over. Then you get to select either the starting point, what we've been looking at now, or ending point which will show all the paths that lead to that last action. So let's do this now and select the event name as our ending point. Then let's search for purchase event. And here you can select any event or page URL you wish. I just chose the purchase event as it might be interesting to see how people are entering this funnel. Now you can see that the path is reversed and the last event is for our purchase event. If you want to know which pages people visited before triggering this event, we can first change this event name to page path and screen name. Now we see that the order complete page trigger this event, which of course makes sense. Then we can go back in time by simply clicking on this nodes. And slowly we can see that at some steps, people were coming from other pages to individual nodes. This can be very useful if you want to set your pricing page as the final node just to see what steps user take before landing on your pricing page. Or you might trace back your registration or login pages as well. Then you can optimise the pages the drive the most traffic to your registration pages. This can help you optimize your user journeys and improve your overall user experience. 31. Segment Overlap Exploration: We've mentioned segments a lot of times already in the previous explorations. We've also shown how you can create them. But now we're going to be talking about how you can compare up to three segments with the segment overlap exploration. Segment overlap exploration is useful for analysing the overlap between different segments of your audience. By using this exploration technique, you can identify which groups of users have similar behaviours and characteristics, and which segments have unique attributes. To get started with the report, you can use a premade template, though you'll need to scroll a bit to the right to see it. After it opens, you can already see that there are three segments preselected here. And on the right side, you see the overlap between those segments. And below it's a detailed breakdown for each combination. If you move your mouse over the different parts, you will highlight and show the metrics you are tracking. The cool part is that based on this subsegments you can also create new segments which you can apply to other exploration techniques and Google Analytics reports. You can do this by right clicking on any segment here in the graph. Or below in the table and then clicking create a segment from selection. Here in the settings column you have the three segments you can compare. Below you can add different dimensions that will breakdown this data even more, but this will only show in the table below. Which is similar in functionality as a freeform exploration we discussed in one of the lessons. You can also add multiple metrics and custom filters to narrow down the data. Though if you'd like to know for example how many of your US-based visitors that come from paid channels, do that through mobile devices. You can simply replace these three segments. Now the graph gets a bit more overlap between all these segments. You can take this visualisation and make some data-driven decisions on how you want to approach your paid advertising campaigns. 32. User Lifetime Exploration: User lifetime exploration in GA4 allows you to analyse the behaviour of users over a period of time, from their first interaction with your website or app to their most recent activity. This report can give you valuable insights into user retention, engagement and loyalty. For example, you can find out which of your paid campaigns generated the highest lifetime value, or which channels will derive the most revenue in the next seven days. To create a user lifetime exploration, you'll have to scroll all the way to the end of templates and then simply click on it. A thing you can quickly notice is this. This report is very similar to our free form exploration. And indeed it has all the same settings without the option of selecting different visualisations. You have your segment, section, rows, columns and all the settings for them and of course the metrics part. The only difference to freeform exploration is which metrics can you choose. And here you can only choose lifetime metrics, predictive metrics, total users and active users. Now let's explain these metrics and create an example that will give you a better idea on how to use this reporting tool. In this premade report, we have all the users broken down by the first medium they've arrived to the website. Then we have our total users from each medium and the average lifetime value of each medium. This metric tells you how much value this medium is bringing in in dollars, or how much customers from this channel are spending on average in their lifetime. The average lifetime duration metric can help you understand which users were most engaged on your website and through which medium data arrived, for example, even though referral traffic generates a bit higher LTV than organic traffic. The organic one stays longer on your website. The last metric shows you the average number of transactions for each medium. OK, let's now do our example and try and find which medium is going to bring us the most value in the next seven days. For this, we first need to create a new segment. Let's now go under the predictive tab and select likely seven-day purchasers. Then save and apply the segment. And now we can see the prediction on which channel will generate the most revenue from the potential seven day purchasers. One of the downsides of the predictive metrics is that you need to have a substential amount of both active and inactive users for a longer period of time. So bigger brands will have an advantage over the smaller ones who need more time to build a stable user base. 33. Cohort Exploration: First, let me explain why cohort exploration is useful. Cohort analysis allows you to group users who share common characteristics or experiences within a defined time period. By examining the behaviour of these groups, you can discover patterns and trends that can be used to optimise your marketing efforts, user experience and overall business performance. For ecommerce businesses, cohort exploration can help you answer questions like. How do different marketing channels influence customer behaviour? What are the retention rates for first time buyers compared to repeat customers? How do seasonal promotions affect customer lifetime value? By finding answers to these questions, you can create more targeted and effective strategies for your business. Let's now take a look at how you can create a cohort exploration. In the exploration section, you'll need to go all the way to the end, and here you'll see the cohort exploration. Now let's click on it. The first thing you'll see is a bit different data representation so Let's first take a look and explain this cohort table to help us better understand the data. This table consists of cohorts based on weekly user acquisitions, with each row representing a different week. And each column in the subsequent week. In the first column we have the number of users acquired during that week and then the number of these users who returned in the following weeks. For example, in the first week we acquired a significant number of users and we can see how many of them returned in the following weeks. Notice the drop in returning users as the weeks go on. This is a common trend and highlights the importance of user retention strategies. Since the second week started later, we only get four weeks of data. The third week was even more recent, so there are only three weeks of data and so on. OK, now let's go to the Settings tab and explain the options we have. At the top you have your segments, which work the same as in other explorations. You'll basically have multiple tables for each segments you look at. Then we have cohort inclusion. It defines the initial condition a user must meet to be included in a cohort. In other words, it determines which group of users will be analysed based on a common characteristics or experience. This common characteristic can be in any event or action taken by the user on your app or website. There are several predefined inclusion criteria like first touch any event. Any transaction and then any conversion. Or you can use your own events. Return criteria is another essential component of cohort analysis, as it defines the condition that users must meet to be considered returning. Within the cohort, of course. In other words, it determines which users from the initially included cohort have taken a specific action or meta specific condition during the following periods. Here you also have some predefined options or you can select your own events. Cohort granularity refers to the time frame used to group users within a cohort analysis. It determines the period over which users are analysed based on their inclusion and return criteria. You can use daily to understand short-term user behaviour and for identifying daily trends or patterns, weekly for examining user behaviour over a more extended period and can be useful in identifying trends influenced by weekly cycles or events or monthly, which is ideal for analysing long term user behaviour and understanding the impact of seasonal events or marketing campaigns. That spend several weeks or even months. Cohort calculation determines how users activity. Throughout the exploration period contributes to the metrics calculation. In each cell of the cohort table, there are three options to choose from, standard, rolling, and cumulative. In the standard calculation it sells, include all cohort users who make their return criteria for that specific period, regardless of their activity in other periods. This type is used for analysing user behaviour within specific periods without considering their actions in other periods. The rolling calculation includes all cohort users who made their return criteria for that period, as well as all previous periods. The metric displays the total value for that individual period. Rolling calculation is helpful for understanding how user behaviour accumulates overtime and how many users consistently meet the return criteria to the exploration period. In cumulative calculation, each cell includes all cohort users who made the return criteria in any period within the exploration. The metric displays the cumulative total value for each period. This type is ideal for analysing the overall performance of a cohort, taking into account all users activity throughout the exploration period. As with other explorations, you can also breakdown the cohort report by any dimension you'd like. So for example, if you wish to know how the traffic from a specific medium performs overtime, you can add a first medium dimension. In the value section, you can choose the metrics based on your objectives and insights you want to gain from your analysis. Here we have the active users, but if we wanted to know how much revenue returning users are bringing in, we could change it to purchase revenue for example. Now you can see that this specific cohort revenue wise is performing quite good. In the metrics type you can select either the sum or per cohorts user option. The sum, as the name suggests will show the sum of all metrics, while the per cohort user will show the metrics for each user. There are some limitations of cohort exploration. It is placed a maximum of 60 cohorts and when using a breakdown dimension shows only the top 15 values. Also, the demographic dimensions are subject to thresholding for user anonymity, which may exclude users from the exploration if their cohort size is too small. To sum up, cohort exploration is a powerful tool for businesses to gain valuable insights into customer behaviour and marketing performance. By using it, you can uncover trends and patterns that'll help you optimise your strategies and drive growth. 34. Debug View: Let's now take a look at how you can monitor incoming events and parameters in real time by using the debug view. Debug view helps you confirm that your implementation and data collection is accurate and working as intended. It will help you identify misconfigured events, tags and missing parameters. You'll be able to quickly diagnose and fix issues, ensuring accurate and reliable data collection. You can find the debug view under admin. Then in the property column you can click on debug view. To get it together data you'll need to install and configure the Google Analytics debugger extension for Chrome or enable debugging for mobile devices using Firebase SDK. I have the link to the debugger extension in the lesson resources. After you have the extension installed, you'll need to go to your website and enable it. Then simply refresh the page. After you do this, you will start seeing realtime visualisation of incoming data from your website or app. Let's quickly show how you can do this. So let's go to the example page and enable the debug extension. Now let's refresh our page. And then go back to our GA4 and you can see that events are starting to come in. This main panel displays a live stream of events as they occur. Each event is represented by a card containing the event name, timestamp, and additional details like the event parameters, user properties, or errors, if any. The events are sorted in reverse chronological order, with the most recent event at the top. Clicking on an event will expand it to display more detailed information, such as event parameters and user properties. Also you will see potential issues or errors. This makes it easy to inspect individual events and diagnose issues. Here on the right you have an overview of the top events in the last 30 minutes. You'll also notice that you have different event types, each coloured differently. General events are coloured blue, conversion events green and error events red, and you can filter them out by clicking on the individual icon. Right now I only have general events so I can show you this. If you have multiple devices connecting to debug view, you can switch between them using this device selector. This allows you to monitor data from different sources simultaneously. If there are any issues with an event, such as missing parameter or misconfigurations, debug view will display an error indicator, usually a red exclamation mark, alongside the event cart. This helps you quickly identify and resolve problems. In summary, the debug view is a great tool to visualise realtime data coming in, in the GA4, making it an invaluable tool for data validation, troubleshooting and analytics optimization. 35. Events & Conversions: In this lesson, we'll show how you can create custom events and conversions in your GA4 There are multiple ways you can send events to GA4 property, and most of them we've already discussed in the previous lessons. In this lesson, we'll mainly focus on how to create custom events within the GA4 interface. With an event driven model, GA4 offers great flexibility in tracking user interactions. This allows you to capture a wide variety of events from page views to specific button clicks, providing more comprehensive insights into user behaviour. And you can achieve this without the need to modify your code or require technical knowledge. Also, there is no deployment process and the events will start triggering immediately as we will show later in an example. OK, so let's create a custom event. For this you'll need to go under admin. Then in the properties section, click on the events. Here you'll see all your already triggered events such as page view click. And any other custom events you might have created. To create a new event, simply click on the create event button. This will show you a list of all custom events. Then you want to click on the create button again and you'll get your event configuration screen. By clicking in the event name field, you'll get all the Google recommended events listed. If you're not triggering recommended events anywhere else, you can use them for your custom events. Otherwise, I'd suggest you use your own names. For example, if we want to create an event where a user views our pricing page, we could name it page_view_pricing Since we are going to do an example of a purchase event, let's just name ours purchase_done Now we need to define the conditions. Under which this event will fire. Since GA4 is an event based analytics tool, every data point is sent as an event. So the first thing we need to select is which event we want to use for our created event. I know this might sound confusing but bear with me. So for example if we want something to happen when a person views a specific page, we would need to first limit this to event named pageview. If we want something to happen when a user clicks on a link, then we'd want to use the event named click. Since we'll be tracking the order competition thank you page, I'm going to say that the event name should be equal to pageview. Now if we'd save this event as it is, it would trigger on every page view, which of course we don't want so we can keep on adding conditions. In our example I want to trigger this event on a specific page, so I'll add a new condition and select the event parameter. You can use any parameter that has been set in GA 4 and you can compare it to a value. For our purpose, I'll take the page location parameter. Since I know the URL of the thank you page, I'll just write order-received in the value field. If you don't know your URL then simply create a test order and check your URL on the competition page. Since the operator is set to equal, this of course won't work as this isn't the full URL of this page, so I'll need to change the operator as well. In the operator list you have a lot of different operators you can use, but for our example we'll need the "contains" operator as our target URL contains this specific value. In the parameter configuration you can choose to copy all the parameters from the original event to this new custom event or not. You can also modify individual parameters if you need to. And I've left a link to more details in the lessons resources. After we are done, we can save the event and let's do a test if everything works. I have here open the debugging view for this property so we can check if the event gets triggered. Now let's go to our testing store and add something to the cart. Then let's go to the cards. And proceed to the checkout. And let's just place the order. Now, as this is done, let's go back to our debugging view. And here we can see that the event was successfully triggered. Now, what we also want to do is mark this event as a conversion. The usual way you do this is by searching for the event under the existing events here and marking it as a conversion by checking this switch. But since this is a new event, it can take up to 24 hours for it to appear here so what we can do is go under the conversions. Then we can just add the new conversion event manually. You just need to make sure that the event name you input here matches perfectly to the event name you've created. Now if we go back to our store and refresh the page just to trigger the same event again, we should be able to see it in debug view. Let's go and see if it worked. OK, and you can see that the event has been triggered again and that this time it's coloured green, which means that this was considered a conversion. Creating custom events can really simplify and speed up your workflow, but there are some limitations you should be aware of. They don't apply to historical data, and there is an upper limit of 50 modified or created events per property. Modifications take at least an hour to take an effect and are calculated client side. Additionally, custom events cannot be created or modified based on parameters from the items array. 36. Audiences: In this lesson, we will be focusing on GA4 audiences. We will discuss the importance of audiences, understand the key differences between audiences and segments, and explore various applications of audiences in your marketing efforts. GA4 allows you to integrate your audience data with other Google products like Google Ads and providing a seamless way to target your ads and maximise your advertising ROI. In GA, audiences are a dynamic groups of users. Then you can create based on specific criteria like demographics, behaviour and technology. Once you've created an audience, you can use it for retargeting, reporting and for running AB test experiments. On the other hand, segments are static and used primarily for analysis within GA4. They help you understand your website data by filtering and isolating specific subsets of users or sessions. While segments are available for insights and understanding user behaviour, they don't have direct applications in marketing campaigns like audiences do. To create an audience, you can go under admin and in the properties section click on audiences. Here you will find some of the predefined audiences GA4 creates for you, like all users, purchasers and non purchasers. And you can also create a custom audience here. The interface that opens is very similar to the interface you used to create segments. Here you have the templates you can use to quickly create an audience, and at the top you can create it from scratch. The audience build the interface is almost the same as the segments builder, so I won't explain it in detail. Again, the difference is here on the right where you have some extra audience settings. The membership duration setting is the number of days users stay in this audience once they're added to it. The default is set to 30 days and the maximum is 540 days. While the audience triggers let you trigger events when users become members of this audience. You can then analyse these events and even mark them as conversions if you'd like. OK, let's now create an example audience of our best customers. Let's define our top customers to be everyone whose order value is over $300 or who has created more than 10 orders. So. How we could do this is first add the purchase event. And then add a parameter condition. For the parameter we have a bunch of event properties. But what we want to know is how many times this event was triggered. So let's just use the event count parameter. Then we set it to greater than 10. And if we want, we can also peg it to a certain time period in which this condition needs to be satisfied, for example in the last two months. Then we simply click apply. Next, let's create. an OR statement and add a new condition for order value. So let's just quickly search for purchase again. And now add a value parameter, then select the greater operator. And for the value will input 300. Now we could name this audience as best customers and save it. But before we do that, I want to show you another example. So let's just remove all the conditions and start from scratch. What we want to create? Is a cart abandonment audience for all those people that added something to the cart but never completed the purchase. We can then use this audience to target specific users with ads and try to bring them back to complete the purchase. So how would you do that is to add a new condition. And this time let's select. Add to cart events. This will create an audience of everyone that added something to the cart. But we still want to exclude those who completed the purchase so we can click on the add group to exclude button here. Then we want to add a condition for everyone that trigger the purchase event. So let's select the purchase event here. We might also want to permanently exclude everyone that purchased at our store, so we can select this option here. And now we have our CART abandonment audience. I've left the link to some extra examples in the lessons resources if you're interested. OK. Let's just close this. There's one more thing I wanted to mention. And that's that. You can click here on the list on any audience you've created and it will show you some basic data about the audience, but I don't find it very useful. There are also some things and limitations you should know about audiences. First of all, they are not retroactive. This means that they will only start gathering data from the time they have been created forward. Another thing is that after you create an audience, you can't modify it. You do have an edit option, but you'll find out that there is nothing you can change except add or remove the audience event. You can, however, duplicate the audience you'd like to modify and then archive the old one. But if you do that, keep in mind that this new audience will start gathering data from that point forward. 37. Custom Dimensions & Metrics: Custom dimensions and metrics are powerful tools in GA4 that enable you to track unique aspects of your website and user behaviour that aren't captured by default. By using custom dimensions and metrics, you can tailor your analysis to suit your specific business needs and gain a deeper understanding of your website performance and user interactions. Custom dimensions are like additional attributes that can help you segment your users, sessions or events based on your unique requirements. They can include information such as user preferences, content categories, or any other custom data points relevant to your business. For example, if you're running a SaaS company and you have different subscription plans, you could add a custom dimension with the name of each plan to specific events, like for example the purchase event. Then you'll be able to use this dimension in all of the reports in GA4. Custom metrics on the other hand, are user defined measurements that allow you to track specific actions or values not covered by GA4 default metrics. This can include metrics like the number of times a specific button is clicked, the number of logins, or the discount amount. To be able to leverage the custom dimensions or custom metrics, you'll first need to send custom parameters with all your events. After you create and set custom parameters with your events, you can verify them in the debug view. So let me quickly show you how. In the admin section, click on the debug view. Now let's go to our website and refresh it so we trigger some events. Each event here has some extra properties which you can see by clicking on the event itself. And these are the properties we'll use to create our custom dimensions and metrics. So for the dimension we could use the. Ignore referrer. Which can be either true or false, and for metric we want something countable. And the closest thing in this example is percent scrolled. Now that we understand what we're working with, let's create our first custom dimension. For this, go under the custom definitions and create a new dimension by clicking here. We'll need to name our custom dimensions something recognisable. Then we'll need to select the scope. The scope can either be user level or event level. User level scope tracks attributes unique to individual users, while event level scope focuses on specific events or interactions on your website or app. You can add a description so you don't forget what this dimension is for. And the main thing is to select the correct parameter for this dimension. When we were looking at the debug view, we chose ignore referrer, so let's just find it here now. When you're making these custom dimensions, you would select the custom parameter that you wish to segment by. Then we can save this dimension. And that's it. A similar process is for metrics. You can go here. And then create a custom metric. At this point you can't select the scope of a metric yet, but in the future you will be able to select them as in custom dimensions. Then you again select your desired event parameter and for our example we decided to go with percent scrolled. And all that is left is to define the unit of measure. Which can be the standard number, currency, or any of the distance or time measurements. After that just save your custom metric. And this is the process of creating custom dimension and metrics. You however don't need to create a custom dimension for all your custom parameters, you can only do it for those that you wish to use in the reports. 38. Custom Insights: Let's now talk about GA4 insights. They help you uncover trends and patterns in user behaviour, traffic sources and engagement metrics. This can be incredibly powerful in uncovering trends, anomalies, or hidden opportunities that may not be immediately visible in standard reports. You can find the insights card in the home overview at the bottom. Or in the report snapshot. You can also get inside questions in any standard report by clicking on this icon. Here you can find some of the most common questions asked grouped by categories, so you can easily find the right one for you. Once you click on a question you will get an answer straight up in this bar and won't need to browse through different reports just to get this specific insight. These insights can be helpful but are quite basic. Much more interesting are the predictive and custom made insights. So let's see how we can create a custom insight so we can see the insights and get notified if something drastic happens in our app or on our website. To create a custom insight, we first need to go to. View all insights here. Then click on the create button. What you'll get is a screen where you can set conditions on when this insight will appear in your dashboards. At the top you have your frequency. This means how often do you want this insight to be evaluated? You can set this to hourly. All the way to the monthly. For most cases, the daily or weekly period will suffice. Then you can define to which segments you want this condition to apply. By default is for everyone, but you can create a custom segment based on any dimension you have available. Next, you want to select your monitoring metric. This is the metric that will be evaluated against some of your conditions. For example, if we want to track what is happening with our conversions, we would select the conversion metrics. Then we need to decide what we want to track or what the condition needs to happen for us to trigger this insight. By default, GA4 looks at the anomalies that happen. But unfortunately this time we can't set the training period or probability threshold like in the freeform exploration. We can, however, change the conditions. To either if the number of conversions exceeded or falls below a certain threshold, or if it increases or decreases or changes by a certain percentage. If we look for the percentage change, we can also define the comparison period, which can be compared to yesterday, the same day last week, or the same day last year, and depending on whether you want to track. Short time changes in your values or longer periods you'll select the appropriate. For our purpose, let's just set the percentage to 10 and compare it to the same day last week. If you want to compare this week's conversions to last weeks, you'll need to increase the evaluation frequency. And if we set it to weekly. You can see that now we are tracking weak over weak performance instead of just one day Now all we need to do is name our newly created insight and we can name it. 10% conversion change. For most important insights, you might want to also set up e-mail notifications. You can simply do this by writing your e-mail here. Then simply click create. Remember, this insides appear in the insides dashboard only when the conditions are triggered, so don't worry if you don't see them here immediately. You can also take a look at all your created insights in the managed section. And here you can also see the custom inside we just created. You can edit or remove any of these custom insights, and you can also quickly toggle the e-mail notifications by clicking this button. In conclusion, by automating the discovery of relevant trends and patterns. You save time and resources. And it will enable you and your team to focus on more strategic decision making. 39. Custom Channel Groups: Custom channel groupings in GAL4 provides a way for you to categorize your traffic sources based on your specific business needs and reporting requirements. By creating custom channel groupings, you can group traffic sources into custom defined channels. This allows you to analyze the performance of each channel more effectively. You will find custom channel groupings under admin and then data settings. The first custom grouping is the default grouping from Google, which unfortunately you can't modify. But you can create a new channel grouping from this one. You can do this by copying one of the groups or by creating a new channel group. After you create a new one, you can name it and give it a descriptive description. Then you can do a few things with the channels. You can add a new one, modify and remove the existing one, or copy the existing one. You can also reorder channels as the order matters for the attribution. Basically, the first channel whose definition the traffic matches will be used for categorization. Let's just add a new channel. As an example. Let's say you are running a paid CPC search campaign on Bing, Yahoo, and Duck, Duck Go. And you want just these search engines grouped under a paid search channel. I assume you have properly UTM add your links. So the data we used in source and medium is added appropriately. What you could do is add a new channel or modify the existing paid search channel, which will do so, just click on paid search channel. Then we need to remove the existing condition and select the medium under the rule. Next, we will add a new condition that matches exactly the CPC. This will cover are paid part of the campaign. Next, add a new condition group, an in-between the conditions. And we can now define all our sources which are being Yahoo, DuckDuckGo. There are a few ways you can do this. The first one is by adding a rejects condition and listing them all in one condition, which can be super clean. But for our purpose, we'll go with a simpler method of using multiple or conditions. Let's define the first source to match being. Then we can click on or an add a source that equals Yahoo. And we can do this for Duck, Duck Go as well. After you are done, simply save the channel. Remember that if you are adding new channels, they will be added to the bottom of the list. And if there is a channel with a looser set of rules, you need to move it above it. After you are all set and done, you can save the group and start using it in your reports. Custom channel groups can be used as primary or secondary dimensions in reports that support the default channel group. They are also available as dimensions and custom reports, explorations, and when building conditions for audiences. There are some limitations that you should be aware of. For standard properties, you can create only to custom channel groups with a maximum of 25 channels within each group. This might restrict your ability to create detailed channel categorizations for more complex marketing campaigns. Also, the order of channels within accustomed channel group matters as traffic is included in the first channel whose definition it matches. This requires careful attention to channel order when creating and modifying custom channel groups to ensure accurate data categorization. 40. The Wrap up: Congratulations, you've made it to the end of this course. I hope you now have a deep understanding of Google Analytics 4 how to set it up and where to find the most important answers to your marketing or business questions. If you have any comments or suggestions on how I can further improve this course, please let me know. I'd love to hear what you missed and if anything was unclear so I can improve it for you. Like with any product, it can only get better with user feedback and interaction. Also, if you found this course helpful, feel free to rate it and leave a review. I'm also available to you for any additional questions if you have them. Just find me on LinkedIn at Ziga Berce or better yet joint or private success community where you will find heaps of knowledge waiting for you. Last but not least, if you know someone that wants to learn Google Analytics 4, please share this course with them. They will appreciate it. Thank you again for attending and good luck.