Transcript for “Google Analytics 4 Training with MetricsEdge”

[Tiffany Sellwood, co-presenter] I’m actually going to hand it over to Isaac first. GA4, if anybody has already been in GA4 you’ll know that there is very limited reporting inside of GA4, so there are some canned reports available, and then there’s also this section of GA4 called Explorations. It allows you to build more custom reports, so he and I are tag-teaming today.

Isaac is going to walk you through the interface and the general reports that you see by default and guide you through those, and then we’ll take a few questions on that, and then we’ll hop into the custom reports. So, Isaac, I’ll let you take over.

[Isaac Coppola, co-presenter] Thanks Tiffany. So, I’m going to go ahead and, actually is everyone able to see my screen? Sweet. So, I’ll just start us off on the home page, … and if we want to go into reports we’ll go into the sidebar over here and that brings us to our Report snapshot, and so it’s always … I believe it defaults to last 28 days when you come to this page, but easily customizable or, if we want to compare with the previous period or previous year, we can turn that on. But really, this is doing exactly what it says, giving you a snapshot of all of the reporting data on one page.

So, we have our Users, New users, Engagement time, and we can choose which one of these we want trended. This is kind of a real-time snapshot where we can see our users in the last 30 minutes users per minute and top countries they’re coming from. … This is New users by default Channel group, but we’re also able to select a drop-down that lets us see Source medium, campaign, etc.

We’d also look at sessions by Channel group, by Campaign, so everything we see on this page is we’re able to edit it to either New users, Returning users but these Blue Links here will take us to the actual reports, … and that’s going to be where we can see everything in a lot more detail. Also, we’re able to get to that by just coming down here, going to Acquisition, and then going to either User, or Traffic acquisition overview kind of gives us the same thing …just with our acquisition metrics here, but let’s get into one of the reports, starting with user acquisition.

I’m going to turn the compare back off so when we go to User acquisition it will automatically … sort this by the first user default Channel group. And we’re able to see our New users, Engage sessions, Engagement rate, Engage sessions per user engagement time, total of that count, and Conversions. So, event count and conversions, it automatically sets it to All events but if there’s one particular one that you’re interested in you can just select down, so if you want to see how many apply clicks came from organic search we would just turn that on and there’s our answer. And, same thing with conversions right here.

[Tiffany] And I’ll interrupt just to clarify that events have been customized according to some of the objectives of Boise State and they’re done at a very Universal level so things like General button clicks, clicks on the apply button, form submits, video views, all of that and then we have identified what which of those events would be considered a conversion to Boise State, so Isaac if you don’t mind just going to that drop-down underneath conversions so you can see the difference.

So we’ve isolated Purchase as a default, which obviously doesn’t apply to us but Application submit, Form submit, Apply click in a visit the schedule visit which is a campus tour, those are what we have identified as conversions for Boise State. So, that would be the difference between the events and the conversions, and we actually have a cheat sheet of the events that I’m going to send in the chat which will give you the whole list of what we’re tracking and what it means how it’s tracked, and what you can do with that. …

[Isaac] Yeah, so before or in addition to being able to select these ones, we can also change … this Dimension over here from default Channel group. Let’s say we want to look at first user Source medium and then see how many apply clicks came from Google CPC, you can see 350.

We can also add a second dimension, so we have Channel group here and then we can add… let’s do date… so it’s formatted a little bit weird, but this is June 16th and, so, there’s a lot of options we can do. … If we want to look at just display, we can even search up here for that, and so it’ll show us our top which dates had the most users coming in from display.

Something else we can do is add a filter to this page. So, let’s search for hostname. Now let’s say you have a specific hostname that you are interested in looking at, so let’s do blue.boisestate.edu. We’ll select apply and now our data is only traffic for the hostname that we selected. Now, let’s go into traffic acquisition. Here this is a little bit different just because if you come here you’ll notice that you have your new users engage sessions. This is just the difference in metrics, it adds sessions this way, so if that’s what you’re looking for you’re going to want to go to traffic acquisition. If you’re more interested in things like new users to a specific hostname, that’s when you’re going to want to go into user acquisition. So, and these are the acquisition reports, we also have our engagement reports.

So, let’s go into the overview. Same as the other ones, this is going to be things like page views, user engagement, this is where you’re going to want to go for these types of reports. So, let’s start with our events… oops, sorry… events. So, you can see we have 26 listed. I personally like to look at them all on one page, so I go change that to 50 rows per page. That way we get everything right here. Something that might be helpful to do is to add a second dimension for this one and just look at our hostnames this way. So, you can see most of the events are paid views on the home page, and now let’s say we want to look…let’s get rid of this one… say we want to look at another hostname here. Let’s look at majors.boisestate.edu.

This time again we’re going to hit apply, so now this is only to that hostname, and you notice they’ll be significantly less events usually if you filter that hostname is, not all these apply to every page on all these sites. And, now let’s… page path, this is where we’re going to see our Different Page paths on here. So, this actually adds a little bit more. We have some user engagement and Page views on the slash favorites. I think that hostname only is a single page application, so it only has the one, but if we look at…let’s change it to… so, here we have many many more that show up over 8,000 lines.

So, this is when it’s going to be helpful to search for what you’re looking for. Let’s say we’re looking for slash Library, we can just search that and then still…up, but it helps a little bit, and then conversions is going to be very similar this. It’s just the ones that we’ve set up as our conversion events. And so, I’ll show you real quick what that looks like. So, we have all of our events here in settings and we can create new ones, modify existing ones, but these are the ones that we have set up as our actual conversion events. … Tiffany, if we wanted to or if anyone wanted to for whatever reason make something like this into a conversion event, it wouldn’t start tracking it until…it wouldn’t retroactively track it, is that correct?

[Tiffany] Right, yeah.

[Isaac] Yeah, so, whenever we add a new conversion event it’s going to start tracking from whatever day it’s set up.

[Tiffany] But, if it wasn’t a historical event… Sorry, I was just going to point out that the conversions are helpful for if you’re doing, like, any kind of Google ads campaigns, you can pipe in your GA4 conversions into your Google ads platforms and you’re required to have that set up as a conversion in order to bring it over, so you can’t bring over just random events. So, that’s why it’s important to have, you know, the conversion sort of isolated away from all of the generic events.

[Isaac] So, the next engagement report is going to be pages and screens, and this is great for seeing views on our specific Pages, views per user engagement time. So, if we want to see which page has the highest views per user, we can just click here… I don’t know why…There we go. So, this page on slash registrar, 16,38. You want to see what the least is, here we go. Now, if we want to sort by views again and see which page is bringing in the most apply clicks, it’s going to be Admissions apply.

Last one here is the landing page, so this is showing where people are entering the site. … In some pages not set blank … if we want to see how these are coming in, let’s do first user default Channel group. So, we can see our direct traffic, organic search, if we want to see what our most popular organic pages are there’s a few ways to do it. You can just search here, or we can add an actual filter for it where it allows us to drop down. So, both will give you the same information, it’s just really personal preference on how you want to do it. I personally like to just search it. I find it easier to do right there. I don’t think we need to get into monetization, this is more for our e-commerce online stores. … And then, retention is really just giving an overview of new versus returning users. … And, user engagement over time, yeah, again that’s more of a report for like an e-commerce site. Yeah, you know, Amazon would be interested in how many times people are coming back. … But you can…we can actually delete those reports out of this view, so there just are, you know, they’re by default, but we can actually get them out of there since it doesn’t apply to us.

Right, so that’s a basic overview of everything we have in reports. … If we go into real time, this is also pretty interesting to see. We can see exactly who is on, or the most recent sessions like where there’s coming from almost three percent in the last 30 minutes, coming from a smart TV, … but if you’re looking for any sort of real-time information, this is what you’re going to want to look at. Are there any questions so far about any of our reports in GA4?

[Tiffany] Isaac do you want to hit the user attributes in Tech real quick? That’s just where we can get some demographics.

[Isaac] Sure, yeah, so going into user attributes, starting with overview, we have users by country, and that can be changed to new users or returning users. Here again, just like in the real time section, we have our users in the last 30 minutes, users per minute in which country they’re coming from, users by city is a good one to look at. It will take us into our demographic details which is similar to the reports we were looking at in the last section, but something helpful about cities is if we want to see… [Tiffany] Are you looking for a device?

[Isaac] Yes.

[Tiffany] Device category, there we go.

[Participant] Hey, so where it says, this is Jennifer, Not set, does that mean that the user hasn’t set their location?

[Tiffany] Not set in Google analytics is typically just Google doesn’t have the information. So, Google won’t have geographic information for everybody. So, that is why, you know, not set would be in that location. Sometimes like VPNs, for example, people might not have a city tied to it. People that have tracking turned off, things like that.

[Participant] Thank you.

[Tiffany] Yeah, we usually just kind of like decline, just remove it out of the whole data set and just look at what we have available to us.

[Isaac] So, yeah, so, looking at this we can see city and device category to really see how users in each City are utilizing the site, what kind of device they’re coming from. So, let’s look at… let’s look at Boise. So, we can see a lot of users coming from a smart TV in Boise. Pretty interesting. Strange. … But, also, if we close that out we can see where a lot of these app submits are coming from. So we can see Boise in the lead, then quite a bit not set, but Seattle, Phoenix, and again, this is only looking at less than a month’s worth of data. Let’s see, last 90 days, so the order doesn’t change. We can see now Boise, Nampa, Seattle, and yeah, so that’s a great way to get some geographic information here. If you’re going to Tech is our overview, we can see go into what browser people are using, device category, so last 90 days another big chunk coming from Smart TV.

[Tiffany] I wonder if that’s campaign-related? I wonder if there’s like a… if anybody has any digital media campaigns out there that maybe Smart TV is a big Channel?

[Isaac] So, after the overview here, this is how we get into this detailed report here. It’s automatically set to browser. We can change that to look at platform, … even things like screen resolution, device model. I mean, see, let’s look at Vector, browser, and take a look at visit schedules. So, most of our users are coming from Chrome, so no real surprise that that’s going to bring in the most scheduled visits as well. And, I believe that is the gist of how you use the reports. As you see, there’s a lot you can do but it is a little bit limited, and that’s when you’re going…we’re going to use the Explorer section that gives us just a little bit more customization with … how you’re looking for things.

For me personally when I’m using GA4 I always try to use the report section. I just feel like it’s a little bit easier to digest all of this information in this format here, but unfortunately there are times where, if you’re looking for something really specific, it’s going to be easier to do inside the Exploration View. … Does anyone have any questions about this reports section? Okay.

[Tiffany] Take it as a no. We can hop into the Explorer. I will take over the screen, Isaac. So, I’m actually going to send everybody this Google Doc through the chat. This is, it’s simply just a cheat sheet of all of the events that we have created in GA4. It tells you whether something was custom or it was a built-in event because Google Analytics 4 does come with some default events. So, the reason we want to share this with you is not only to tell you what has been set up and what you can work with, but we want to provide you with a definition and then also give you what comes along with that event. Because in GA4, the beauty of GA4 and the custom events, is that you can add any kind of parameter or value to the event itself if it’s available in the data layer.

So, with all of these custom events we’ve also captured things like, you know, what’s the text that people are clicking on if they’re, you know, clicking apply? Because even though it says apply clicks, we have different calls to action that all mean apply, so you might be interested in what button text is working the best. We also are bringing in link URLs. If it’s an outbound click, we want to know what URL is being clicked on, the page location of where this action is happening. We have events on email, telephone, and SMS engagement, so with that click we are also capturing the email address, the phone number that’s clicked on, so I just wanted to give you this cheat sheet. It’s like a glossary of what kind of data is available to you as you consume these reports and are trying to get more granularity and more meaning out of the data. And this is also very helpful when you’re building exploration reports because you are building the report, so you have to know what you’re looking for.

So with that, let’s hop into exploration. Isaac just reviewed the report section, we’re going to hop into explore. And in explore, essentially, we have… we can start with a blank report, or we could use a template. I typically use either the free form template or just the blank template. I’ve never really found too much value in the funnel exploration or the path exploration. I think GA4 has a lot to work on in those areas to make it meaningful, and I think you can get, you know, most of what you need out of the table format.

So, when you hop into Explorations you’ll see that in here we have several exploration reports that are already configured when you create a report. You can save it, and that report becomes available to you every time you log in. And, if you want to share that report so if you have team members that might also want to use that report, you can actually make it viewable to other people. So, if you can see this icon that has two people instead of one, these are reports that I wrote for the OCM (Office of Communications and Marketing) team to measure their brand campaign. I shared it with them so they can access that report. The one thing about sharing the report though is that the person that’s shared with or people that have the ability to access it cannot edit it, but they can make a copy of it and then create their own report from that.

So again, these are just, you know, reports that I’ve created that I thought were valuable enough to save. But if you’re starting from scratch just hit this plus button right here … GA4 wants to take a minute. Okay, and so then we enter into the Explorer interface. We have variables on the left hand column which will be all of the dimensions and metrics that we want to use in our report. And then the tab settings, which is essentially how we want this report to be visualized, and then over here on the right hand side will be the report after we create it.

So, to start with you can name your report if it’s a report that you’re going to want to save. So I’m going to call this button clicks because the example I want to give today is creating a report for button clicks by Page, and then I also want to look at what cities are clicking on those primary button clicks. So, by default, as Isaac mentioned, everything sort of defaults to the last 28 days but I can go back further if I want. So I’m going to go from April 1st through today, hit apply, and note that when you log into this report again next time it will not go back to that default of last 28 days.

It’s going to save the date range that you created here, so I’ve had a few moments where I’m like, oh my gosh, why do we not have, you know, growth in the data? It’s because this date range is static, it saves. Segments is essentially an ability to filter a set of data and then look at that against another set of data, so that can come in handy if you want to look at mobile users versus desktop users, for example. I think for this example, we’re just going to create a standard Report with dimensions and metrics though. So you have to actually know what you’re looking for again because you have to add the dimensions and the metrics that you want. So if you click the plus button… okay, whoops, I get … this view out of my way… you’re going to be given a list of all of the dimensions that are available to you. I mean, the list goes on and on and on if you open each of these, so that’s why it’s helpful to understand what it is that you’re looking for. But in this case I want button clicks.

So I want, according to my cheat sheet, with button clicks I have click Text link URL and Page location available to me for parameters. Those are dimensions so I’m going to add…I’m just going to search for click text. And I’m actually going to put click URL in there too, and then I’m going to add page location, hit import, and now we have all these Dimensions available to us for my metrics.

GA4 is event-based, so that means that everything is an event. Almost all the metrics are essentially an event, so all I need for metrics is event count. So now I have what I want in my report and now I need to create the actual visual visualization. So I’m going to start by adding … you know what? I need event name in here too because I only want button clicks. Okay, so I’m going to start by dragging. You can either drag your dimensions and metrics over to the settings, or if you just click on rows, it’s going to give you your available Dimensions. So here, I’m going to add click Text, and then on my values I want event count, and it’s going to populate, essentially, click Text event count.

Now, if I want to know what URLs are — these click texts – are going to, I can add another row. Click URL or another column essentially, for click URL, and there’s not a lot of not set happening, and that’s because it’s taking every event and just providing the click Text available, and obviously some events don’t have clicks, click Text tied to it because, like an application submission, for example, doesn’t have a click test so now I want to filter this report to only be click, button click. So, I’m going to go down to this bottom here where it says filters, and I’m going to filter the event name. I’m going to use contains, and I’m going to search for button and select clicks button, and then hit apply.

Okay, so now I can see that the click URL is actually, you know what, I think it’s link URL…hold on… I’m gonna get rid of this click URL. Let me see if I have a link URL… Link URL, import, and now I’m going to select link URL. Okay, in some cases we do have some link URLs where someone’s clicking a button or capturing the text, and if it’s that the button goes somewhere we will capture that URL as well. So now I can see these are the buttons that have been clicked the most, how many times in the last, you know, 90 or so days, but if this is too much data I don’t need to see all of, you know, these buttons happening from all over the website. Or I really can’t even tell where these are coming from because it doesn’t have my website, so I can add page location as another dimension, and now I’ll know from which Pages these buttons are being clicked.

So I can see here Library, Jobs, Public Safety, etc. This is not a very digestible way to look at the data, so I’m actually going to select nested rows… sorry not nested rows… I’m going to bring the page location to columns. So, actually I’m going to move this page location to the column section. Now I can see it’s a little bit easier to digest and I can actually extend this to 20 columns. I can see which Pages people are clicking on and what’s the click text. I’m actually going to remove the link URL because it’s kind of making the data a little messy. Okay, so here I can see that, you know, on the Library Pages the search text is being clicked on. Jobs, obviously Current Opportunities, but again this doesn’t give me my personal website’s data.

So in order to filter to that I can go down here and add another filter I’m going to select page location, contains, and then I might just want to see Admissions, and then hit apply. Okay, so now I only have… all of the URLs on top are Admission specific pages, and I can see where people are clicking what’s the name of the click Text on the buttons. This only goes to 10 rows. That’s obviously not very much so I’m going to expand that to 500. And now I have all of the text that’s being clicked on. I can sort this for every page to see what’s the top clicked item, and then we can even go further and say maybe I want to understand device behavior for each of these calls to action. So let’s say I want to add device category. If I go to Dimensions again, I have to add that Dimension, so I want Device category… … Okay, device category, import. Now that’s available to me, so I’m going to drag that in as a row, but it’s really going to split my data up as we’ll see in just a second.

Okay, so now I can see desktop, start your app application is the number one, but then start your application mobile is below. It’s just kind of hard to digest this, so I’m actually going to go over here to nested rows and select yes, and now it’s going to break down each of those button texts By device category, so it’s just a much cleaner way to visualize. So start your undergrad application I can see much more easily now that desktop is the primary device for that call to action, learn about the cost of attendance, again we have the breakdown desktop, mobile, tablet, desktop, mobile, tablet on undergrad cost of attendance… So, … this is a way to use multiple Dimensions and in, you know, a visual format that’s much more digestible.

Now this is sort of clunky…unless you have a really large screen…this is a really clunky way of viewing this report. So you do have the option on the explore reports to download, and I highly recommend that you do if you’re trying to make any sense of the data. So if you hit this down arrow, export the data, you can do it in a Google sheet or Excel format or PDF. I’m going to do Google sheet for now, import the data, and now I have all of that data but it’s in a Google sheet, so I can sort do whatever I want with it. share it out with teammates, etc. And then if I wanted to keep this report and, again, share it with others, this is the icon up here that you want to click to make it a shareable exploration. So then anybody logging into Google Analytics 4 will see this report. Okay, any questions on that first example?

[Participant] I have one. I have a I have a quick question. If you’re saving it but you’re not ready to share it because you’re going to come back and work on it, you just can save it and you don’t click that share plus button and you’re good to go?

[Tiffany] That’s right, you actually don’t even have to hit save. There’s no save. Okay, so I’m gonna go back and you’ll see button clicks is there, and if you…sometimes I just go in and I want to play around and find something quickly, which is like these Untitled Explorations…that was me just trying to find an answer… if you ever need to delete something you can just hover click the box and you can delete it.

[Participant] Gotcha. Thanks.

[Tiffany] Yeah, you’re welcome. Any other questions? Other use cases? Because I do have…I think we’ll demo one more which is looking at applications by city and landing page. No. Alright, so let’s do another report here.

I’m going to do applications by City and landing page. I’m going to go back a while because I know we’ve kind of missed application season, so let’s go back to… well, this goes all the way back to 2020. let’s go to September through November of last year. I’m looking for applications by city and landing page, so the dimensions that I need are event name, because again, an application is actually an event, because I want to be able to filter to my application. And I want City, and I want landing page, and then import. And then on metrics I’m going to use event count. I could also, if I wanted to do, just like sessions I could do that, but in this case I just want to know how many applications, which is technically an event. So now I’m going to drag or select my event name and then my event count, because I want to show you one little trick that’s kind of fun.

Okay, so this…now that I’ve brought an event name I’m getting all the events. I only have 10 rows here so I don’t even see the application, so I want to do more rows. Okay, here’s the application submit row 18. Now instead of just creating a filter down here, I can right click on the row and do…I can select include only the selection, so then it would filter it by default. So now I only have application submits which is exactly what I want. Other times if you want, you know, you want a set of events but you want to … to exclude things you can always…this is what’s nice. You can always undo what you’ve done by using the back arrow, and instead I could just exclude… You could select rows and exclude a few, but in this case we want to include only so I’m going to go back to my application and do include only. Okay I have 9,158 applications in this time frame. That’s great, but I want to know where they came from, so I’m going to select in my rows City… uh oh, I’m getting locked up here…there we go. No surprise, Boise, Nampa, Seattle just as Isaac showed us, but now I want to understand…okay, we know where they’re coming from, but how do they arrive on the website? What’s the entry page?

So I can grab landing page, and I’m going to bring it in as a column again just to make it a little bit more digestible, since we have so many dimensions. So here I can see, you know, the totals by page. So the home page is the primary point of entrance, the admissions apply page is number two. Looks like this is an account login page, admissions, apply, etc. Again, I can make this … bigger by going to 20 pages or 20 columns. There we go. Okay, and now let’s say this is all great but I really want to know what traffic sources are driving applications. So I might get rid of city…I’m going to remove that… I’m going to go to dimensions and select session. Whoops. Session Source medium. We can also select just Source, just medium, the campaign, etc. But in this case I’m just going to do Source medium, import that, Select Source medium.

Alright, and now I can see that Google organic looks like it’s driving the most, direct, Bing organic, Google CPC. So maybe I just want to see this paid search because maybe I’m responsible for a paid search campaign. So again, I can highlight that row and include only that row and get a better view of those landing pages. It’s kind of funky, I don’t know what happened here. I think I’m my computer is freezing. Uh-oh… let me try that again. Let’s say it’s loading. Well would it be? Because it’s 500 rows. Yeah, either that or we have like a column header that’s just huge and squeezing everything down. You get the gist, though we could just isolate that or we could do instead of the… I would…let’s see here, I lost it. Session Source medium.

Why don’t we take the column and move it to a row, and then we’ll make it nested. So instead I’m gonna do a nested row. Okay. This isn’t a very good way to see it either, so I’m actually going to go down into my filters, and instead of selecting the row I’ll filter to Source medium, contains, CPC, and hit apply. Okay so now I can see these are the top landing pages, online degrees, number one admissions apply, MSW, looks like some programs here. So this should give you program level or, you know, landing page level I guess for your paid search campaigns with how many applications were submitted with that session. So that is another example of how you might use Explorations, and then if that is all too complicated I just want to remind everybody that we have this Dashboard, the GA4 dashboard that we created. … Shad, I don’t know how it’s accessible to everybody but I think you have it published somewhere, correct?

[Shad Jessen] Yes, it’s on our Webguide site.

[Tiffany] Okay, so if you just need super high level data fast you can always access this Dashboard. You can select your site, so essentially come up to this drop down, I’m just going to search for online, I’m gonna do the hostname online programs, our online programs. Once you do that then the entire report is filtered to your website pages and you basically get everything that you need, at least from a high business objective level. So we have sessions, users, all of these conversions that we’ve identified by Channel applications, device type, we have Geographic data on this page. I’m trying to go through quickly because we have time for some questions… page engagement, so essentially what we’ve done is we’ve piped in all of the GA4 data into this dashboard and just tried to make it a little bit more digestible.

So this is sort of a third option. We have, you know, the general reports in GA4, the exploration custom reports, or dashboards. And those are, you know, the three primary ways to use your GA4 data. Alright, I think that wraps up the demo portion. Do we have any questions or use cases that we might want to take a look at? …

[Participant] Thank you. This is Ricardo from the online programs. I run advertising for our online school. So, my question is, how capable of, or how possible is it, for us to create audiences based on these events?

[Tiffany] That is a great question. You can either create an audience from the report interface itself, so, like, I could go to segments and create a custom segment here let’s say. Do you want to give me a scenario? … Like somebody hitting a specific page or coming through a specific campaign?

[Participant] Yeah, we can we can just use a website visit to MBA.

[Tiffany] Okay, so here’s where we create the audience rule. So I would want to include users that contain, or that come through a specific campaign. So if we do campaign we can select either the session campaign or their first… the first user Campaign, which would essentially be the first campaign that they came through. So, I would actually do the user scoped one for now since this is an audience, and then you add your filter, so is your campaign name, does it have MBA in it?

[Participant] It does.

[Tiffany] Okay, so I’m just going to hit contains, and then search for MBA, and then hit apply. And you should see on this right hand side it’s building an audience that will tell you roughly how many people would be in that audience. Okay, so I have 5.4K from September 1st to November 30th. You can create more rules, so you could say they came through this campaign and they, you know, visited this website or they took this action, and then you can also add sequences.

So, if you wanted it to be people who came through the campaign and then maybe they came through again on organic…organic search, etc., you could also add exclusions. And then, once you have this…right now I’m just building it out as a segment to apply to my report, but you can click this build an audience selection and this is…I don’t know if you’re familiar with the way that Universal analytics works, but you basically select your membership duration. You can set to maximum and hit apply, save and apply, and now my report is going to filter to that audience. If it wants to load. But it will also be available to you … Oh, it’s probably not going to because of all this weird filtering I’ve already done. If you go to admin, go to audiences, there’s our audience right now, so it is only sort of forward-looking. So when you build an audience you have to remember that, you know,you only get the data from that point forward. But now you can take that audience and you can pipe that into your your Google ads platform.

[Participant] Great, well, thanks for showing us that, thank you.

[Tiffany] No problem. You can also use this interface to create a new audience, and they have some canned ones in here you know, like these are all e-commerce but maybe anybody that submitted an RFI… … I guess none of these really apply. Templates like technology, mobile users, desktop users, acquisition, etc. Yeah, pretty similar to the way the universal analytics form worked.

[Participant] Yeah, it does look similar to what we used to do, thank you.

[Tiffany] Any other questions? How’s everybody feeling about GA4? We’ve got…

[Shad] There’s a lot to learn.

[Tiffany] What’s that, Shad?

[Shad] It’s a lot to learn.

[Tiffany] Yeah.

[Participant] When you say a couple more days, is that when it clicks…it turns over? July 1st is it?

[Tiffany] Yeah, July 1st.

[Shad] And Tiffany, how long will the historical data remain available?

[Tiffany] Very good question, because that number has moved a few times. So, you will still be able to log into the universal analytics account until next July and access your historical data. So before next July we will want to find a more permanent storage solution for that data, but I actually recommend if you have a smaller website or have very specific, simple goals going into Universal analytics, just downloading the data into Google Sheets is a good way to kind of just cover the bases. And you have that historical data from June 30th of this year on.

[Participant] So when you say historical data, you mean before GA4? Like GA3 historical data or… Shad, I remember being on a call or chat. Did you say that we’ve had GA4 implemented for a while? So you’ve been collecting data? Or maybe you said it, Tiffany, but we’ve been collecting data since, when is it?

[Tiffany] I think it was last June.

[Participant] So, that historical data is going to be there because we’ve had GA4 since last June.

[Tiffany] That’s correct. So if you’re in GA4 and you do want to do a year over year analysis you will be able to do that as of July 1st? … Yeah, so here’s Universal analytics. If you basically just want to be safe and cover your bases with some downloads, if you go into any of the reports … just like GA4 if, once you kind of have all the data that you need, and, you select more rows, you just go up to the top here. You can hit export and again Google Sheets, Excel, whatever you need to do. And I would go back and do a full year of data and then, the previous full year of data, and just have all those years backed up in your Google Drive. Great question, Shad.

[Shad] Well, just a reminder to people on the call, if you do need access or you don’t have access yet to the GA4 dashboard, just submit a ticket to the Help Desk. Go through the Help Desk and tell them what you want, they’ll get that over to us and we will provide that access for you.

[Tiffany] And I know that at universities it’s very important for you to be able to isolate your own website or your own unit’s data, so when Isaac was showing how to filter each of those reports in the reports interface, one thing to note is that at this point that filter only persists on that page. So once you navigate to a different report you have to recreate that filter. So that’s another reason why exploration reports might be better off if you’re isolating data to a certain unit. I hope that GA4 changes that and makes that persist because that’s the way it worked in Universal analytics, so I don’t know why they would make us redo all that work, but it’s just good to know that because if you’re looking at data and you’re assuming in your head you’re just looking at your data and you see crazy numbers, that could explain why.