Transcripts
1. Introduction: In this section, we're going to take the measurement planning knowledge that you've acquired so far and help you get some tool specific experience. In particular, Google Analytics for, for those of you familiar with the old Ga, Google Analytics for formerly known as atlas web, is a new kind of property. Different reports than what you're probably used to. So might see a modern outlook on digital analytics, which I think is fair. For example, one advantage of Google Analytics for property is that you can use it for website and app, or both a website and an app together. This was not possible before. However, since this is not a course about Google Analytics, we're only going to focus on the components that are most relevant to measurement planning, such as events, convergence and the analysis Hub. Let's take a look.
2. How to access the Google Analytics 4 (GA4) Demo Account?: We're going to start off by giving you access to the Google Analytics demo account. If you check the resource section in the course, you'll see the link that is going to lead you directly to this page, to just click there and you'll be able to see exactly what I'm seeing. I'm just going to scroll down right now and show you what the demo account is. So immediately, there is a button called Access demo account and what that is, Google has provided practice data and practice Google Analytics properties for any new users to play around with it. If they don't have their own website or if their company doesn't have Google Analytics set up yet. Since the introduction of Google Analytics for Google has introduced a couple of additional demo accounts. So if I scroll a little bit further, there's an explanation here that you can read on your own time. There are two different demo accounts. One is the Google merchant merchandise store and the other one is flooded. Flooded is fairly new. And that is a Google Analytics account for an app. That is a strategy puzzle game. And you can see how analytics are generated within that app. The Google merchandise store has been there for, for a long time with the universal Google Analytics. But now we have the so-called Google Analytics for. So let's click on Access demo count and see what Google Analytics for is really all about. And once you load the interface, you will see the classic Google merchandise store Universal Analytics. So this might look familiar if you use Google Analytics in the past. But what we're going to do for the sake of our exercise in a project is we're going to expand and go into different properties here. We're going to use J4 Google merchandise store. So I'm going to click on Open and you can immediately see how the entire interface changes. And I must say that there is a bit of a modern look on this one. A lot of new menus have been introduced and some of the old redundant ones have been removed. In the next video, I want to walk you through the Google Analytics for homepage and show you how visualizing and presenting data will, can help you generate more insights and can help the overall measurement planning process.
3. How to navigate the Google Analytics 4 (GA4) homepage?: As we established already, reporting is the product of a well-executed measurement plan. So let's take a look at how Google has decided to present the data and old information regarding each metric in this demo account in their new Google Analytics for, as you can see, they're starting with the top-level metrics first, users, new users, average engagement rate, total revenue if your website is e-commerce. So you can get a grasp of how your website or store is performing. On the right side here, you have users in last 30 minutes, which shows you live performance of where your users are coming from in real-time. This is really important, especially if you have an e-commerce website or if you have a marketing activity that happens on a specific date and you're expecting a huge uptick. Now, let's scroll down a little bit to see what else is there. The interesting thing that Google has decided to do and is always very keen on, is asking a question before presenting the actual chart. Where do your new users come from? What are your top campaigns? In that way, it's very easy for somebody to get information about the chart below. Right here we can see where the uterus are coming from. What type of channel? Organic referral? Cpc, cost-per-click, paid media, affiliate or e-mail. On the right side we can see our top paid media campaigns or if they're organic. Now, we're going to scroll a little bit further to show you a couple of key metrics and sections that we're actually going to spend a lot of time and the remainder of this course. The top two are, what are your top events? In the measurement plan? We talked about specific KPIs and metrics into triggers behind them. So in Google Analytics for you have a better version of an event. Of course, events have been there for a long time, but Google Analytics for is trying to streamline them. So let's see what we have in the events. We have things like pageviews, user engagement, scroll, view, item, session starts. So those are all very familiar events and these are pretty much the most basic events that will later on comprise our triggers when we're trying to make a tag. And last but not least, we have conversions. Conversions are closely related to an event, but are really the key actions that we would like to tag because they matter to our business. They're very similar to the marketing KPIs and metrics. We're going to expand them all these areas a little bit later. But before we close out this section, I want to show you something that Google has worked a lot on. And it's really important for the new generation of analytics and measurement. And that has insights. We're going to click on View all insights here. And that's going to open a panel for us that has different recommendations that Google has identified through their algorithms. In other words, Google is trying to focus not only on data dumps and metrics and a large amount of information, but actually create snackable pieces that can help you grow your business, can communicate better, which is also the purpose of a measurement plan. Let's see a couple of examples. Automated insight. This one here, engaged sessions per user. We're 84% lower than average for people in Frankfurt, Germany. This gives you the little snippet of information that can take your website to the next level if you explore further, when that means, you can of course, click through it and see exactly what Google Analytics meant. So here we have German flag engaged sessions per user versus the average. This group average. And we have a lot more information here about this specific insight. So that can perhaps notify us that maybe our website translation for German is not working and nobody can read it. Little snippets like this one can really help you understand your business in a better way. Now let's look at another one. For example, organic channel drove the most conversions, 53 percent, 06 last month. So let's see what this is all about. If people are coming in organically. That might mean that our SEO efforts are working with produce a lot of different content pieces that are getting people to join our website or recall it and then type it in immediately. So that is good inside to know where the traffic is coming from. If we look at the iterative steps, we have direct referral. And that can give us a sense of how many people are directly typing our websites. Do we have referrals that are driving to our websites, whether that's certain blog or another type of website. But this gives us the surface level information that lets say referrals have 12 thousand conversions. So we can dig deeper into referrals and see which websites are actually referring the most users. So this is really how Google is polishing their Google Analytics for and trying to improve communication within their analytics tools.
4. What are GA4 events and how to create a conversion?: Now let's move on to convergence and events. You can see them in the menu here on the left. So we're going to open events first just to see what type of events already in the system in this demo account. Now, it's important to note that there is a difference between conversions and events. Events, our website behaviors and actions that a user might perform in Google Analytics tracks. Conversions are normally actions that affect your website revenue or the business goal of your company. So they are simply tied to what you're trying to grow within your business. Let's see what Google Analytics for is tracking in this specific demo account. The first event that we can see here is add payment info. And there are 4,123 triggers of this event. This is how many times this event has happened. And obviously there is a 10, 0.7% change here, a positive change compared to the previous period that we've selected. So if you look in the right corner here, we have April 18th of May 15, 2021. You might have something else because this is the last 20 days of this recording. But you can modify this one and you can see the corresponding change. The other interesting part here is the users associated event. So we can see that there are fewer people that actually click them this event. So we have 1, 0, 0, 0, 0, 0, 2. Simply put the count and the users are different in value. And that's totally normal because a certain user might have tried to add payment info a couple of times for a good that they were buying. Let's look at the other events. We have things like Add to Cart for the e-commerce websites, Android lovers. This is perhaps people that have Android devices and they've triggered the event when they logged in from a phone. We have things like Glick, very simple. These are potentially older clicks and a specific section. Now we have errors. Google Analytics is also used to capture different errors if a form was not submitted, for example, or of a problem occurred on the website. And that way you can see where the problematic areas are. As you can see, these are just actions that Google Analytics for is tracking within your digital property. They're not necessarily tied to a business goal. Yet. As a next step, I really wanted to show you how to create an event. However, within the demo account, we won't be able to do it because it's just viewing axis. So I've created a new account and putting some data. Unfortunately, you want to have access to that. But you can follow with me from your own personal Google Analytics for account. Or you, or you can set up a demo one. I'll click on this one and navigate to the events here. And we're going to see a couple of the familiar events that we saw in the other demo property. Now let's click on Create event. Once we click that, we get to custom events. And if you look on the interface, it's fairly familiar to Google Tag Manager. Google is trying to merge old and tools available and create a seamless interface between them. So they don't look like different tools from different companies, but the look like a Google Analytics Suite. And I just want to show you a couple of fields not going too deep as this is not really a tag implementation course. Firstly, you would have to write the custom event name. There's a lot of name suggests that obviously here from default events are the most common events. So File Download, you can specify it even further. Matching conditions. This is what your technical team would potentially set up in Google Tag Manager. So you can write the perimeter. There is a perimeter on your website that triggers file download. This is probably what you're going to put here. Then you're going to click on equals or any of the other options that are available. The closely resemble regular expressions. Once you have that, I'll click containing this case, the value that you're going to put here is the value that this trigger provides. So if we had a PDF download and they were hundreds of those PDFs and you want to just to track one that's related to your product with our car example that we had in the first section. If you just want to see the SUV PDF Donald's for a specific model, you can write the model one value and Google Analytics for we'll track only this model. Obviously this technical infrastructure is set up by your tag implementation team. There's some additional perimeter configurations that could be created, of course, and add modifications. But once you're done with this, you can click Create and you'll get fairly easily in event. Now, we're not going to save this one. We're going to go back, discard the changes, and go back to the main interface. And we're going to look at something that was a little bit grayed out. In the Google Analytics demo account. We're going to focus on this mark as conversion. In the earlier versions of Google Analytics, there were goals which are very similar to conversions. However, the Google team has tried to make convergence setting a little bit more intuitive so you can link convergence in events in a much better way. For example, if we were to run a blog or a content-based website, pageviews was a real conversion and business KPI because we were generating revenue for every page view as a publisher. We can simply go here and mark this as a conversion. And immediately, Google Analytics creates that within the conversion tab, and it is as simple as that. Let's go to the conversion tab and see what happened there. I'm going to click on conversions here. And I'll take a look at what's available. Well, we have purchase something that I've set up previously. Unfortunately, there are no counts here and we also have something that we just created and that's page views. We have now communicated with Google that pageviews, it's a really important metric for our business. And that's why we've marked as a conversion. And the next part, we're going to take it a step further and see how we can build an audience based on different events and triggers. If you'll recall, creating an audience, is really important to the segmentation stage of any measurement plan.
5. Part 1: How to build an audience to apply segmentation in your measurement plan?: And this part, let's navigate to the Audience tab here within configuration and see how we can build an audience. When x is simply click on the audience's, normally what you're going to see is a blank tab because there are no audiences created. But for the sake of this exercise, I've created a few, probably the most basic one. Firstly, we have all users. This is simply all users on the website. And here we have the description. This is fairly simple here, but we can write a link or a description just to remind us what is the audience Name? And there are a few familiar metrics that we explored in the previous video. So we have the users and the change based on the comparison period and we've selected on top. And of course, when the audience was created, this is super, super important because sometimes names are all you have in these audience tabs. And the date can tell you when the actual data started flowing. It says, audiences in Google Analytics for NGA, Universal Analytics are not retroactive. Therefore, whenever you create the audience, then the audience against the filled in. Let's see what are our options if we tried to create a new audience. Simply click on the audience here. When we try to create an audience, normally, Google will have a couple of suggestions for us that are the most commonly created audiences. So you can of course, start with, start from scratch and build your custom audience. Or you can toggle between general and templates to see what Google is suggesting. In the general menu we have recently active users deal for users that were active within a specific time period? Yeah, non purchasers, people that have not made a purchase, really important for e-commerce websites. And within the templates, you have a few common things as well. You have demographics, you have technology, and you have acquisition. Let's try the demographics one. I'm going to simply click on this one and the menu is going to transform. At first, it might look a little bit intimidating, but there's a lot of information on this page that can make things easier for you when you activate those audiences or when you suggest them to be used in the segmentation process of your measurement plan. Let's take a look. We'll start here on the right-hand side. Membership duration. As you remember, I mentioned that this is really, really important because it indicates how long a user will stay within that audience lists. Normally that's set up to 30 days. But of course you can change that depending on your needs when you're creating the audience. It can be 30, it could be 90 days or a 100 days, depending on the buying cycle that your business has. Now let's look at one of the qualifiers in our audience. Let's look at gender. First. We always have the dimension here. The second box here is showing us is one of or the interruption is not one of them. And what that means, It's really, are we going to target positively or negatively? In this case, we're going to keep it as positive targeting. So we'll be finding everybody that has that specific gender in the next box is where we have to specify that gender. So if I open this, I'm going to have female, male and other. Let's select Mail for example. Immediately what happens is Google is showing us an estimate of how many people are male within the audience that we're trying to create. So for all the sessions in this segment, 2300 are male. And you can see here on the bottom, it's showing 3.2 k. And that means that these are a 100 percent of the sessions in the segment. Last but not least, we have audience trigger. And that's a really important piece because if you're familiar with e-mail marketing, Normally we create sequences. If a happens, trigger B, this is a similar situation, but with audiences. So let's, let's try it out. We'll click Create New. And we'll see what Google is prompting us to do. It says locked bowling event when a user becomes a member of this audience. So we can specify an event name that will be automatically created in our Events tab if a person enters this list. So I can simply write test underscore GO. And I'll know that if somebody enters this list, the event test GO would be triggered. Of course, this is a simple example. But if we have lifetime value calculations or churn rate for bigger businesses where if somebody exits a specific list of clients, they have to be re-engaged immediately when a campaign or promotion so they don't lose them as a client. This is super crucial. Underneath the event name, you have a little box. So by taking this box, we're simply saying that yes, we want to log a never event to see if a membership refreshes. And that way you can see the transition of your customers when they enter and exit a specific list might be super important for your business. To close it off, we can simply click Save, We haven't you audience trigger setup. We have one of the qualifiers here in the audience gender. You have it set up to male. But because this is a preset audience, we have to fill in the rest in order for us to be able to save it and complete the audience setup. So I'm going to write against age, I'm going to just select all the agents available. These are kind of the classic breakdowns. I'm going to pick a language code. This is normally would the browser setting sends to Google Analytics. So English US interests, ID, that's something else that and is mostly a really to paid media. So we're going to just put technology, techno files. And then for countryID, there's a couple of IDs that we can select, Canada, US, we're gonna pick us in this case. And oldies, red underlining should disappear. So you're all set to save your audience. And remember that within the summary here, this will change. It will fluctuate sometimes is not going to give you the correct estimate. But ideally, this is just for directional use. And once you save the Ionians, then you're going to see how many people are in it and you can analyze it further. So let's proceed to saving. And here's our brand new audience. So an audience Name. We really didn't put anything. So we have untitled audience here. That's what happens by default. You can obviously put the name such as, let's say geo audience or male, 24 to 55. Like you can play around with the actual naming description if you want to add something more. And here it's saying to us that there is under ten users. So because we are applying so many qualifiers and we made it soon niche, there's very few users. You, you're probably never going to activate an audience. Just we tend users is very rarely that's going to happen, but you would have bigger audiences. This is just an example in this case, and of course, created on Today's date is May 16th, 2021. And there you have it. We've created our first audience based on geo signals.
6. Part 2: How to build an audience to apply segmentation in your measurement plan?: Now let's do this one more time, but add a little bit more complexity. We're going to use the Google provided templates, but we're going to create our own custom audience. So I'm going to click New here and then create a custom audience. From there before I start any work. As you saw, the audience showed up as untitled audience, where you change that name is here on top. So we're going to do something related to the source of the acquisition and the platform type. So I'm going to write or read it in brackets. Mobile. And then I'm going to put here not next to it. And you will see in a minute why the description piece is what we're going to add right here. And that normally shows up next to the name as you saw it in the other examples. So we're gonna do users who came to the website from read it, but not mobile. So they did not use the mobile platform. They came from desktop or tablet. Now we have this sentence written down, but how do we translate that to an actual segment? So here it's y. When you're creating a measurement plan, the instructions that you're giving different teams, and the layout of your marketing KPIs to really, really important because you're describing what audience you're going after. So let's try to do this here. So we have the first, there's include users when we're going to add a new condition. And we're going to go into source in medium. And that's gonna get us to traffic source here. So you have medium name source. If this is a real campaign, if it's paid, already know the name, you can still do that as well. But we're gonna do source and user acquired campaign source. From here I'm going to click on value. And we didn't value. I'm gonna get reddit.com immediately. I'm seeing what are the acquisition channels. So reddit.com. And then we're going to take at any point because we're not trying to do anything with the timeframes here. We'll just say wherever I've acquired it, whenever that has happened, as long as it's from Reddit. That's fine. So we have that completed. So far, we have the readied population. And so right here in the summary tab, you can see that sessions in this segment, 445 in the last 30 days, these figures are an estimate based on the last 30 days. Actual audience size may vary. So that's why I was saying this is just a guiding tab that you can use for reference. Now, the green bubble here is showing what we've included. So 305 users we have that are coming from Reddit. Now let's apply the exclusion. So I'm going to add group to exclude. And that shows up in red. And so we're going to see now how our Venn diagram is going to be completed here. So I'm going to click Add new condition. And I'm going to type here in the search bar, bar platform, and I get platform device category. So I'm going to click on that, then contain the value here. I'm going to say mobile because we don't want mobile, we want desktop and tablet only. So I'm going to exclude mobile and click at any point. And look what happened here on the right side. This is a really cool visualization because you can actually see what is happening with your data real time. So we had the 305 total included. We are excluding 32 people, so 32 people King from Reddit, but they came through mobile device and does not what we're looking for. So 305 minus 32, 273 users. Now, because we've completed this, we have set up the membership duration and we know how big is our audience. We're ready to click Save. And once that happens, the audience immediately pop up here, read at mobile not sometimes the number of users is low. You will have to give time to the audience to be fully create it and refresh. As well as there's no created on. So I'll refresh. And normally a lot of these numbers will be updated or in a couple of days, there is certain delays in Google Analytics. So it's important to wait for a little bit. So we have the created on the users are still low. But that will refresh over time depending on the size of your audience. Simply by creating these audiences, you can see how powerful segmentation can be and how it adds additional context to your overall marketing strategy.
7. How to navigate the "Analysis Hub"?: For this last part of the section, we're gonna go back to the Google Analytics for Google merchandise store count if you haven't done so, you can do by clicking here on top, select my demo account, J4, Google merchandise store. And once you click it, you'll be exactly here at the homepage. Now, let's look into something cool. The analysis hub. It's a relatively new feature in Google Analytics, and it allows you to analyze data directly in the Google Analytics interface. And it's a very interactive component of Google Analytics for. So first, you will have to go to Analysis hub. This component used to be called the Advanced Analysis tab in GA 360. And you had that in Google Analytics, Universal Analytics. As soon as you land on the analysis hub, you can see a couple of suggested analyses that you could do. There's exploration. You can see a pivot chart and your classic table, There's funnel analysis. So you can see how users are going through the marketing funnel. And then you have path analysis where you can see the user journey through this tree graph. For this exercise, we're just going to focus on the funnel analysis so you can see how old the components that we've learned so far it come together. When you look at that analysis, I'm going to click a funnel analysis here. And once it loads, You're gonna see this standard funnel that's really well visualized. And so let's try to make sense of older data that's here. There are different steps in before we actually get into the steps. We're just going to minimize these just for now. And they're gonna go here on the bottom just so we can fully focus here. Step 1, first open visit. So this is really telling us how many users visited your website or your digital property for the first time. That's why you're having 100 percent here, because this is the top step and this is your overall population. So active users, you have 72000 users. Now, if I start going down in the funnel, we're having how many organic visitors? Well, only 58 percent. So the rest are coming from other channels. So as far as this funnel is concerned, we're not counting them. We're just going to see from all the people how many were organic visitors. So every step has a certain rule, and obviously the amount of users goes lower and lower and lower because we're adding more qualifiers and we're making this whole funnel more, more specific. Now here on the bottom you can see how many users basically dropped and how many we've lost in a percentage and also in the value. So we have the organic visitors. We've got a 42000 than session start. How many people started from each organic visitors? Sessions in day began exploring the website. Well, only 5.8 thousand. Step 4 is screen page view. So how many users actually viewed a page or screen of an app? So this goes a little bit lower again. So we have 4.1 K, we're losing a couple of visitors have some might have started a session, but they did not view more than one page perhaps. And then here is the step 5, how many people purchased? So in this case we have 0, so nobody really converted and purchase. But normally you would see purchase side with single digit here when you have these type of standard and picker funnels, not everybody who lands on your website is going to convert. The important piece here is that once we built these funnels, we can see how users are flowing from step one to step 5. And we can customize these steps in the table here below, we can see the steps from one to five. And if I scroll down, I'll see 45. We can also see the completion rate for each step, the abandonment rate and the actual abandonment. And this is really a translation of the top chart. The only additional piece here is we can add a slicer to check which device category was used. So we can see from the first visitors, from the seventy one hundred, ten hundred visitors that are a 100 percent here. How many were coming from desktop? How many are your mobile or tablet? And so if we start applying filters on this chart, we might be able to see that a lot of the first opens that are organic, The happened to be from desktop, not tablet. So we're adding extra dimensions to our funnel. Now I'm going to open the tabs here that we close just so you can see how we could evaluate them. So the techniques that we've chosen here is the funnel analysis, the ITER analysis. There's a lot of them can also help you just kinda slice your data. The standard funnel or trended funneled as these are the two options here, make open funnel. So this is a really important piece and this was part of Google Analytics 360. There are two types of funnels. There's the closed funnel in the open one. The close is if you entered from the beginning of step one and you did this whole process within one session. That's normally considered to be a closed funnel. So we've completed all the steps from within one session and you cannot enter for many other steps. You have to start from one to five. That's what we'll be counted as a closed funnel. And if you complete it, you get a completion rate there. The open funnel is you might join from another step if that allows it. Sometimes that might not make sense at all because it's a sequential process and they cannot really start from step two or three. But if you're doing more generic analysis and your steps are really broad and anybody could do them, then you might want to have a close to funnel if you were looking at something specific to measure or evaluate sigma1 comparison. So this is really your chance to apply further segmentation to your funnel analysis. You can add any type of segments so you can add language, perhaps you can add gender, or if you're an e-commerce, you can add a single product in C, this visualization, just for a single product that you're selling. Within the steps as I promised, you could actually customize these steps that can be easily moved around and you can also edit them here from the top, you can see exactly what step 1 is always directly followed by step to an old these details. And you can add different parameters and customize the steps and perhaps bad any type of exclusions or, or an add information about how long a step could remain open. So within five minutes you will have to complete. You have to go from step one to step two. This can get fairly complex and really detailed. For example, if you are high traffic websites such as Netflix, you might want to see how people move from different genres and shows soon they're browsing behavior and how long it takes them to start watching the show. So if your steps or different shows and different genres, you can limit here and say within five minutes or within 20 minutes to see how long for a specific group of people it takes him to pick a show that they like. So there's a lot of, a lot of different facets here that could be applied and it can get fairly interesting. Now I'm going to go back and kind of show you the last pieces here. So device breakdown again, you can drag and drop from this left side, you can drag and drop different dimensions and break this down. So this is not necessarily a segment. So it does not look up a user IDs. This is just a slicer to show you from your main dimension. What is the secondary dimension that can help you break down what you had in each step so you can get additional contexts. A well-structured funnel analysis like this one within Google Analytics or any other tool that you pick, can really bring a measurement plan to life and allow it to be super effective. So you can actually generate insights and learn from the data that you're collecting.