Podcast

Countdown to Google Analytics 4 with Chris Sietsema

Analytics expert Chris Sietsema of Teach to Fish Digital gives us an update on the current state of Google Analytics 4 (GA4). We discuss some of the most important differences between Universal Analytics and GA4, and some of the ways the switch to GA4 has already impacted higher ed marketers. We wrap up with some of Chris’s favorite GA4 resources.

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Transcript

Jarrett Smith:
You are listening to the Higher Ed Marketing Lab. I’m your host, Jared Smith.
Welcome to the Higher Ed Marketing Lab. I’m Jared Smith. Each episode, it’s my job to engage with some of the brightest minds in higher education in the broader world of marketing to bring you actionable advice you can use to level up your school’s marketing and enrollment performance. On July 1st, 2023, Google’s Universal Analytics, the most widely used website analytics platform in the world, will stop processing data. After that date, all of Google’s web analytics will be handled by the latest version known as Google Analytics 4 or GA4.
While the transition to GA4 has been on many folks radars for quite some time, there’s still a lot we’re learning about the new platform. In fact, it’s been under near constant development since it was first released in the fall of 2020. In this episode, analytics expert Chris Sietsema of Teach to Fish Digital will give us an update on the current state of GA4. We’ll discuss some of the most important differences between Universal Analytics and GA4, and some of the ways the switch to GA4 has impacted higher ed marketers. We wrap up with some of Chris’s favorite GA4 resources. So if you’re in the midst of a transition to GA4 or have already made the transition, but still feel a bit uneasy, this episode is for you. Without further ado, here’s my conversation with Chris Sietsema. Chris, welcome to the show.

Chris Sietsema:
Thanks for having me.

Jarrett Smith:
Well, I am excited to talk all things Google Analytics 4. I think you were probably on the show, maybe, I don’t know, over a year ago at this point. We were talking GA4, and now holy smokes, it’s definitely here. We’re using it. It’s weird and different and still under development. For anybody who maybe isn’t fully up to date, can you just give us the Quick Cliff’s notes to catch everybody up?

Chris Sietsema:
Yeah, yeah. You alluded to the fact that we’ve been using it now, or we’re using it now. I hope we are. I don’t know that that’s true for everybody. For anybody that’s listening that hasn’t been using it’s still, it’s okay. You’re not alone. There’s others out there that haven’t really jumped in just yet. Google Analytics 4 is just a new version. It’s an “upgraded” analytics platform from Google. Previously, we’ve been utilizing Universal Analytics for, I want to say, 12, 15 years, something like that. Just at the point that many of us got used to it, Google went and updated the system. There’s several differences, but the biggest difference is that this is an event-based measurement platform. An event-based platform means that previously we could bucket our metrics into categories like page view metrics like time on page and bounces, and e-commerce metrics, purchases, average cart value, those types of things.
Then event metrics, which are anything on click, PDF downloads, clicks to a button, clicks to hit an email address or a phone number or whatever, attempting to call, whatever it might be, and now everything is operating off of this flat circle. Everything is an event. There’s no more page views, but there are page view events, and there’s no more visits or sessions at what there are session underscore start events, so everything is an event now. That in my experience, working with folks on the client side has been the biggest hurdle to wrap our heads around that. All of our stuff that we typically use is still there. It’s just called something different, and it’s probably in a different place.

Jarrett Smith:
You mentioned earlier if anybody’s not using GA4 yet, it’s not the end of the world, but there are some deadlines attached with this, because Google is sunsetting Universal Analytics in the not too distant future. Can you tell us about that?

Chris Sietsema:
Yeah. The plan so far, and GA4 came out I think at the height of the pandemic in October of 2020 because we didn’t have anything else really to worry about at that time. They announced that around that time, and at that time they said, “Okay, around July 1st, 2023,” which is two and a half years away, at that point, “… we are going to sunset or stop collecting data in Universal Analytics, and thus you’ll really want to jump into GA4 and utilize that as your primary measurement platform if you’re using Google Analytics,” that is. That is the date at which Universal Analytics will stop collecting data. Will we still be able to access those reports? Yes, that’s what they’ve said, at least. We will be able to access those reports. The other question that I’ve heard from folks is, “Okay, cool. I really want to be able to utilize my Universal Analytics, my old platform metrics for a while, because I’m doing year-over-year comparisons and things like that. At what point will they just no longer be available?” No one knows the answer to that.
At one point, Google on their site said that January 1st, 2024 it’s just going to be gone completely. They’re just going to erase it from the face of the Earth. That’s not going to be accessible. They’ve since removed that language, and it’s just a big question mark. No one really knows. The word on the street is it’s still going to be January 1. But if we know Google, we know that they are very good and adept at kicking the can down the road a little bit, which is why I’m wouldn’t be shocked, honestly, if they moved the actual deadline back for the use of Universal Analytics. July 1 is the day, which we really need to start using GA4. I wouldn’t be surprised if they moved that back. I wouldn’t count on it, but it wouldn’t shock me.

Jarrett Smith:
So hope for the best, but prepare for the worst.

Chris Sietsema:
Exactly. Yep. Yeah.

Jarrett Smith:
Yep. Okay, Chris, why are they doing this? I mean, it’s a whole paradigm shift. Is it worth it?

Chris Sietsema:
I’ve gotten that question a lot, why are they doing this? But it’s been phrased a little bit different. Why are they doing this to me? It’s in a personal affront, which I can empathize with. It does feel pretty personal, because some of us are in that thing all the time, Universal Analytics, so why are they changing this platform that we know and love? I think there’s three reasons. One is if you compare Universal Analytics or GA3, the thing that we’re been using for years now to some other analytics platforms on the market that are paid solutions like Adobe, for example, most of the top “analytics platforms” are event-based models. GA was behind the times a bit, and so they’re coming up to speed with the event-based tracking model [inaudible 00:06:58].

Jarrett Smith:
I remember back in the day, Mix Panel came out, and looking at that, I think that was all based around events, and I was like, “Whoa, what is this?”

Chris Sietsema:
Yeah, why? Yeah. The page view model is a little bit out of date. Again, it’s primarily because people who’ve been in the analytics industry for a while prefer event-based because it’s gives you more flexibility, you’re not limited to those categories we talked about earlier, like page views, events, et cetera. There’s also a greater level of detail now that’s available. When we talk about events or event tracking in Universal Analytics, we typically had three little bits of detail that were attached to each event, which are called parameters. Then parameters or bits of detail that are attached. We had event categories, event actions and event labels. If, let’s say, somebody downloads a file like a PDF on the site, the category would be file download, the action might be just download. Then the label would be whatever document that they downloaded.
Now with GA4, you got up to 25 parameters that are attached to every single event, so you can see are what page was it on, what kind of file was it, what was the file type, what was the name of the file, what position was the file, was it the top of the page or the bottom of the page? All those different parameters could be attached to it. The other thing, I think, that’s a big upgrade and the reason why they’re doing this is that there’s a built-in reporting interface. We’ve always had custom reports, but they haven’t been that great, in my opinion. They’d be arduous and difficult to use. The custom reporting in GA4 is gorgeous, super handsome.

Jarrett Smith:
It’s basically Data Studio mashed into GA4, is the way I look at it, or pretty close.

Chris Sietsema:
Yeah, I would say it’s a more nerdy, less handsome version of Data Studio, or Data Studio, you really need to make things look pretty, for lack of a better description. You can really do some hardcore analysis and explore. I think users of the platform will really dig that. There’s just features that we haven’t had before, like funnel analysis, which is more important for folks on the e-commerce side, but there’s also segment overlaps where you can draw correlations between really important things like conversion events and other more seemingly innocuous events like video plays or the file downloads we talked about or scroll behavior. How does that correlate with conversion activities? You can change UX and update different content on the site.
The other big reason I think that they’re doing this, there’s two more, the second one is really consumer privacy. There’s this feature in Google Analytics 3 and 4 such as demographics. If you turn on Google Analytics 4 right now, your demographics reporting will not work. You’ve got to, as the user of the platform, turn that on. Google’s basically saying, “We don’t want to touch this. Consumer privacy’s a thing now that we want to remove ourselves from. We’re putting all the onus on our users.” You and I as users of the platform have to flip the switch and turn those reports on, which have consumer privacy applications for tracking things like interests, demographics, age, stuff like that, gender.

Jarrett Smith:
Even though Google’s the one supplying that information.

Chris Sietsema:
Yep. Yep. Will you please push this button? Okay, great.

Jarrett Smith:
Yeah.

Chris Sietsema:
There’s also-

Jarrett Smith:
No, you’re implicated too. You share the blame.

Chris Sietsema:
Yeah. Yeah. It’s very transparent what they’re doing. I get it. I guess, the lawyers must have got involved, God bless them. Also, this is a little technical, but IP anonymization, which is a fun word to say, is essentially Google’s ability to track users by IP, and IP anonymization is just basically, “We can’t really tell who it is, but we know if somebody accessed the website, not sure who they were, we’re not going to collect that IP information. You can’t create a report by it.”
That wasn’t turned on within Universal Analytics by default. It is now in GA4. They’re covering their what there as well. There’s also more strict or stricter data retention policy. This is a big one that we might have chatted about a year ago, and that the data retention policy by default is Google will store two months of your data. I’m going to say that again. Google will store two months of your data and people say, “What? That’s it. How come?” Now, you can update that so that it will, within the data retention area of the admin section of GA4, you can update that so it’ll collect up to 14 months, but that’s it.
And so, they’re not allowing themselves to fall into a sticky area where they’re capturing all this data that could have some potential consumer privacy implications, if that makes sense. To clarify that on the data retention piece, does that mean that if I turned on Google Analytics 4 back in October of 2020, I don’t have that data? There’s just like a 14-month rolling window from 14 months from today? No, you still have that in GA4. It’s when you pull that data out into an exploration report, which is the customer reports, or if you pull it into Data Studio or Tableau or Power BI or whatever you’re using for visualization for dashboarding, that’s when the 14-month or 2-month, if you don’t update that setting. That’s when those implications come into play.

Jarrett Smith:
Oh, interesting. So it’s not that they are throwing out the data after 14 months and you don’t have access to it, it’s just that when you go to pull it, you can only grab 14 months back.

Chris Sietsema:
Correct. Yeah. There’s, within GA4, there’s a couple main sections. There’s reports, and there’s explorations, which are the customer reports. In reports proper, all that data’s there, you can find it. It’s a bit shallow. If you ever check out those reports a little bit deeper, you find there’s not much here. I can’t do much analysis in there. I really need to jump into Explore. The moment you move into explore the customer reports is when that 14-month window is applied. Same thing with Data Studio.

Jarrett Smith:
My understanding is there’s also a native connector into BigQuery that is… Do you know if that allows you to, within explorations, go back past that 14-month window if you’ve connected into BigQuery or?

Chris Sietsema:
I wish I knew the answer on this. I’m pretty sure that it does not. Any day that’s coming out of reports will have that 14-month window applied. The BigQuery connector will be important for a lot of folks who are listening to this, but not everybody. Those of us with massive amounts of data, let’s say, I don’t know, upwards of 15,000 to 20,000 visits or session start events per month, we’ll probably need to look at BigQuery just because it’s a data warehouse, it’s a database. I think that that actually leads to the third reason they’re doing this is revenue. I think that they’re moving away from Google Analytics 3 or Universal Analytics because GA4, I think, in my opinion, has a better integration with Google Ads, makes Google Ads easier to use in terms of audience creation and just the connections between analytics and ads. Ads is obviously Google’s moneymaker.
Then due to, yes, there are privacy implications, consumer privacy implications for why they’re adding more strict data retention limits, but that also forces us to utilize BigQuery, which by the way is a paid tool. I think you and I have offline talked about cookie deprecation and things like that, which is a different topic, but somewhat related. Cookie deprecation essentially is going to make retargeting as an advertising venue not feasible anymore. Those ads, those retargeting ads from Google represent a good chunk of the pie for their revenue every month. They’ve got to replace that amount. That might have some implications to, that might be one of the reasons why they’re doing this. Lo and behold, money would be a reason they’re doing it.

Jarrett Smith:
Surprise.

Chris Sietsema:
Yeah, shocker. Yeah. Better product-

Jarrett Smith:
But Chris, GA4 is free.

Chris Sietsema:
Yeah, yeah. Yep.

Jarrett Smith:
If you’re looking into your crystal ball, I mean, where do you think this is going?

Chris Sietsema:
Well, in many users who’ve been in the platform GA4 for a while, you’ve probably noticed I have that if Google Analytics 4 was a vehicle, that vehicle’s going down the road at 55 miles an hour and Google is simultaneously trying to change the tires on it. They are making changes all the time in realtime. That’s something we should probably hit on too in that if you don’t already subscribe to the Google Analytics alerts and newsletter, do so, because they’ll keep you informed as to new introductions and updates to the product that are coming out because they’re happening all the time. For example, when you and I first dove into GA4, there was no such thing as bounce rate, and some of us were doing back flips, “Thank God, no more bounce rate.” But guess what? [inaudible 00:16:38] it’s back.” Many people are happy about that because they relied upon that faulty metric. There was no conversion rate. They brought that back. If you’re doing e-commerce, average order value hard to track down. It’s not anymore. There was no landing page report. They just added that a month ago.

Jarrett Smith:
Oh, I missed that so much. I was like, “Come on guys, this is such a…

Chris Sietsema:
Well, it’s back now, thankfully. I think they’re listening to a degree to those whispers and complaints about what’s missing from the new platform, and they’re slowly adding those things in, but they’re also including new features that we didn’t have before, which are really nice. There’s certain things that I wish they would add still that are not there. For example, the channels. Google buckets are referral sources into groups called channels. Organic search is a channel direct as a channel display is a channel. In Universal Analytics, you could create your own custom channels. You can’t in GA4. There is new ones. You’ll see organic social versus paid social. They can draw a distinction between the two. There’s organic video, so traffic from YouTube or places like that. That’s awesome that they’re bringing those in, but you can’t change or edit any of those. I’m hoping that they allow that to happen.
For segments or little lenses that you can place on your report, I want to see everybody who came to the site from Nebraska or who accessed the website from Twitter or what you can add, you apply segments or little filters on every report. In Universal Analytics, you could save those. You could have a segments roster, or a list of segments you would utilize all the time. You can’t save segments. You can create them or comparisons or filters is what they’re called now in G4. You can create those, but you cannot save them, which is silly.

Jarrett Smith:
Yeah, that’s really inconvenient, because those segments, I think looking at aggregate traffic just really doesn’t tell you that much. You really have to dig down into individual slices of users. Yeah, that’s been one of my gripes, which I guess takes me to my next question, which is, if you’re looking at the what’s actually been improved from your perspective as we move into GA4 and maybe what’s where we’re worse off saving segments I think is one of those items where we are worse off than we were in Universal Analytics. But it’s not all bad. I mean, there’s some cool things there. What are you loving about GA4, and what are you saying scratching your head on?

Chris Sietsema:
I’ll get the worse stuff out of the way first. It does take some time to get used to, period. People who are jumping into the system for the first time are lost, and that’s okay. All I can say to those folks, “Just get more reps. Just keep going.” What’s the quote from Churchill? “If you find yourself in hell, just keep going.” Not every marketing team also has the resources and time to create a custom program. That’s a weakness of the platform, I think, because it does require some customization. The analogy I would make between Universal Analytics and GA4 is that let’s say you’re going to rent a room, you need a place to stay and you need a room. Universal Analytics already has a bed and a couch and television sit set and the sink and a bathroom and everything is there that you need to live.
GA4 has some of those things, but there’s no paint on the walls, there’s no carpeting, there’s no baseboards. You really need to go in and customize everything and make it a livable space. Some folks will say, “Great, I can make it my own. That’s wonderful. Others will say, “Oh, I have to make it my own?” I would say, if you’re in the former of that group, great, embrace that. But if you’re waiting for Google to create some platform like you had in Universal Analytics that everything has worked out for you, you don’t have to really do any thinking or strategy about how you want to measure and what your measurement program should look like, you’re going to be waiting for a long time. That’s a weakness or an opportunity for, I think, everybody. The other worst thing about it is that there are those data retention limits we talked about.
There’s also what’s called, I don’t know, if you’ve experienced this with any of your Data Studio reports, I should call it Looker Studio now, by the way. Your Looker Studio reports. There’s this thing called quota limits, and maybe some of your listeners have run into this, but if you are creating a Data Studio/Looker Studio report utilizing GA4 data that has a bunch of charts and graphs and tables and scorecards and whatever, and let’s say you’re sharing that thing on a conference call with maybe say 8 to 10 other people on the call and everybody’s looking at their report from their machine and their own office or home or whatever they’re at, the chances of that that thing will break within 20 minutes are high, because there’s this thing called a quota limit. Have you run into this?

Jarrett Smith:
No.

Chris Sietsema:
Good for you. I’m happy for you. You will. The quota limit is basically the system has been taxed, the report that you’re utilizing, that everybody’s accessing the data from, there’s been too many data polls or extractions of the data from GA4, and so charts will just start breaking. For example, I’ve got a higher ed client up in the Northeast and they have a Data Studio report that’s basically broken out for every college, every department. It’s the same report, but just the filters are applied to show this department versus that department and all the various metrics. When they look at that thing altogether, there are, I want to say, 18 to 20 different pages in that Data Studio report. It breaks every time, because there’s quota limits. That’s a thing that people will be running into, for sure. Is there a solution to that? Not yet.
Basically, it’s one of those things where you have to limit the number of folks that are looking at it. There’s just all these hoops you have to jump through to make sure that if you want to share a report and distribute a report, which is the point of Looker studio or Data Studio, it becomes a little more arduous. That’s the not so great stuff about GA4. The good stuff is that it’s more accurate, there’s less sampling. Universal Analytics always utilize sampling. To provide those reports quick, fast, and in a hurry at the stamp of a finger, they wouldn’t look at all your data. They would look at most of your data and extrapolate the rest. GA4 doesn’t utilize sampling as much, and so the data’s more accurate, which is nice. I always feel a custom is better, more custom, more better.
Like we were talking about earlier, I want to make my own room, I want to customize my living space. I want to make sure that this platform is unique to me as possible. With GA4, you can do that more so than you ever could with Universal Analytics. You can create your own events, call them whatever you want, come up with your own naming conventions, make it less Google Analytics and more your brand here analytics, which I like a lot. Then the other piece, I really think is just the visualization component component. Yes, there are quota limits for Data Studio or Looker Studio. I need to start calling it that, but there’s also like we talked about some of the explore reports, like there’s those funnel analyses, the segment overlaps, there’s better pathway analysis, so you can see how people move through the website or through the app or from event to event, from behavior to a behavior, which can be very eye-opening and helpful when you’re building out a program and building out content to appeal to an audience.

Jarrett Smith:
I had personally have been a fan of the new attribution model that they have, the machine learning model. I don’t really honestly know if it is more accurate than what was in Universal Analytics, which I feel like any attribution report has to be taken with the grain of salt, but I do like the way they present the data a little bit better. It does feel a little more useful and a little more comprehensive in the way that it tries to represent the user journey, the sources, and that they’re waiting things, just the presentation, the whole way they present. It seems a little more in tune with what I think is actually going on.

Chris Sietsema:
I would agree. I think that the jury’s still out only because I haven’t seen it really work to the point where it’s completely different. Part of the reason is that in order for any attribution model to work properly, you’ve just got to have a massive amount of data, just gobs of data for it to work properly, so it can do all the math and reach all the points of statistical significance and all that good stuff. The biggest difference to folks who are not familiar with attribution models are what the attribution model difference is between Universal Analytics and GA4 is Universal Analytics relied upon what’s called last-click attribution, which means whatever the last source is that provided that traffic, that last source is going to get all the credit. The analogy we probably talked about before is whoever pitches the last nine or the ninth inning is going to get credit for all the pitchers that are for the win, and none of the pitchers that played the game innings one through eight are going to get any credit whatsoever. That’s last click, which is no fun.
Now, that was the default in Universal Analytics. In GA4, they have a new attribution model that is selected for you by default, which actually cold cross-channel data-driven. That’s just a fancy word for we are going to look at all the data and we are going to determine based upon the behaviors that were taken by the audience, which channel or channels had the most impact on the user’s decision to finally convert? However you define conversion, we’re going to look at how each channel played a role and give more credit to those maybe earlier in the funnel that had an impact. The way they’re doing in that is basically, again, collecting gobs of data and then drawing correlations between behaviors earlier in the journey and seeing those same correlations with the final conversion event.
And so, for example, if we find that, “Wow, on the person’s, let’s say the average visitor takes five visits before they convert,” and at some point those that watch a video, for example, really converted at a high rate, there’s a high correlation for whatever reason, between conversion behavior, whether it’s apply or enroll or form, submit, whatever it is, and video behavior. Whatever channel led to that video behavior, whether it was in the first, second, third, fourth, or fifth visit, that’s going to get most of the credit. That’s a very simplified version of how it works. But again, it takes a lot of data for it to work properly, and I’m holding out hope that it’s going to be better. I just can’t say for certain if it is yet.

Jarrett Smith:
Yeah, it’s definitely different.

Chris Sietsema:
The step in the right direction, for sure. Anything the last click is a good move.

Jarrett Smith:
I think the unnerving thing about it, to me at least, is it is very much a black box, so how they’re arriving at that it’s, “I don’t know, trust the robot.”

Chris Sietsema:
Totally. Yeah.

Jarrett Smith:
Whereas if you were talking time decay attribution or something like that, you’re like, okay, “In theory, I could work this out. I can wrap my head around how it’s arriving at all this.”

Chris Sietsema:
Yeah, really, I guess there’s three options. One is you rely on whatever the robot says, which is the default. It’s that cross channel data driven model. You can choose another model if you want. In the attribution settings within G4, you can still go to last click or first click or linear. Linear is the one where everybody gets a trophy that all the sources are weighted equally. The other third option, which sounds like a bear, would be to use something like BigQuery, some big database tool, pull all that data out and then run it through your own model that you create or you build or you buy separate from Google, which again, sounds like a whole lot of resources and not much fun. Probably a more accurate way of going about it, but holy cats.

Jarrett Smith:
Is there anything else that you’re just really loving in GA4? I got to tell you parameters, you really opened up my eyes to how useful parameters could be, and collecting all those extra decorations on your events can really produce some interesting reports.

Chris Sietsema:
Yeah, that’s exactly the way I would put it. There are decorations. If an event or a behavior that we’re tracking is like a birthday cake, then the decorations are the frosting and sprinkles and fondant and candles and all that good stuff. For example, a lot of my higher ed clients really want to track when someone hits the apply button. We’ve been able to do that for always, really. That would be an old school on click event. But the issue is for the universal method of tracking, Universal Analytics method of tracking, we could only gather three bits of data. Maybe like, okay, they clicked apply, what page were they on? And maybe what program? There’s three parameters right there, and we’re done. That’s it. Now with GA4, you can attach extra decorations on that birthday cake, such as the course name. What was the program type? Is it like master’s, doctoral, executive ed, whatever it is, categories of the course, what college it’s at, what university it’s at, whatever.

Jarrett Smith:
Start terms.

Chris Sietsema:
Yeah, start term. The position of the button on the page, the link text. Did they hit apply now, apply here, which was it for? So there’s UX implications or user experience implications. The problem is not whether we’re going to have enough data. The problem is going to be whether we’re gathering too much, how to tame that. What I’ve been working with clients on, is basically asking the question. Okay, I know you want to gather the faculty name for the professor or the instructor for that particular course. Will you ever sort by that? Will you ever create a report to sort by that? Yes. Okay, let’s get it. No, then let’s leave it behind. Let’s not get data just for the sake of getting data. Let’s have a intended purpose for it, or a plan for it. But for all those other things, you can absolutely say, “Yeah, I want to sort by course name and by program type and course category or whatever it is. That’s all pretty important.

Jarrett Smith:
Good stuff. Is there anything that isn’t there that you really have your fingers crossed will come back?

Chris Sietsema:
Yeah. I think some of those things that we chatted about a little bit like the channel definitions. The quota limits, I hope those actually go away because those are a thing. The other thing is that when you are creating an exploration report, which is the souped-up customer reports that are new to GA4, if I create that, I can’t necessarily give you edit privileges. If I create a report, it’s mine, I’m the owner, and I’m the only one who can edit that exploration report.
You can view it, I can share it to you. It’s read-only mode, but you can’t go in and say, “Oh, I adjusted your report, and here it is,” which is probably in some cases a good thing. If you create reports, nobody goes in and messes with your reports, but that’s one thing that I hope they fix. Also, it’s a bit interesting, we talked earlier about how there’s no sampling in GA4. That’s true. I’ve seen issues where not all the data will come through straight away to certain reports. I’m hoping that they fix that and make it a faster, more usable tool. Again, it’s free, so we can’t really complain too much, but there are some speed issues associated with GA4 and how long it takes to load reports and things like that.
But primarily, the sharing privileges is an annoying thing. Now, to get around that real quick, if you wanted to, let’s say I create a report, I’m the owner, and I share it with you for read-only mode, you can duplicate a that report and that duplication is now owned by you, but now you’ve got more reports than you do.

Jarrett Smith:
Twice as many reports.

Chris Sietsema:
Yeah, you’ve got duplicated reports, which is silly.

Jarrett Smith:
I know that you’ve helped implement GA4 for a lot of different folks, and so I’m curious, in what ways is this maybe changing our reporting processes a little bit? What can you tell us about that?

Chris Sietsema:
Within GA4, I think there’s three options for just data visualization, for reporting, dashboarding, whatever you want to call it. There is the reports section, there is explorations or the custom reports explorer, and then there’s a Looker studio or Data Studio or some other visualization platform. I think each of those options, each of those three options have a use case. The first one reports, again, they’re pretty shallow. There’s not much data in there. If I’m going into a meeting in five minutes and I need to get a number quick, fast, and in a hurry, I’ll just go there and get it. That’s the use case for reports. “I need a number, let’s go get it. Okay, great.” If I need to sit down and do some analysis and really start to dig in and see how do I break these metrics out? How do I compare this by course name or course type or different behaviors and different file types or whatever it is?”
If I really want to start to break things down, I’ll do that analysis in explore, so explore is where you get very nerdy. Then for any visualization platform, like a dashboarding tool, like a Looker studio, that’s where you go out and share the data. That’s where you present the data. If you’re sitting on a Zoom or a Microsoft Teams call or whatever it is, or even around a boardroom or a conference room table, that’s the implementation or the tool that I’ve used there to actually share it, because it’s more visual appealing, it’s not as… The explorer reports are handy and they really allow you to do some great analysis, but they’re not sexy, they’re not pretty, and so the Data Studio, Looker Studio is where I’d probably do that.

Jarrett Smith:
Have you seen any other operational changes that have had to happen as a result of GA4? Any process changes that you’ve noticed folks making?

Chris Sietsema:
A little bit. Primarily revolving around this idea of creating a custom program. And so, I think any marketer can tell you what exactly is important to her from a metric standpoint. What are our KPIs? What do we really need to keep our eye on? What’s important to us that serve as a guide for whether or not we are achieving success? To actually build out and customize a program is a different skillset. Internally for some organizations, I’ve seen folks who are graduating up to a data analyst role that also involves not just looking at the data and preparing reports and siphoning through different metrics, et cetera, but also configuring things. Tag Manager, which we probably talked about in a previous episode, Tag Manager is a vital tool for GA4. I cannot envision utilizing GA4 to its maximum potential and capacity without Tag Manager. That is a skillset that is pretty vital, and that’s a lot of internal folks that I’ve been working with have been building those muscles for Tag Manager.

Jarrett Smith:
Yeah, because Tag Manager’s quasi technical.

Chris Sietsema:
Yep. Yes. Yeah. It was built to supplant the need for a developer to do all your coding work for you. You and I who are marketers can jump in and actually place tags and place script and tracking code on a website with really just by following directions. It’s not too terribly technical. But at the same time, Tag Manager allows you to listen for those very specific behaviors that are important to you and fire tags that feed events to GA4, those custom events like the Apply Now button we talked about, or FAQ buttons or click to play the podcast episode or whatever it is. Those folks that are utilizing Tag Manager are building their wherewithal to understand what to listen for and how to trigger those events, so they populate GA4 properly with all the decorations on all the different cakes.

Jarrett Smith:
If somebody is listening to this and maybe either they want to build up their GA4 and Tag Manager muscles more, or they have identified on a role on their team where there’s an opportunity for someone to build up those muscles, what are some of the best resources that you would point folks to? I haven’t looked at it in a while. A while back, I was looking at Google’s resources on GA4, and I found them lacking, maybe because the platform’s still under development. It was underwhelming. But what are some of the go-to places for training and getting really serious knowledge on how to use these tools?

Chris Sietsema:
I think your assessment of the Google tools is right on to use a more technical term, I just call them trash. They’re not very helpful. They’re very good [inaudible 00:38:47]. There’s been this whole spring of new voices and folks that are really trying to help other people figure this whole problem out. The areas that I typically rely upon or folks that I typically rely upon are YouTube. There’s a really great amount of YouTube channels, so you can actually see the tool and see what button to push and when to push it and where to go and where to find certain things, how to work through certain problems. There’s no shortage of resources there. The places I typically go are called Measure School. There’s a really good YouTube channel, and there’s also one called Analytics Mania, which is a great one as well. Those two channels, they’re independent of one another. They’re two separate channels, but the two folks that run Measure School and analytics media are very, very good. I rely upon them heavily

Jarrett Smith:
At your recommendation, we used Analytics Mania in-house to get our team up to speed, and it’s really been helpful.

Chris Sietsema:
Nice. Google has a quiz you can take. If you look for the GA4 credential quiz or whatever, it’s a quiz and there’s 50 questions. You can take the quiz and get your certification for your LinkedIn profile, your website or whatever it is, or your resume, whatever it is, you can absolutely do that. It’s something that I would do. But I’ve also seen folks who’ve taken that and say, “Yeah, I just looked at their materials in one screen and took the quiz in another. You almost have a work built-in cheat sheet, so you’re not really learning too much without getting your hands dirty. Those tools, those YouTube channels, I would certainly look at. The other thing I would do is I would always encourage my clients to make a wishlist. What are the events that you’ve never been able to track before? What are the behaviors that we know we need to measure? Let’s make a wishlist.
From that wishlist, let’s determine for every item on the list, let’s identify the parameters that we want to attach or the decorations to each cake and identify that the various ways that we can create tags for those in [inaudible 00:40:58] and just start going, to start doing things. Whether you are perfect, you’re getting A in all those processes, doesn’t matter. The fact that you’re doing them and working through them is the most important thing. You just need practice and reps

Jarrett Smith:
Well, and I think one thing that maybe I’ve learned this from you is that with GA4, you’re a bit more on a journey. You can do the basic setup, you can start collecting data. It doesn’t have to be fully baked. You may not have baseboards, you may not have doors on your cabinets yet, but you can add those things on. To your point, even your first attempt at adding them on may not actually much like me putting on actual cabinet. Doors may not be perfect the first, second or third time you try it.

Chris Sietsema:
Yeah. I’m really digging this home maintenance metaphor, because it never ends. As a homeowner or anybody who’s managed a property or whatever, it never stops. It never stops, right? There’s always something to do. There’s always a list of things that we’re trying to improve upon. I would say, governance of the platform is also a crucial skill, going forward, in terms of, all right, we’re gathering data, we’re collecting the data. Can we utilize it? Are we wielding this tool to the best of our capability? If not, how do we change things? Do we change the naming conventions? Or again, if we’re collecting all this data, do we ever sort by it, okay, no, let’s clean it up a little bit? There’s new pages, content sections of the website that are being brought on. Do we need to update that? Maybe we’re going through a website refresh or a redesign. How do we plan for that? And so, it’s always an ongoing process, just like the management of a website or an app is.

Jarrett Smith:
Yeah, absolutely. One thing I think you’re quite good at is documenting what you’ve put down so that when someone in a key role, your analytics person moves on to their next job, that there’s some sort of artifact left behind that tells you, “Hey, how is all this arranged actually?”

Chris Sietsema:
Thank you. I appreciate that. Yeah, I think that just like we talked about earlier, how Google Tag Manager, that tool is basically attached to GA4, going forward, in a similar vein, I don’t see how you could actually do four configuration preparation of a measurement program without writing it down it. There has to be some documentation. No matter how fancy, ornate, simplified that is, we’ve got to write it down for two reasons. Number one, when you’re creating it for the first time, it’s almost like a guidebook as you’re implementing tags and making sure that things are tracking properly. But then when you see some events come through, you might ask, “What is that? What was that one again?”
So, the documentation becomes, at first is a recipe for configuration of the program. After that, it almost becomes a historical, it’s like a glossary. It’s a historical record of everything that you’ve got, that like you said, you can pass on from one to the next if you’re doing it properly. Everybody from the CEO, from the intern can read that thing and understand where to go, what to do, and how to utilize it, and how and why this program is built the way that it was built as a true reflection of us.

Jarrett Smith:
Well, Chris, there’s been a lot of really good information. If folks want to reach out to you to find out more and maybe even get some hands-on help with GA4 and analytics set up, what’s the best way to do that?

Chris Sietsema:
Probably through my email, which is Chris@teachtofishdigital.com or the website is Teachtofishdigital.com. I’ve also put together, we talked a little bit about documentation. I’m happy to share some sample documentation with anybody who’s listening to this. If you go to Teachtofishdigital/GA4, teachtofishdigital.com/GA4, you can find a sample document that I’ve used. It’s not editable, but you can make a copy. It’s just a Google sheet that you can access. One of the tabs in that Google Sheet is a, how do you use this document, so you can check that out and read it.

Jarrett Smith:
Yeah, and I do think anybody who hasn’t done their documentation yet, Chris, you’re doing them a huge solid by putting that online and allowing folks to go get it. It’s a big, big leg up. Anybody out there who’s interested, I would encourage you to go snag that Google sheet. It’ll save you a lot of time and keep you organized.

Chris Sietsema:
It’s good to see. Every time I’m in there, I see a couple other people in there at the same time, so I know it’s being utilized, so that’s nice.

Jarrett Smith:
Well, Chris, it’s always fun to talk to you and to continue to learn, so thanks so much.

Chris Sietsema:
Thanks for having me.

Jarrett Smith:
The Higher Ed Marketing Lab is produced by Echo Delta, a full service enrollment marketing agency for colleges and universities of all sizes. To see some of the work we’ve done and how we’ve helped schools just like yours, visit echodelta.co. If you enjoyed this podcast, please subscribe and leave review on Apple Podcasts. As always, if you have a comment, question, suggestion, or episode idea, feel free to drop us a line at podcast@echodelta.co.

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Jarrett is our VP of Strategy and the torchbearer for all things digital. Since joining us in 2014, he’s made it his mission to help clients seize the power of smarter marketing strategies—and reap the rewards.