Leah Davenport Fadling: Welcome, everyone, to another episode of Fundraising Today and the Go Beyond Fundraising podcast. In today’s episode, we’re going to be exploring the latest innovations in the digital marketing and fundraising landscape. Specifically focusing on how your nonprofit can utilize Google Analytics 4 to enhance your online presence and optimize the acquisition of names at the top of your marketing funnel.

Joining me is Emil Isaakov, one of our rock star data analysts and Allegiance Group + Pursuant. And Emil, you’re going to walk us through all the changes implemented with GA4 and how nonprofits can optimize their websites for their goals.

Emil, welcome to the show!

Emil Isaakov: Thank you! I’m looking forward to helping nonprofits modernize and adapt to some of the changing landscape when it comes to marketing and data analytics.

Leah Davenport Fadling: I know this is going to be a really rich discussion, and you’ve prepared some awesome notes for us. A lot of nonprofit organizations that we work with here at Allegiance Group + Pursuant come to us for help with their website. And making sure that your website is set up to accurately capture all the activity that’s happening and make sure that it’s actively tracking and measuring against whatever goals you have is really important. And it’s an important conversation to have right now as we’re looking at our strategic plans for 2024.

So, for those who are tuning in, and Google Analytics 4 is maybe a term they’ve just seen floating around on the internet and they’re not really sure what it all entails, what is Google Analytics 4 or GA4, and how is it different from the previous version of Google Analytics?

Emil Isaakov: Yeah, so Google Analytics 4 is the newest version of Google Analytics. The former version was called Universal Analytics or GA3, depending on where you see it. But it is Google’s attempt at modernizing and thinking long-term as far as data collection, storage, all that kind of stuff. So, the old version of Google Analytics — I’ll just call it UA or GA3 throughout this podcast — it was around for, I don’t know, 10+ years. Everyone relied on it. It was a very powerful tool, and there’s still some things in GA4 that aren’t quite up to that standard yet.

But Google, the idea with the new version, GA4, is that they wanted to make sure they were ready to handle all this data. Most websites that I’ve worked with in the last decade have used Google Analytics as their data analytics platform. So, you can imagine when most of the web uses this to store data, they want to think about it that way. And this is actually one of the powerful things that comes with it.

So, let’s just start from the beginning with the differences between Universal Analytics and Google Analytics 4. Universal Analytics — anyone who’s familiar with it — it was very session-based. Any kind of tracking or data analysis you do is done on a session level. So, let’s say a user comes to your website from an organic search on Google or Bing or what have you. That session is what’s recorded, and that’s the focus of all the data there. Whereas Google Analytics 4 is more of an event-based tracking approach. And what that means is, an event is any kind of action that a user performs on a website, whether that be clicking on a button, submitting a form, downloading a file. All of those are events, and they can be tracked — some of them are already tracked – they can be tracked with GA4. So, it’s a very powerful and flexible data tracking approach, and it’s scalable for millions and millions of events. That’s the idea with it.

With the free version, you have the ability to track up to a million events a day. For most, almost all, websites, it is a powerful tool. Right now, it’s slowly being built out. It has a lot of powerful tools right now, but it’s going to get better. So, I think that’s one of the first main differences between GA4 and GA3, I’ll just call it. It’s a little easier to say it that way.

The next thing I think that is really different about the two is with Universal Analytics — and this is one of the things that people don’t quite like about GA4 — there’s a lot of pre-built reports that you have on the website, or you have things to track audience-level data, behavior-level statistics, positions. You just had a lot of reports that were already built in there. And for the most part, I would say when I used Universal Analytics, I would use maybe 20 to 30% of the reports. So, there were some really good ones there, but there were some that I rarely used. I might dip my toes in here and there. But they were still useful — they were all pre-built. And with GA4, we don’t quite have all those pre-built. But what you can do is you can customize your own reports within the interface. So, whenever you log into GA4, you can see, “Okay, I have my website domain report here. I have my campaign report here.” You can pre-build these reports, and it’s very useful if you just put in the extra time initially to set up those reports.

There’s also a thing called Explorations, which is, I think, the strongest portion of Google Analytics 4, and that’s their custom reports interface. In the past, (we) had a custom reports interface, and it was limited. You had some things that you created in there, but it was just not quite as powerful. You can’t do things like you can do in GA4 where you can look at, let’s say, cohort analysis on a more granular level for event-based actions. If you wanted to see, let’s say, people from specific states in the U.S. that came from specific campaigns that performed specific actions. That granularity, it was very difficult to create custom reports in Universal Analytics for that, but now you can do that in GA4. So, I think that’s one of the really powerful tools you have available to you in GA4.

Another thing that I would say is kind of useful in GA4 is that, out of the box without any extra customizations needed, you have some built-in tracking that is included. So that includes things like file downloads, video interactions — specifically with YouTube — site search, or “about” link clicks from the website. So, you have, let’s say, a lot of “about” links to other websites, you can track when someone clicks on those links, what the link URL is. Oftentimes, we’ll add a little more tracking around that where you can tell what was the text that was clicked on, things like that.

And then, the last thing I would say is form interaction. So, when someone starts a form, submits a form, typically I would double check that specific data point because sometimes it’s inconsistent, so you might need to clean that up. But that’s another thing that comes with GA4. You have a lot of out-of-the-box tracking that you don’t need to set up. So, when you do tracking, you don’t need to do anything else for that; it just comes with it.

The next thing is AI features in the free version of GA4. So, in the past, Google Analytics 360 customers, which were the paid customers — it usually had a steep cost, I think it was something like $100k+ for a year. They had some of these AI features. But now a lot of that is coming to GA4, so the types of things I’m referring to are anomaly detections. So, let’s say over the course of a few months, let’s say a quarter, there was a steep drop in sessions, and it’s out of the norm. Whether it be because it’s not a weekend and you saw a steep drop or things along those lines, it flags that for you. So, you can set up alerts for anomaly detection. And if there’s something out of the ordinary — maybe tracking for some reason dropped, or you’re no longer being indexed by Google Search, things like that — this anomaly detection is very useful.

Another thing on top of that is predictive metrics. And now, this is something that requires quite a bit of volume of traffic, purchases if it’s a paid site. We’ll just refer to donations because a lot of our nonprofits are fundraising clients. You need a lot of those in a short amount of time — I think it’s something like 28 days, so around four weeks of data. And consistent quality of that data. If you’re able to fulfill specific requirements, you have things that are predictive metrics, and what these are, let’s say you’re trying to predict the amount of traffic you’ll get or the amount of purchases or donations you’ll get in the future. Predictive metrics will help you predict the number of donations and then the predictive revenue of that donation metric. So, that can be very powerful, but it does require some extra work to implement and make sure that you’re technically eligible to use that feature.

And then the final thing that I think is different between GA4 and Universal Analytics is that Universal Analytics could retain your data down to a very granular level, like individual actions and events for 10+ years — however long you’ve had tracking enabled. But one thing that — and this is all about Google trying to think about the future and not wanting to store the data of the whole web on their databases forever. But instead, they have a 14-month retention window, and this is something that can be frustrating, but don’t worry — it’s not all your data. So, the way I would describe it is, you have all your aggregate-level data, so let’s say your campaign-level data going back to, I don’t know, 10+ years. That isn’t an issue. It’s more when you want to get down to the event-level data, where you want to know the exact number of the, let’s say, webinar file downloads that you had from a few years ago. That kind of data, you can’t currently store past the 14-month window. There are solutions to that, and we’ll talk about it later, but that is one thing I did want to flag about GA4.

Leah Davenport Fadling: Yeah, thank you so much for that comprehensive overview of what some of the top changes between GA3 and GA4 are. And I think what I find interesting as I’m trying to sum up some of these things in a nice, succinct idea is that GA4 basically looks at your website as a place for marketing conversions to happen. And it wants to specifically focus on those things because it recognizes the function that a modern website performs rather than the old way of doing things, where Google Analytics really wanted to focus on the total journey someone had on a website. Because it’s starting to recognize that companies and organizations are most concerned with actions that someone takes on your website versus just their browsing behavior. Do I have that right?

Emil Isaakov: Yeah, to a certain extent. The way I would describe it is with Universal Analytics, it is about that user journey within a single session. And you can track conversions, they were called “goals” in the past, but you couldn’t get as much granular data on that type of conversion. So, let me provide an example. So, let’s say you have a donation submitted and you have all that data in your donation platform but also in Google Analytics. But with Google Analytics, you can add extra layers of information to that specific donation event or purchase event. So, you can add things like, what is the form name or ID? Is it a one-time or recurring donation? And how much is the donation value, and then what is the transaction ID? So, those are five layers of extra added information to just a single goal or conversion.

So, it’s one of those things that, again, it’s about scalability. It’s about making your data much richer, so being able to distinguish between this donation and another donation. And a lot of donation platforms have that ability already baked into their platform, so Luminate or Raiser’s Edge — a lot of these platforms already have that. But what happens with Google Analytics — and the power of Google Analytics — is that it allows you to better track how you acquire that initial traffic. So, you have that final piece in your donation platform, but what GA4 brings is that extra layer of information of, where did someone come from, how long did they stay on the website, what pages did they navigate toward. All of those are stored in event-level data. By using all that data, you can provide a user journey, but you can also get more granular data or layers of data for each action. So, I would say that’s probably the biggest difference — you have more layers of information you can add to each action.

Leah Davenport Fadling: What do these changes mean for the average nonprofit who is trying to optimize its website for things like lead acquisition? I’m thinking, like, getting more names on mailing lists or just getting some additional information about folks that are visiting their website that they hope become donors.

Emil Isaakov: The way I would answer that is that with this event-based model that comes with GA4, you can better track actions leading up to the lead acquisition. So, with the old version, you could easily track that final step, and you could set up the funnels, but you couldn’t surface that data as well. So, let’s say, for example, a donation form or a lead acquisition form that you wanted to track. Typically, what we want to do is add at least at another step before that that you can track. Let’s say I landed on the form or on the page with the form, and I viewed it, maybe clicked on it. I can track each of those — the view, the click — and just see how far along in the process did a person get before they fell off. And if, for example, you start to drop off after a specific step in the funnel, you see, “Oh okay, maybe there is friction there.” It’s just a little bit cumbersome, maybe they didn’t see the next step of the form.

There’s a lot of things that you can get from this event-based kind of model that you normally couldn’t. You could create a funnel, but it wasn’t very easy to surface that information and act on it, make decisions. For example, the classic example that I use is, in the past, I had a client that had a multi-step form — eight steps. And we noticed that most people would get 80% through the form and then toward the end, they didn’t complete the action. We were like, okay, why is that? So, we went through the actual form process to see what was going on. And we noticed that the last step or last two steps were below the fold for the form, so they would get to that eighth step or whatever it was, and they wouldn’t actually see the next step, so they thought they were done. But if they went further down, they could have downloaded something, maybe signed up for our newsletter, but they never saw that.

So, that’s the power of GA4 and how it can be used to optimize pages, to optimize campaigns. It’s just really powerful in really understanding how each of your users are interacting with your website. And that’s mainly what I’ve been trying to help our clients do — understand how users are using it, how can we improve the user experience, how can we improve conversion rates? All that stuff can be done with GA4, and it’s because it’s so flexible and customizable. It requires a little bit of work to do, to get all the extra added features, but once you do, you can do a lot more with the data you have.

Leah Davenport Fadling: I love that. So, with all this additional power and customization and flexibility, what are some recommendations that you would have for a nonprofit that has switched over to GA4, but they don’t really know what first step to take to optimize their website to help them get more of the conversions that they’re wanting to happen? What are some steps they can take?

Emil Isaakov: Yeah, that’s a good question. So, I use a fairly, I would say, I don’t want to say an industry standard, but in analytics, we try to systematize a lot of different things because it helps streamline the process. It helps us tackle things from a point of view where we can iterate and improve each time. Let’s say you do an analysis over a period of a year, and then you want to make sure after you do that analysis you have some insights that leadership can make decisions based on.

I’m going to go through some of the steps that I recommend our clients and nonprofits go through, and this applies to any type of company, I would say. It’s just general knowledge to apply to your own use case.

First step I would say is identify your goals and KPIs. And first, I’ll focus on the goals. When I say goals, I don’t mean, “I want to increase the number of email signups.” I want you to instead think about your business goals. At the top level, what are you trying to accomplish? Actually, what is your mission statement? You can even start there if you really want. And from there, you can then slowly work your way down into providing you a data collection and analysis strategy. So, let’s say your business goal is to maximize your donations and your revenue so you can better get out your message to people about a specific cause that you really care about. So, let’s start from there. Don’t think about KPIs, because I think we fixate too much on KPIs, and we get too much into the weeds. What’s the metaphor people use? Don’t get too much into the trees, you miss the forest. Don’t get too deep into it just yet. Think about it from the top level.

Once you know what your business goals are, then you can start to think about what is an action that you want your users to perform on your site that will lead to accomplishing your business goals incrementally. So, typically donations are a very common primary conversion because it allows you to keep your funding up to a level that allows you to keep sending out marketing materials — “Okay, we have a specific event where you can learn more about our cause” or whatever it might be. It allows you to do so many more events, so that’s what I would consider a primary conversion.

Once you establish all those primary conversions that are key to your business, I would then go one step down into what I consider a secondary conversion. So, these secondary conversions, how I would describe them is that they will help lead your users to eventually complete those primary conversions. So, common examples of secondary conversions are a lead acquisition–type of action. So, is someone submitting a form, whether it be a newsletter, email signup, webinar where they can learn more about your business or what you do. That’s what I consider a secondary conversion.

And to accurately identify a secondary conversion, it is important to analyze data over a large span of time because you don’t want to just pick at random, right? You want to make this type of decision from a data-driven approach. So, this is where you would actually dig into the data. Let’s say you look at people that come from specific campaigns and they spent a certain amount of time on that page. And that you notice that when people spend two minutes or more on the page or they navigate to a specific page on your site, they’re more likely to actually convert.

So, what I often see this with is — this is a very obvious example — but if you send a user directly to your donation page versus another page that you want them to learn more about your business first, typically they will convert more often just because there are (fewer) steps needed to finish that conversion that you really care about, which is that donation. This is where you would definitely want to look into your data and see what correlations are there between things like time spent on pages or signing up to a newsletter. People who come from that newsletter later on, maybe through the email channel — so, that would be a channel or dimension within Google Analytics 4 — are likely to convert. So, that’s what we often see with some of our clients — if you are able to get them on your email newsletter, and then they come back later, they often convert more than someone that would come from an organic search or even a paid search, stuff like that.

So, that’s your secondary conversion, and the idea behind this series of steps where you slowly go down and down more is that you don’t lose sight of the primary goal you’re trying to achieve when implementing your data collection and analysis strategy. So, you slowly work your way back, and then you identify what things can I optimize for that will lead me to that primary conversion?

The next thing, the next step in that once you’ve identified all these conversions, is to implement your data collection strategy. So, once you’ve identified your primary and secondary conversions, identify what other layers of information you want from those conversions. Again, I’ll use a donation conversion as an example. With a donation conversion, you want things like, maybe the donation form ID, so you can identify which donation forms perform better than other donation forms. It may be something about the copy or the page layout for that donation form to be doing better.

So, you want to have a way to identify what exactly are the people looking at and which donation form they’re converting. And you want something like a donation form name or — if you don’t have an ID, you can use a name. Another thing is it a one-time donation or recurring donation. Another thing is obviously the donation value — you want to know how much they actually donated. And the last thing is transaction ID. So, those are the five event parameters we call that you want to collect. So, identify those so later on, once you actually implement this, you have those all on order so you can make your implementation smoother.

And then, once you identify those, then you can start to implement it. We usually use Google Tag Manager because it’s the industry standard and it’s a really good feature-rich tool for implementing things like that. You can track form submissions, visibility on the page. Let’s say you have a form that someone’s finished submitting. They then want to be able to trigger on that form submission, but sometimes you can’t do that on just a basic form submission or a page, a thank you page, sometimes that’s another common way of doing it. Instead, you could do it as a thank you message. I use Google Tag Manager; I would recommend doing that.

And then last but not least, this is something that might be review for most people, but make sure whenever you’re doing any kind of campaign landing page, you include your own parameters within your landing page URL. So, for Google Analytics, that’s the UTM parameters of source, medium, and campaign at the very least. And then if you have other platforms that you use, make sure those URL parameters are being used as well so you can identify how each campaign is performing against each other and optimize based on that. So, that’s the implementation portion.

The last two steps are integration of your — and this is an optional step, I would say — integrate your data with other marketing tools. So, since you’re using Google Analytics and it’s a Google tool, I highly recommend using things like Google Ads if you don’t already use it. It’s a very powerful marketing tool. I’ve been getting the word out about Google Ads. Since they’re both Google tools, linking between those two and working between those tools is very easy. For example, let’s say you have a hundred people that have converted over the last month. What you can do with Google Analytics is create an audience based on people who have converted or people who have donated or have submitted a form. Then once that audience is made, you can import it into Google Ads and actually target those people or similar types of users to help them convert in some other way. So, that’s why I would recommend Google Ads. And you can also do a similar thing with Facebook Ads — not quite as well integrated, but you can implement Facebook pixel or Meta pixel. And what’s something that’s newer is the conversion API to optimize your Facebook Ads campaigns. And both of these tools use a ton of data to optimize your campaigns, and they’re very powerful if you just make use of their optimization tools.

And then the final thing I would say — and again, this is optional, but I would recommend it — is link your Google Analytics property with Google BigQuery. And the reason why I recommend this is, I mentioned before there’s this 14-month retention window that Google Analytics has enforced, and the reason for it is because they don’t want to carry all this data. But what this allows you to do is store your event-level data in basically a data warehouse. And you might think, “Oh, is that another added cost? We don’t really want to worry about that.” With this connection that you make to Google BigQuery, you get a free tier of basically data storage and data computation. Once you go past that free tier, you do have to pay, but typically, unless you’re a very large organization, you don’t have to worry about that for maybe one or two years. And once you do actually start to exceed the free tier, the amount of money that you have to spend for an extra gigabyte is two or four cents. So, it’s a very affordable solution for storing your data long-term. And I would highly recommend it.

And then, really the last couple steps are — I can’t go too much into detail on these — but I would say analyze your data. This requires way more time for me to explain and go into detail about. I could talk about this for hours, it’s my job. But it’s just, look at your data or break down your data in different ways. For example, some questions you should ask during the analysis process are, what traffic channels or sources lead to the best name acquisition? How far along in the funnel do they get from these different channels or sources? Another question is how far in various conversion funnels do users get, and how can you reduce friction within that funnel?

And then, after you do all that analysis and you can gain some insight from that, you can iterate on your campaign strategy for the next quarter or the next year, things like that, and improve it. Analysis and data are all about making the decisions using the data to back it up and then improving with time. Iterate and improve, I would say. And I guess that would be – I know that’s a lot, but those are the steps I would recommend to go through when you are trying to use your data in a way that is going to improve your conversion rate, improve your business goals and help you attain those business goals.

Leah Davenport Fadling: Yes, that definitely was a lot, and I’ve got a couple of follow-up questions, but I love that you walked us through that whole step-by-step journey because I think for a lot of folks who don’t even know where to get started, it can be helpful to have a picture of what that entire process looks like. And I was glad that you ended on data, because data analytics is something that, like you shared, you do day in and day out, and it’s really, for the clients that we work with at Allegiance Group + Pursuant, it’s the first step to working with the client. Looking at their historical data and making recommendations for their campaigns — and especially holistic campaigns based on their data and based on their goals.

And so, when we’re thinking about nonprofits, where their website is one channel for fundraising, social media is another channel for fundraising, direct mail is another channel, and we’re living in this multi-channel, omnichannel ecosystem for fundraising, knowing how things are performing in the digital world is so important. Especially with the limited budgets that nonprofits are so often dealing with.

Let’s go into a specific example. How can Google Analytics 4 and doing some data analysis on your GA4 data help, for example, which social channels or ad channels are giving you the best bang for your acquisition buck? Nonprofits ask this a lot, especially in the lead-up to year-end. How can we get our pipeline nice and robust for year-end giving and for Giving Tuesday? So, what kind of answer would you give a nonprofit that was asking you that question?

Emil Isaakov: If a nonprofit was asking me that question — specifically, what social channels they should focus on and things like that — I would use historical data if they have that available already for those various channels. So, what you would do is you would pull a report from Google Analytics using something like Source Medium. And this is where the UTM parameters that I mentioned before in your URLs are really important. If you don’t put those in there, we can’t really track that social channel or that specific campaign, so make sure that’s already in there.

But once you do have that in there, we can identify, “Oh, there’s a thousand users that came from Snapchat or 300 users that came from Facebook,” and they led to, let’s say, a five-minute time-on-site metric, and the conversion rate is something like 5% for lead acquisition. So, you can bring all that into a single report within a matter of a minute and then look at it over a large period of time, on a month-by-month basis and see that, okay, it seems Instagram posts or TikTok posts are a really good bang for your buck. You want to make sure you unify this with your cost data. This is usually pretty easy to do with Google Ads because it’s integrated with Google Analytics already, but it’s not as easy when it comes to social channels.

So usually what you’ll do is you’ll have cost data in, let’s say, a report that you pull from the social channel, and then all the other data that you pull from that same social channel in Google Analytics for your web data. And then once you unify that, you can understand, okay, you have a few columns for the amount you spend on a campaign over the course of a quarter, let’s say; the number of impressions you gained; the number of clicks you gained; the number of sessions, users that came to the website. So, this is going to the GA data. And then once you unify all that data, you’re able to eventually — let’s say it’s a donation campaign — as the last column, you can compare the cost versus the revenue. The metric that’s typically used for this is return on ad spend. So, you can calculate that metric toward the end and see, “Oh okay, our return on ad spend is above $1, meaning for every $1 we spent, we gained more than a dollar.”

So, I would definitely pull a report from your social analytics database — so, typically it’s the Meta ads database or the Meta Pixels database. Pull that report for the same time period that you would pull it in Google Analytics, unify that data, look at it from a cost analysis. And then, based on return on ad spend — or, let’s say, calculated return on ad spend. So, let’s say you don’t have donation as a conversion; you set lead acquisition as conversion. You could do a calculation roughly to get a return on ad spend. The company I used to work for, leads were the lifeblood of the business, really, because if you don’t have leads, you have no way to actually get sales. And generally based on data, let’s say over the course of the year, the average number — so let’s say you have a thousand leads, and then you have sales, and then you calculate based on the number of leads, I made this many sales, had this much money at the end. You calculate the average value for each lead. And this is an estimated value but based on a year’s worth of data, you can safely assume it’ll be in that ballpark. So, you can use that as another return on ad spend calculation toward the end.

So if you’re able to combine all this data together, you can give a rough estimation — it’s not exact because every year is different, every campaign is different — but you get a rough estimation of okay, this specific campaign did a really good job of getting us 300 leads over the course of a quarter, and we can safely assume it’ll give us roughly this much amount in revenue. And you can make your decision year-over-year based on that. So, that’s how I would approach that.

Leah Davenport Fadling: I think we have time for just one more, maybe two more questions. So, let’s use another example, a nonprofit’s newsletter. That’s a really common secondary conversion that you describe. If a nonprofit is listening today, and they really want to grow their list of new names of folks that are signing up for their newsletter, looking at their Google Analytics for data, what could be some hypothetical recommendation you could give them to improve that segment?

Emil Isaakov: I would first look at a few different things. I would look at the landing pages that often help convert into a newsletter. I would look at different channels, sources, and mediums that help convert to that. And then, based on looking at all that data, looking at which channels convert to a newsletter and which landing page. I think landing pages are typically more indicative of how often people will convert because let’s say you have a newsletter form lower down on the page on one page and then at the very top, maybe the top right corner, for another page. The likelihood of someone converting on that second page is more likely. So, I would look at landing pages, the different acquisition channels, how often or likely are people converting to a newsletter signup based on those channels?

I would look at a few other things, maybe the paths that users took from before the newsletter signup. So, in GA4, there’s an exploration or a custom report called the page path exploration, and what that allows you to do is, you can at the very end put newsletter signups, so all the newsletter signups within a given time period. And work your way backward to see what pages people are most likely to come from that lead to that newsletter signup, or which actions prior to that newsletter signup did people perform. So, it gives you a little more insight into how people are using the website and what’s more likely to lead to that specific newsletter signup conversion.

Leah Davenport Fadling: So, I think this is the final question for us to wrap up today. We know that the cut-off date for moving over to GA4 was last summer of 2023, and that any data that a nonprofit has is essentially stopped, is not being tracked anymore in Google Analytics. So, if a nonprofit needs assistance with getting everything up to date and up to speed with GA4, what’s a quick recommendation that you could make for them?

Emil Isaakov: I would say if you feel comfortable with Google Tag Manager, and you have a Google Tag Manager account, go in there, set up with Google Tag, create a — actually, first go into Universal Analytics. And it probably has already created a GA4 property, because this is what Google did after the cut-off. It automatically created the property. But the issue is a lot of these properties don’t have data flowing to them. It was created, but it was never flowing.

So, what you go and do is you go into that GA4 property that was created – or if it wasn’t created, go into the admin section, and create it. And then once you do that, there should be within the admin section a data streams selection. You click on that, and there’s a specific ID that you need in there. Ultimately, that’s what we need. And that ID corresponds to something, like basically an identifier by which Google Tag Manager can send data from your website to Google Analytics. Once you create that tag in Google Tag Manager — the Google Tag, it’s called — and enter that ID in there, make sure you’re sending page view data. It starts sending all that data along with file downloads and video interactions, all that form submit stuff.

It’s a pretty quick process, and if you just want to start from the basics, I would set up a Google Tag Manager account if you don’t have one. If you do, add a Google Tag with that ID, and send data to the GA4 property. Check back the next day to see your data’s flowing, things like that. And you should be good to go, at least from a start.

Leah Davenport Fadling: Emil, I’ve certainly learned buckets today. Thank you so much for tuning in and sharing some of your expertise with our audience. And if anybody’s listening or watching today and this all sounds overwhelming and you would like for an expert to come in and help you out, Emil at Allegiance Group + Pursuant and some of our other experts would be more than happy to give you a little boost there and step in and take things off your hands.

Emil Isaakov: Yeah, it was fun. One of my goals when I first joined Allegiance was helping nonprofits modernize and adapt to the digital landscape. I know from working with nonprofits in the past in my other roles that it can be a little intimidating at first. But I think it’s vital that we all adapt to the digital landscape just because there’s a lot of powerful tools here that you can make use of with at least the very bare minimum investment. But if you want to really tackle it from a data-driven approach, yeah, let us know. We’re always willing to help. We want to help nonprofits achieve their goals.

Leah Davenport Fadling: Thanks so much, Emil. Have a great rest of your day!

Emil Isaakov: You too. Have a good one.