 All right, we'll go ahead and get started. Thank you so much for joining us today. We're really excited to have you all here and have this conversation with you. My name is Mickey Reggio. I'm a project manager and analyst at Parsons TKO. And we are a consulting firm that works with non-profits and mission-driven organizations on their strategy and outreach and marketing. And so we work with IT teams fundraising to help them all better connect with their audiences. So let's dive right in. So you guys probably know that Google Analytics is transitioning from Google Analytics 3 to Google Analytics 4 in the summer of 2023. And so this could be a scary change for some people. There's a lot of different things happening, a lot of things to prepare for. And so we're here with our amazing panelists to help you figure out how to prepare yourself and your organization best for this transition. Also, please at any time, please feel free to drop any questions into the chat and I'll ask them to our panelists. And with that, let's do some introductions. Jason, I'll pass it off to you. Thanks, Mickey. Hi, everyone. My name is Jason Hamrick and I lead Data and Insights at Phase Two and we're a digital agency based just outside of Washington, D.C. in Arlington, Virginia. We serve commercial companies like Johnson & Johnson and Major League Soccer, Health and Wellness organizations like Advent Health in Northwell and public sector companies like the Cystic Fibrosis Foundation, the Crohn Foundation and the EEOC. In my role, I help our clients navigate data and analytics strategy, marketing operations and implementation and privacy and consent issues related to customer data. I'm back to be here today. Thanks very much, Jason. I'll go next. I'm Stefan Bird-Proeger. I'm the head of the Data Strategy Practice at Parsons TKO where we work with organizations to help them make sure they're getting the best value out of their data and using their data as a strategic resource. And so a big part of that is thinking about data operations but also the role that data plays in business processes throughout the organization. And so this is a very interesting topic for me in particular. I've been a denizen of Google Analytics for the past 12 years or however long it's been a product. In fact, I remember when it wasn't even Google Analytics yet back in the Urchin days. And so it's a unique opportunity to sort of live through another phase transition, changing the life cycle of this product. And this is exactly the kind of work that we live to do is to help people navigate changes like this. And I'll pass it off to Nate next. Thanks, Stefan. Hey everybody, it's great to be here. I'm Nate Parsons, one of the co-founders of Parsons TKO. My own background is in technology and user experience design. I did development for 10 years and user experience design for five. And now I focus a lot on long-term technology planning for organizations and life cycle management of technology. And so changes like this GA3 to GA4 change which are really complete sort of product swap are the high things on my radar because I think a lot of organizations have a hard time managing these sort of cycles of change when things look like point upgrades but really they are strategy changes for the organization and how they address and sort of staff these different kinds of important capabilities like having insights and the ability to optimize their outreach. And so that's kind of one of the reasons I was really excited to participate in today's panel and I'm really glad to be here. And I'll hand it back to Mickey to get us started. Thanks so much, Nate. All right, now that we're all acquainted with each other let's dive into the questions. So first let's start at the basics. What is Google Analytics 3 and what is Google Analytics 4? Yeah, I think I can take this one or at least start. So Google Analytics 3 is beyond the universal analytics Google's all-in-one web tracking, reporting and analysis software issues by about 65 or 70% of websites. And GA4 is its successor. I think it's 12 years in the making is as Stefan said I think for us it represents this major shift. It's first overhauled the system in the last 10 years. So Stefan, do you have anything to add? Yeah, yeah, I'll jump in there. You know, Google Analytics 3 I think in particular is very important for the nonprofit sector because it was the free tool. You know, in fact, you know, I think, you know Jason spoke to its market penetration sort of internet-wide we've seen it even higher for the nonprofit sector. We actually did a survey, a study of more than 1500 nonprofit websites, .org websites and it was on 95% of them. And a lot of those remaining 5% were just broken. They didn't seem to have anything. So it really speaks to its penetration and it's evolved in a lot of ways with the nonprofit sector but I would say even more so the nonprofit sector and their understanding of data and analytics and website data in particular grew around this product. It's really been a bedrock, you know even down to terms we use things like page views and bounce rate. We know those words because those are the words that Google Analytics taught us to speak. You know, when we talk about website behaviors and so there's a lot to be said for that and you know, as far as what is Google Analytics 4? You know, even, you know as we were discussing, you know, how do we frame this? Google Analytics 4 is not a transition of Google Analytics 3. It is a brand new product. It is misleading to give it the same name and just say it's version 4. So it is, it's from the bottom up a whole new vocabulary in terms of how they talk about things. It's a totally new analytics product and that's, you know it's a big part of why it's important to take note. It's not something that's gonna happen quietly. Yeah, and just to tag onto that a little bit I think, you know one of the questions people might have is like why is Google doing this? You know, why are they changing from, you know a very well-beloved and, you know successful product to a brand new one. And I think there's sort of two big thrusts from where I said, you know one of them seems to be that you know, there's a lot more liability in data collection than there used to be with GDPR and the California Consumer Protection Act and the things going on in Ohio. You know, the cost of misusing or miscollecting people's data is going up and tools like Google Analytics 3 we're gonna be very difficult and expensive for Google to engineer to be compliant where GA4 can be engineered to be compliant sort of out of the box. And the other piece of the puzzle there is that you know, Google is a commercial business and they're trying to ring more money out of the marketplace and GA4 is a tool that is designed to support commercial ventures and sort of upmarket more sophisticated ventures that rely more heavily on paid advertising to a much greater extent than GA3 was which did that plus a lot of useful things for the community. And it was also sort of more of an all-in-one tool. You know, as Googles become more sophisticated they have built siloed more specialized tools that they want to weave people together into a collective ecosystem rather than have one all-in-one that kind of does a little bit of everything. And so that's a little bit of the, you know piercing the veil, but I don't think that's as important as what you should do about it now they've decided to do that. All three of you touched on this a little bit that so many organizations use Google Analytics 3 but what specifically is so different about this launch this transition from GA3 to GA4 compared to GA1 or 2, for example. Yeah, I mean, I'll speak to that first. Please. I know the others have things to add on but a lot of the changes to Google Analytics that we've seen in the past, they were always incremental. In a lot of cases, you didn't know about it. You know, there were no press releases. You know, there were no news articles about it. It was sort of one day you opened up Google Analytics and a new feature was there. You know, even it's sort of funny to think about, you know, versions. You know, when was 2, when was 3? You know, they had some name releases but behind the scenes there were lots and lots of versions and every time you opened it, there was something new in Google Analytics and so even though it went through these versions, the whole history, a lot of the changes were to just a tweak in how the data is collected. You have to swap out the code on your website because the technology has improved but it was still the same product underneath and it was still the same data underneath. Enter Google Analytics 4. This is a total, you know, Google Analytics as we know it is dead. Long live Google Analytics. And so this is a big, a complete change in product and really the end of the product that we've known for over a decade. Yeah, I think that's fair and I don't think that we can overstate that importance. We've had as a community 10, 15 years to develop best practices and templates and pretty much anything you wanna do inside GA3, someone in the community is likely solved that problem. And now us as a community, both the practitioners and as people who are interested in data are having to learn those things anew in many cases. So it's from a technology standpoint, there is that big data shift. The data you collect in GA3 is not gonna be available to you in GA4 so that your live first date really is kind of a milestone or a watershed date for the community. We're kind of pushed back to where we were, you know, and a few years ago and to Stefan's point, even though there have been changes incrementally along the way, we have a whole host of best practices and things we know work. Well, I think that what that means for organization is, organizations it's great opportunity to think about data strategy, to think about marketing and communications anew. And learn those new terms that GA4 can be bringing to us. Yeah. So we know that Google Analytics 4 is coming, whether we like it or not. And so we'll talk about some alternatives if you decide not to use the Google Analytics tool in a little bit. But for those organizations that are considering moving to Google Analytics 4, can you guys talk about the cost of this and how to measure that cost? Yeah, I mean, I'll let Jason start off, but I'll tag in after that because I have some thoughts. I know Jason has done a lot of really great research on this. Yeah, I think we need to think about two kinds of costs first, about one time migration costs, so we're both planning and executing that migration. Because like I just said, the data can't come with you. So if we're thinking about migration, it really is the configuration of that new tool. So there's no such thing right now. It's a one-click migration from GA3 to GA4. So there's going to be some staff cost or some consultants cost. And maybe a couple of hundred of hours, depending on how complex your current marketing system is right now to make that migration. So there's that one-time cost. And then ongoing staffing is going to be different. I think as both Nate and Stephanie have alluded to, GA3 is this all-in-one system. You get collection and analysis and reporting all-in-one. GA4 expects you to separate those ideas out. And so if you look forward to staffing and training and retraining, understanding those individual pieces is going to be an ongoing cost. Yeah, I mean really well said. And I think that the skills profile change is a lot too. In Google Analytics 3, there was sort of like you said, there's such a great community support. There were so many good templates and things to use out of the box. You didn't necessarily have to add sort of unique skill sets to use the tool once you understood analytics and kind of what your data strategy was. But in Google Analytics 4, they're adding two really deep new skill sets that they're expecting you to learn. The first of which is sort of report design and insight design. In Google Analytics 3, you've got the reports basically out of the box. And if you liked and liked those, you could go and install a template of reports. And it would give you a new suite of nice reports that the community had made. In GA4, they're expecting you to use a whole brand new tool, Google Data Studio, and connect it to your analytics holdings and then mine your own insights out of that. And the community over years will eventually build some templates for you to use. But for the next couple of years, it's going to be a very heavy lift on those organizations to mine their own insights. And similarly, one of the really big changes is the data retention policy between GA3 and GA4. In GA3, you could basically hold on to your data forever. It starts to get sampled and it wouldn't be always completely accurate, but you could look back for long periods of your corporate history. And in GA4, your options are two months or 14 months. And so what that means is that your analysis of big events or things that happened last year has a 60 day window to occur. So your data and insights team now has to be operating really quickly after a major event to see how it performed year over year and to have those insights and those questions sort of predetermined because the amount of research and engineering time they have is going to be greatly circumscribed to actually analyze that data. And the reason that is is because they've moved data warehousing to a new product or an existing product that they're adding to everyone's mix, which is Google BigQuery, which has this ability to retain, I think, up to four or maybe five years of data, but even it's not infinite. And it is a data warehousing tool that most people are not familiar with. And it has its own querying system and its own way of mining insights. And it also, in essence, needs to be connected to Google Data Studio. And so that's a whole lot of new staff capacity and expertise that most organizations don't have on hand and weren't expecting to have on hand and are going to have to dedicate for multiple years, not just for a two month or three month transition. I'm going to soapbox for a second here because I want to have a quick interlude because we've already said a lot of things that are critical of GA4, the switch to it, a lot of the risks and dangers. I want to pause for a second to say that Google Analytics 4 is and is going to be a very good product. It is extremely cool as a data professional. I think they've done an impressive job of architecting it from the bottom up. It's incredibly flexible. If you think about tools and the evolution of tools, it's like going from something like MailChimp to something like Salesforce. It's like, wow, there's a lot of power here. Wow, there's a lot of capability. And there's a lot of complexity. There's a, you know, all of the possibility of what it can do is what makes it hard to own and hard to use, especially for small teams. And I think, you know, Nate and Jason, you both hit on exactly the right point, which is the cost to nonprofit organizations is going to be the loss of skill, in operating the analytics tool, the analytics processes. And I think this is, you know, the answer of how much it costs is a big function of when, there's the cost of planning what you're going to do. There's the cost of actually building and putting it into practice. And then there's the ongoing cost of owning it and using it. And this is, I think this is where this transition is hardest for the nonprofit sector because we actually have a lot of analytics talent in the nonprofit sector. It is buried in other people's day jobs. You know, when you have an analytics question and, you know, nine times out of 10 in the nonprofit sector, you are going to your web developer or you're going to your social media team or you're going to whoever the intern is this summer because, you know, they're young and probably know how to use it or, you know, are willing to dive in and figure it out. They have the time to figure it out. And so that's going to be a big part of this cost is a loss of that sort of inherent talent that we've had buried in our staff. And I think the expectation and the need to build a new talent across so many different tools to use the tool successfully. It's Google Analytics 4. It's, again, a great product. It's an enterprise product. It's an enterprise product that's going to be tough to use in the sector. But we're going to have to figure out how we adapt to losing Google Analytics 3 because to be clear, if we haven't been clear yet, Google Analytics 3 is going away. It doesn't matter who you are. It doesn't matter how quietly you use it. You know, if you log in in a dark room, it's still going to be gone. You know, it's, Google Analytics 3 is going away for everyone next year. And, you know, we've watched in some of the questions in chat. There's some promise of access, I think up to six months of access to data in Google Analytics 3 after it expires. But, you know, who knows when and how much Google is going to change. I have to say, I'm already surprised they're moving as fast as they are and retiring the product. I thought they would give Google Analytics 3 longer. But the truth is, it's they're scared of GDPR and this is how they're protecting themselves. And so it's not just the tool they're getting rid of. It's the risk they're getting rid of. And I think that means we should expect our data to go away on the timeline they're promising right now. Yeah, and Stefan, I think you make great points. And I want to take this interlude to say, okay, what are we losing? But what are we gaining? Right, because you mentioned how great GA4 is just as a piece of software. What Google is doing right now with GA4 is just introducing all these new services and capabilities to a free tier of software, which used to be only available either not at all or only in their paid tier, their Google 360 service, which was $100,000 a year to start. So they're taking a lot of these more advanced analytic capabilities out of that tool and releasing them to this free tier, which is great for us. So you get better conversion tracking. We're getting better campaign tracking and some new campaign tracking options. So not just a person's current marketing source or attribution source, but their first source of the first time you saw them, which is great for fundraisers and development officers especially. Lots of improved new event tracking, including out of the box things like outbound clicks and downloads and video engagement, social engagement, stuff we get out of the box. The thing I'm most excited about is predictive audiences. So look at the data and see which audiences are most likely to donate. How can we then use those in Google ads or in other tools and retroactive analysis. So people came to the donate page. How did they get there? People came to the event registration page. How did they get there? All of those features were only in the paid tier and now they're in the free tier for us and that's fantastic. It's simultaneously offers these great audience focus, predictive and forecasting metrics at the same time offers better privacy and consent controls. So for me, that's really impressive. And so as we're talking about the change and the staffing changes and the loss of institutional knowledge, we're getting all these other things too. Depending on the thread of change, there's been a lot of discussion in the chat about how to migrate data from Google Analytics 3 to Google Analytics 4. And Rick from my team has so graciously started to answer some of these questions in the chat. But can you talk a little bit about the best way to migrate this data, whether it's from GA3, whether it's to GA4 or perhaps another tool? Well, I'll start with a sort of orthogonal answer and then I'll let these guys answer the actual question which is that the first question about the migration is where are you going? And I think that for a lot of folks, default answer is gonna be, well, I wanna get from three to four. But really the question now is like, I wanna go from three to the best fit tool for my organization. And that's a different choice than the nonprofit community in particular has had for a long time. It used to just be, we use Google. And now I think it's going to be, we have an option between maybe three to five tools that really fit our organizational place, because there are privacy-focused alternatives to Google 4 that are more like Google 3 that are all in one solutions that you could deploy and still have a lower staff cost of ownership or expertise cost of ownership to use. And that's a choice that a lot of organizations should consider before they're just like, oh, let's get the stuff from three to four. And I think that that's a really important thing for a lot of executives and you communications teams to consider, right? That like, this is now a product selection choice. It's not just a GA3 to GA4 migration effort. And I think that that's the first question that most people should be asking, which is what is it, what do we want it to look like to own and operate our data strategy? And once you have that sort of figured out, then you can kind of decide like how to get from three to four or three to another tool or three data to BigQuery to another tool or to four later on. I mean, there's a lot of options once you kind of answer that fundamental data strategy ownership question. But if you don't answer that, you might be really sad if you just moved from three to four. And so I'll let our experts kind of dive into actual mechanics of it, but that's a really important strategic question that people should focus on. Yeah, I think that's, that's fair, Nate, that the strategic question needs to come first. If the strategic question does come to you going from GA3 to GA4, there is no one quick migration right now. I think as we've talked about a little bit, just the data as it exists in the format that it's collected in GA3 cannot go into GA4. They use a very different data collection model, the details of which we could talk about for hours, but another time, but at a high level, the two pieces of data, the two types of data aren't compatible. And so if you try and make comparisons among them, you might end up with mistaken analysis. There are opportunities to potentially take the data of GA3, as Nate said, put it in BigQuery or some other tool, and then reshape it and remind it. And so you might have your GA3 data here in your data studio or Tableau, whichever system you use, and your GA4 data over here in GA and data studio or Tableau, whichever system you use, and you're comparing them. But I think that July 1st data is important because we are gonna lose that easy period over period, pre and post comparison. I'm gonna triple down on that strategy point. To answer the archiving question, what that looks like depends on your organization, your relationship with data, your relationship with your data tools. If you have a data lake, great for you, that's a great place to put your data. I'll second Jason's point about, don't think you can just squeeze the new data into the same table. It's a different kind of data, different baseline. So much has changed. You need to recognize that this is different data. You'll have to come up with your own blend of herbs and spices if you really wanna try to draw a trend line through your data and your history. I think for most organizations, when we say archive our analytics from Google Analytics 3, let's focus less on the data and more on the insights, the stories that we wanna tell, the things that we are doing with the data. How are we using it? So I think for a lot of organizations, your archive of your GA3 data is gonna be your archive of board reports or wherever it is you go to report on your website data. So just be really thoughtful about the timeline in which you're gonna do that. What are the things that you generate as a team and figure out what you're trying to gain from analytics? What's the role of analytics in your organization? So that's what comes back to that data strategy point is we need to figure out, and the way I'm excited about the trauma that we're all going through, because I think it's forcing the nonprofit sector to reconcile with the fact that data is underutilized and underfunded. It's underutilized because it's underfunded. We don't, as comms practitioners, as fundraising practitioners, as mission-driven warriors at large, our organizations don't get support for data in particular. We always have to squeeze it in somewhere else. And I think this is a really unique opportunity for us to say, hey, something major is happening and we're about to get caught. People are gonna get caught recognizing that they have not focused on their analytics because August 2023 is gonna come and someone's gonna ask a question. They're gonna say, oh, oh, actually, turns out we're not collecting any data at all. I didn't know that. And it's gonna speak to the underinvestment that we've had. And so I think for people who are in this room right now, people who are watching this, this is a moment for us to proactively look at this change, get ahead of it, ask ourselves, why does this matter to me? Why does this matter to my organization? And work through those questions, talk through the things that we wish we were doing with our data. Having that sort of introspective experience, that's what we mean when we say plan for the transition, plan for what comes next. Because all of your answers to those questions are gonna be your requirements for what you should buy, what you should build, and then how you should be using your analytics in the future. This is data strategy. So it's a wonderful time. It's a wonderful time for data strategy. Nothing like a crisis. Let's not waste a good crisis and miss the opportunity. Thank you for mentioning that, Stephanie, because I do actually want to transition a little bit into more tactical ways that our audience and organizations can prepare for this change. So I'd love to hear all of your suggestions for different types of tools that could potentially replace Google Analytics 4 if an organization chooses to forego that. Yeah, I'll start off with, again, a sort of a funny side note answer to this answer, which is that one of the things that Stefan and I are working in the background and mostly Stefan to give him full credit here is a decision tree for organizations and a guided decision-making process for this. Because for each organization, it's gonna be a different answer potentially, but there are some really obvious and good strategies to pursue based on what kind of organization you are and what your data strategy capacity is and your focus on it is. And so, when we start talking about tools, I think everyone should just be aware that each of the tools mentioned that people will mention here in a second fit a use case. They fit a certain kind of organization that they are really good fit for, and we'll try and mention that here, but we're also gonna try and provide the community with a framework for actually making these choices and kind of saying, let me sit with this for a week or so and really kind of ponder it for my organization because some organizations may add capacity and decide to go a little more upmarket and like as Stefan said, kind of reexamine their data strategy and really approach it anew. Other organizations might look at it and be like status quo is good and others might say, okay, well we actually aren't getting as much out of as we wanted, but we still wanna have the opportunity for the future and that might be a really different choice, right? Like instead of an all in one tool, they might want a really good data collecting tool even though they're not doing the analysis yet. And so, just know there's a lot of different strategies you could pursue. And when we start talking about tools, they really should be picked with a strategy-first approach where you're like, we wanna do X, this is a great fit for X. Yeah. Nate, I think I wanna again, second everything you just said, if we are naming tools and thinking about the use cases, then if you're an organization who's basically right now and using Google Analytics 3 out of the box, basically turned it on and let it do its thing and you want that all in one, log into a single interface experience, probably the best alternative right now is a tool called Matomo. It's similar in how it thinks about data, it's free, it is that all in one solution of collection, analysis, and reporting. Like Google Analytics, it can be used in the cloud or you can also download it and use it on premises on your own servers. And it can be, you can use it really easily out of the box or it's endlessly configurable to be as privacy-aware and consent-aware as you need or as open as you need. Of course, the long answer is everything we've already talked about. What are your reasons for moving? Is it cost? Is it privacy? Is it utility? What's your current staffing? What are they comfortable with? How much new skill development do they need to do? How complex is the rest of your ecosystem? No, if you just have one or two other things, if it's you and MailChimp and out-of-the-box RazorDedge, for example, that's gonna play, that's gonna be a really big factor into which tool makes sense. And there are also a host of paid tools out there. Did you kind of take a little research to sift through? A disappointing amount of dissent on this panel. There's not much we can fight about here. I agree with Jason. I think if we're talking about features, if we're talking about skillset, Metomo is a great choice. Metomo, for anyone who hasn't heard of it before, which is probably everyone, they've been around for a long time. They built themselves as an alternative to Google Analytics and open source alternative to Google Analytics that was privacy-centric. And so they grew right alongside Google Analytics. In fact, if you go and look at it, they did a clever job of really head-on addressing some of the shortcomings of Google Analytics. And some of the problems, I think some of the sort of analyst use cases where Google users would make the wrong interpretation of their data, Metomo saw that. They're like, ah, we know how to change our interface so people don't make that same mistake here. Really great, it's a great tool. But it is, it's a new tool, it's a whole new ecosystem. And you need to know that you have a team that can set it up appropriately for your organization. It is not free and easy to set up. And especially if you want it to be free long-term, and there's a way you can do that, but it takes more effort to get it set up. As Jason mentioned, there's like an on-premises version of that. So this is, you know, it's not a plug and play. And I think the other thing to note about Metomo as a choice is you are committing yourself to that legacy model. And I think there's a, you know, it's a small community that you're joining when you go with Metomo. Really good map to your existing skill sets, but it's with a small and shrinking community that you're joining. Google Analytics 4, again, let's not, you know, we're knocking it a lot, but one of the benefits of going with Google Analytics 4 is you will be following the herd and you will have that herd security. You're going to be surrounded by a bunch of other people who are struggling with exactly what you're struggling with when they also realize that it's not Google Analytics 3 and I don't know how to use this. And you can jump in with all of them and learn how to use it together and jump into the future with Google as they really are pushing people to be more, quote unquote, modern in their approach with data and GA4. But I think there's also, I mean, there are lots of other tools out there and some of this is going to depend on who you are and what your organization does. So there are tools that are really well optimized for publishers. Parsley is one that I know a lot of publishers already use. And so if your organization's, you know, outreach model is very similar to that of a publishing house, then looking at Parsley is a very good choice. I think the other thing to consider is what tools might you already have hiding somewhere in your outreach stack? There are tools, you know, I know HubSpot, for example. If you happen to be one of those organizations that has HubSpot, they have website tracking features buried in the platform. And so you may actually have some website tracking features that you already have access to. They are probably going to be very limited. But if you have a very limited use case, if you can commit to, we never have to say anything except how many hits the whole website had overall. Sure, yeah, you might have a tool that can do that. So yeah, look at your existing stack to see if you already have something else. Great, thank you. Now that we've talked about other potential tools and solution, what is the profile of a good Google analytics for a candidate? Well, yeah, I'll throw a quick answer out there, which is, yeah, I'll let you, because I know Jason has some thoughts here too. And I think that to me, the organizations that are the best fits are the ones that are really using data to inform business decisions. And I think that that's a smaller percentage of people who have tracked data than you might think. A lot of folks don't bring data into the decision-making process. They don't inform campaigns from next year with the last year's data and things like that. But the ones that do and the ones that want to answer harder business questions or want to have more insight into things that have been obscured a little bit in GA3 are really good fits for GA4, because as everyone's mentioned here, it's a very sophisticated and powerful tool and it can answer questions more completely than GA3 could when it's used properly. Yeah, I think that's right. Having organizations that are gonna be sophisticated enough or have a use case to use data and analytics for that decision-making process, I think it's gonna be part of it. Part of it is where on the revenue spectrum are you? Are you an organization where your website is just one part of your fundraising and revenue and marketing mix and your communication mix or is it the lion's share? And depending on where you are and the role that your website and therefore analytics play in your content outreach strategies, I think that really speaks to are you a good candidate for GA4? And usually honestly for those smaller organizations too, two or three people maybe in your marketing comm shop, the out-of-the-box features of GA4 work really well. And I think both of those answers are right and I would say for me, an organization that has a champion for their analytics capability, does your organization have somebody who is going to take on the responsibility of not just making sure that GA4 does what the organization needs, but helping people access that value. Because GA4 by itself is not gonna be self-service. You can't just set it up, give everyone a login and expect people to be successful because people are gonna log in and they're gonna say, I don't know why I'm here, I don't know what I'm asking of it, I don't know how to get the answer to the things I'm asking. So you need somebody who will say, I am gonna be the person who owns this. Whether you're just picking someone on staff like, hey, email person, you seem really techno savvy, like can you own this for us? That's gonna happen a lot of times and that's wonderful, keep that person forever. But I think if you're an organization that can truly invest in this capability, both in terms of time and probably also money, then I think you're gonna be very well served by Google Analytics. Because again, because it can be so customized, whatever your organization's definition of impact is, you can model that in Google Analytics 4. You can make it perfect for you. And if you have a sort of business intelligence, probably not unit, but a business intelligence approach, if you use dashboards, if you can build them, if you can move data from one system to another, then you're gonna do great with Google Analytics 4. It's gonna be wonderful for you. You need to plan for it, you need to invest in it, you need to build that capability, you need to build the customizations and build the skill on your team. But it's gonna be very good for you. So I think that's my amended answer. And I'll just, I'll just tag on to that. I think for a lot of organizations, like if you're gonna think like, what are the table stakes here? If you can't fund a Google Analytics or an analytics expert at 10 hours a week in your organization, it's probably gonna be some rough sledding for a while. So I think that's a really good baseline for most organizations. Like if you're looking around at your staff and you're like, my comps team can't spend 40 hours a month on this, it's gonna be tough. And I think that's a really good baseline from a lot of organizations to think through. And it can of course soak up a lot more time as Stefan was just pointing out. But I think it's certainly something that needs a lot of care and feeding and especially for the first year or two of operation. A lot of discussion in the chat about UA, which is universal analytics. And so what would your advice or guidance be for preparing for this disruption? Sure, I'll take a first kind of bet. Preparing for moving from universal analytics, GA3 to GA4. I think we've, it's going back to some of the things we've talked about. So audit your current strategy, audit your current ecosystem, figure out what data you're collecting. Which data, which of that do you actually need in order to answer those big business questions? So audit that current strategy, figure out a plan, maybe create a new data strategy that only incorporates that data you absolutely need. It's one of the things we've talked about since the outset now is, we have been very good at organizations as collecting lots of data for a long time. Oh, it seems just collected in MailChimp. Oh, just we'll use it eventually. And now we're at a place where we're all accountable in very real ways for everything we're collecting. So creating a data strategy that only collects the things that you need. I think it's gonna be important. Making sure that all those metrics are actually tied to real goals. Real, either website goals or big organizational goals is gonna be important. Documenting that across the organization. I think this is an opportunity for those little pox of expertise to come together. If you have someone in IT and in marketing and in fundraising and in communications, those people can now be talking to each other and have a unified approach. And that's the place to start is identifying by those little experts you already have, bringing them together. Yeah, I think, again, doubling down on that, it's that introspective process that I was talking about before. I think auditing is correct. And to be clear when I say audit, I mean, not just your technology, but your organization, your strategy, your business processes, understanding what you use your data for, how the data you collect moves through the organization, moves through people's brains to help people make decisions and really sort of figuring out the role that analytics plays. So figuring out everything that you have, what exactly are you gonna lose when Google Analytics 3 goes away, Universal Analytics goes away. And then I think, as Jason was describing, taking the time to look forward and figure out that strategy. And we actually, we have a toolkit that we're gonna be publishing. And once we get that toolkit out, there are some self-service tools, a process that we encourage people to go through. So we'll have resources for people to follow. But I think, whether you do it through that or you do it on your own or you have a consultant that you wanna work with, that's gonna be the process is to really figure out what do we need from our analytics. Why are we sad that GA3 is going away? What are the things we're gonna lose? And that's gonna be your foundation. And then what are the things we wish we were doing with data? That's gonna be your future. And that's what we should be doing. That's what everyone should do over the next, what is it, 13, 14 months? And so it's plenty of time, plenty of time for that. And we're ahead of the curve for the most part. Yeah, I'll just tag on one last piece there, which is like, one of the big questions data strategy-wise is do you know, do you know the questions you wanna ask of your existing data? Because if you do, you could get by with some PDFs of the reports of that data. I mean, you don't need any of the data going forward. If you don't know the questions you're asking of your previous data, that's where, and that data is valuable, that's where it gets to be more interesting and more expensive, honestly, to kind of keep that data so you can do additional analysis on it or different kinds of questioning of it later. And so that's probably your first question, is like, if you already think you know the questions you wanna ask, you can probably report that stuff out in a nice summary format today and not worry about the raw data. But that's a big choice because keeping that raw data is gonna be expensive. That's great advice, thank you. Moving back into kind of the tactical decision-making piece. If you're thinking about using an alternative to a Google product solution, what thought process should an organization go through to decide that? Well, I guess this is definitely something I think a lot about. Salter, my hat in the ring here, which is that, you know, I really think it comes down to a couple of things which is, you know, if the data can really advance your organization's mission or your success in useful ways, you know, and for a lot of organizations, that's true, then it's really about how much cost and effort you're gonna put into to achieve that value, you know, and I think that's a really big part of the choice here. You know, if historically you've had analytics and it's been kind of useful, but you haven't really made different choices or you haven't changed your, you know, content strategy or your outreach strategy or fundraising strategy based on that data, then a big investment here is questionable, right? Because you don't have a historic track record of, you know, getting a return on investment there. You know, if you have had some really good insights and you have been able to, you know, advance your organization's mission because you've had that data and you've made good use out of it, then it's time to do an ROI analysis and kind of decide like how much of our treasure are we gonna put into this effort, you know, because it's gonna take a lot of sweat and a lot of money to, you know, get there, you know. When I say a lot, I mean, it's always proportional to your organization and what you're getting, but I do think for many organizations, it's gonna be an order of magnitude or two orders of magnitude more than they've sent historically with GA3. So I do think it's really worth thinking it through. So that's kind of like a real high-level answer, but I'll let our experts kind of weigh in as well. Yeah, Nick, I think I can tag on to everything you just said, seconded. And the questions that one would think about are, you know, things we've talked about before. So what are your reasons for moving? What are you looking for in a new tool? What's your current staffing? What can they do? What do they need to learn? How complex is your current tool set? What sort of ongoing support do you need? Do you need professional services or do you have that capability in-house? What kind of training and tutorial sessions do you need, you know, different organizations and different pieces of software offer those? Sometimes they're offered by the community. And then thinking downstream about how do you need to either integrate that data with other data or then create it and use it in dashboards or reports. Who are gonna be the consumers of your data, not just the producers? Those are lots of things to think about as you're looking at a new tool. And there's that, what is your organization's approach to servicing that need? You know, I think the sort of analogy I always use is, are you an organization with a data oracle or an organization with data missionaries? You know, how well, how centralized do you want your data capabilities to be? Or how democratized? And I think that's gonna have a lot of implications both on what tool you choose at the heart of your analytics, be it GA4, Matomo, Parsley, Mixpanel, yeah, the whole list. Google, Google Analytics Alternative and you will get all the lists of every tool you could consider. There are so many out there, truly thousands. But what kind of service model your organization has for analytics is gonna determine whether you wanna have that centralized data resource or you want somebody to create internal resources that other people can use independently. And that's gonna, you know, how you wanna service that is gonna have a big implication for how you wanna set that up. Great point, thank you. As we're nearing the end of our time here together, I do wanna dedicate some time to answer audience questions. I know my colleagues, Rick and John, have been answering questions in the chat as we go. So if there's anything too that hasn't been answered, you wanna ask our panelists, feel free to resurface that in the chat. But first, I have a question from Liz. Are there any courses on GA4 yet that you suggest? Yeah, there are several and there are two that we suggest. I can probably put these in the chat, but two free courses are one offered by SkillShop, I guess three, so one offered by SkillShop, that's a introduction to GA4. There's a fellow named Julius who runs analyticsmania.com and his getting started with GA4 course is really great. And a third is a fellow named Simo Ahava, Simo is an Oracle inside the Google Analytics world and Simo has a whole host of courses around the entire Google ecosystem, GA3, GA4, Tag Manager, BigQuery, Data Studio. He's who a lot of us talk to when we get stuck. Also for all of our listeners, all of these links and resources will be on our website after, so don't forget to check back there to get more information, but back to you, Nate. Yeah, I was just gonna say, those are all fantastic. I mean, one more I might just throw on the list and this is on the sort of much pricier end of things is KS Digital, like their stuff is fantastic. It's another Google alumni who saw all the sausage being made inside the factory and then is coming out and telling people what's what. She's really great, the lady who runs that. Yeah, so that's just another one, but you're talking like for the whole suite there, it's like 10 grand or something, it's like one K for the first course and they go up from there, but so it's not cheap, but fantastic. Yep, those are good ones. I don't have any better than those in particular. I mean, I, Simo Ahava, to be noticed by Simo Ahava would just be amazing. His resources are tremendous. He has contributed more than any one other person, I think, and to sort of the practice of analytics using the Google ecosystem. So if you are an organization, if you are the person at an organization who is going to take on technical ownership to your analytics capability and you are comfortable with technical ownership, Simo Ahava is hands down your best friend. He's got all the answers. Well, I think we have time for one more question and this one comes from Erin. Erin is curious what a possible pathway might be for clients who use analytics minimally just to check basic stats, but do not use the majority of the powerful features of the platform. Yeah, I'd say that answer coming soon is really probably the short version of the story. Like I think you are all sort of hesitant to recommend one because frankly, we didn't have to answer this question two years ago. I mean, this was not something that anyone worried about. We're just like, well, it's just GA3. It's just, it's fine, right? And so I don't think there's an obvious winner. I don't think there's an obvious solution. I mean, as people point out in the chat, none of the things we've suggested today are totally free and a drop in replacement. And most of the things we're going to suggest probably initially are going to have a little bit of learning curve because there's just not the same bench of internet knowledge too. There's not all of the, you can't Google it and get like the guidebook that tells you how to do it in 10 minutes, right? I mean, and so I think we're hoping to start to answer that question, but honestly, I think this next year is going to be, there's going to be a wealth of research done by experts on that. And I'm sure Jason and Stefan will be contributing to that conversation, but I'd say the short answer is right now, don't jump at the first thing because I don't think there's a community consensus as to what that simple replacement tool should be, but there will be one. And I guarantee you in a month or six months, there's going to be a lot more information about that. Yeah, I think that's good. As you said, yeah, as you said, two years ago, we didn't have to answer this question. We all thought we would have three, four, five years to make the choice. All the GDPR changes now have accelerated the timeline. If one is not going to stay inside the Google ecosystem and move to GA4, I think the answer is, I may say a little bit TBD, if one is going to stay inside the Google ecosystem, then even an out-of-the-box Google Analytics 4 implementation will get you the basic page views, time-on-page, et cetera, that you're looking for, especially with their out-of-the-box events. Aaron's question animates me tremendously because this is like the heart of nonprofit analytics. And why I made this my career? Because the minimal, that word minimal means something different for a lot of organizations. And minimal is so undefined. And minimal is what most organizations are doing. And it was okay that we did that in Google Analytics 3 because minimal had the rest of Google Analytics to back you up when it wasn't minimal anymore. Because a lot of organizations do the minimal until the board asks how the one report did. And then Google Analytics let you go in and it let you figure it out and you could go all the way back three years ago to when we published that report and you could get the answer because the board needs to know. And I hesitate to give any answer on what's okay if you want the minimal because the quick answer is Google Analytics 4, great, follow the herd, go for it. But that minimal is gonna have a much, much harder wall than it ever did before. And so I think that's the real risk here of getting going too quickly into a new minimal solution. Yeah, yeah, Aaron, Aaron's your question. Thank you for your questionnaire. I wanna change my answer to Stefan's answer. You're exactly right. Doing that introspection is gonna be so important for some new organizations. All right, well, we are coming up on our time. Jason, Stefan and Nate, I wanna thank you all so much for these amazing insights and thank you to all of our attendees. Before you all go, please, we have lots of other resources that we would love to share with you. We have a podcast, we do at least monthly events, videos and articles and blogs all to help you make this decision. And we will have a toolkit coming up to all registrants via email. It will also be available on our website to help you make these tricky decisions. It'll walk you through exactly what to think about for your organization and it will help to guide you to choose whether you wanna go with a platform like Google Analytics 4 or maybe Matelmo. And so again, thank you all so much for coming. We really appreciate it and hope to see you next time.