 I'm Rick Richards. I'm a business analyst here with Parsons TKO, and that means that I look at all kinds of things. I look at what organizations want to do with their data, what data they already have collected, if those things align to their strategic vision. But I also dive into the data a bit more deeply than that and look at what's the quality of that data. Is it answering the right questions? Is it being used to answer questions that it ought to be used to? So this is the kind of genesis of where this comes from, basically how to get ready for GA4 and also, you know, on the back end, should I even use Google Analytics for? Is that a thing I should be moving to in the first place? We're going to assume if you came here today that you're actually really interested in getting started with GA4, and we'll want to take a look at getting you up to speed. And this is our agenda here. It's less about what we're going to cover and more of a why. A couple mantras here. We want to discuss the history of Google Analytics, not to bore you, but we want you to be up to date and understand what's going on and why it's happening. We want to review technical changes to the platform and big shift predictions so that you're in the know and you're prepared for to go into your organization and your teams and to speak confidently about those things. And we also want to plan next steps, help you plan next steps for you and your teams. Obviously, so you're prepared and you can follow up that confidence with rule know how. So we'll start with a quick synopsis, how we got here, the evolution of Google Analytics. And now Google Analytics has been around for quite a while, but Universal Analytics, which is kind of what everyone's been using. It'll be actually be slightly more than 10 years when it is sunset next summer, July 1. And it's a big deal. It's a really big deal. We'll talk about that a little bit, but you know, the, for the past 10 years, let's say. It's a standard for web metrics and not only is it the standard for kind of how conversations were against Universal Analytics has been totally free, totally free to customize totally free to get the data back out, whatever you capture in there. So it's a huge piece of many businesses and many orgs and especially since it's free many nonprofit organizations use this because it's right there you just flip a couple switches and you're getting data. You do a couple customizations that's free you're collecting more free data, you pull that out into Google Data Studio. Again, another free tool where you can create amazing dashboards using using all of that data. And while it may sound like, okay, we're just getting a new version of Google Analytics. It is not at all that simple, which we'll be talking about today. So J4 is going to replace Google Universal Analytics. Next summer, it will be gone for good. We're actually kind of in the sun setting phase now where you can be using both platforms, which is a recommended approach, both from us and from Google themselves. So, you know, whether you're just using something basic and you're just saying, oh, I'll just jump to J4 when Google tells me I have to, or you've really pushed the limits of Universal Analytics you set up all kinds of customizations, custom metrics, custom reporting, etc. It doesn't matter. Unless you are paying for a 360 account. It ends July 1 2023. And if you are paying for a 360 account, I think you get a couple extra months, and that's it. And there's some, there's some really good reasons for that and we'll we'll mention it as we go. I want to say, if you want to avoid data loss, and you want to avoid reporting discrepancies that are going to mean tough conversations with your teams and your boards and your constituents. If metrics suddenly change, if you don't do anything now, you wait till June 30 2023. And then the next day you flip over all your reports and suddenly all of your metrics look different. And if you can't explain that you're going to have some upset upset folks on your hands. But if you start talking about it now, you start teaching within the organization. And, you know, your board and your constituents out, you know, from within the organization, you start talking about how these metrics change, you start talking about how the data looks a bit different, but might be a bit more accurate, or might represent different You will hopefully be in a good place. So, and again, just to note that if when I say universal analytics, this is what people have just called Google Analytics up until this point. It's always been called universal analytics but nobody called it that everyone just said Google Analytics and so now Google Analytics for sounds like a new version new features etc. And it is much, much, much more than that, because as you may have noticed the unit has changed and many things have changed since 2012. The GA Google Analytics universal analytics was initially built. This is way back. It was a tool to measure UTM tracking and basically you could see how well your ads did. How well they performed because Google wanted you to pay them more money to run ads. So, easy peasy. And then more and more people started using it. And it became this more holistic tool. But it was still based around how people use the internet. A decade or more ago, right. It's a website based tracking tool. And that eventually people started using mobile devices more and so they kind of retrofitted mobile tracking in there but it was like separate and not really the same thing and yeah, it was not clean we just kind of kept bolting on pieces to a much older ship. And then, you know, because of all that it was GDPR and other privacy laws non compliant due to those not existing when it was built. So, GA for now, which really started kind of released to start being used in 2020 but it's still ongoing changes, very much in flux. That has been designed from the ground up around modern web behavior. It's been in the past five years since that's kind of when it's been developed apps are no longer an afterthought. In fact they inform how metrics are collected. And we'll, we'll talk a little bit more in depth about that on the next slide but you know, think about the way people used to use computers, just go home, sit down at their desktop, pull up some pages, go look at one site look at a couple different things that that was what universal analytics is measuring GA for really concerned with people from all different devices might be looking for five seconds might be just clicking a button and downloading something. All kinds of new ways to to measure engagement. Google tried to address a number of the these emerging privacy concerns if you're following news. You may know that they're still not quite hitting the mark from Europe's perspective. And that's that's still ongoing but suffice to say, way better than universal analytics which was just, you know, roll roll your own privacy GDPR compliance. And GA for is not really centered around ads Google that's still, you know, major profit point for Google, but it is not the main thing it's not there, the main driver. And so there's so much more. That's available in this tool. However, that means that, you know, they want to the, you're going to start seeing them asking for money for for things I think that is a that's a prediction. But we'll see, we'll see how that goes as we talked about, you know, trends to watch out for. So, as I said, the internet has changed and so should your analytics. And this is kind of what we just talked about a little bit but with universal analytics and what you might be used to metrics are heavily based on the page itself how many page views of this get. How many sessions view this page how much time did people spend on this page. It relies heavily on customizations because it just did that out of the box and so if you wanted to look at how far down to someone scroll, how many things that someone download, what links did they click. Did they buy something these are all customizations that are mostly unavailable in universal analytics e commerce was was added. So that's helpful but everything else kind of had to be done by hand and put in there. One thing is that you could put whatever data you wanted to in there as long as it wasn't personally identifiable information, ie someone's name or email address. Because that would get you banned from Google but everything else you could put in whatever you wanted and pull out whatever you wanted. But as we move into GA for metrics are heavily based on engagement a user has on your site when you look at the default report, it doesn't tell you the bounce rate and the page use it tells you how many engaged users out of your total users that you have and how long were they engaged or and what that looks like here with our kind of rough, rough graphic there at the bottom. As you can see someone's someone's just got their phone open, maybe they had a play a video on your site, maybe they hit the download button, maybe they just like scroll through one article real fast. That's, that's what GA for is building this picture around, and it's starting to track conversion events and starting to be really concerned like anything can be a conversion event. And from there also has a lot of AI tools built in where it's starting to try to figure out its own recommendations that it would have for your site, whether or not you want those is, you know, up for debate. But that is, it's really designed to be a tool to kind of watch over all of your different properties, all of your different iterations, you know it meant for apps, as well as mobile sites as well as desktop sites, etc. And it's trying to kind of do everything for you and figure out everything for you and kind of really pull you into Google's ecosystem there. And because of that, you can so customize a lot of the data you're capturing but it's a lot harder to get back out. Or I should say it's harder to get back out without going through Google and using BigQuery and opening yourself up to potentially expensive, expensive options in terms of querying and data storage. So, as I mentioned a minute ago bounce rate and time on page and I also said when we started here that we have, or you may already be using these these are, these are kind of primary pieces that people like to report on. And they're going away they're vanishing. We talk about average session duration ie how long somebody's visit lasted to our website. We talk about this is in universal analytics on the left side of my screen, we talk about average time on page how long did someone spend on this page. We talk about bounce rate. And that's one of the most these these are actually some of the most misunderstood metrics, particularly time on page and bounce rate, because in universal analytics is expecting like early 2000s level of usage right you come to a site, you look up a thing, you look at multiple pages. That's what we care about the people who come and look at one page and or get within 30 seconds and leave. We don't care about those we're going to call those bounce bounce bounce people. But as you can see, as we look in GA for over here, the average engagement time. These are reports pulled from the same time period from both the universal analytics and GA for property. And you can see that average time on page was four minutes and 19 seconds GA for recorded the average engagement time of 33 seconds. So again, if you're reporting on time on page now and then suddenly July 1 you start reporting on average engagement time. People who read your reports, particularly board C suite. Anyone like that is going to go, what happened. What, what is going on. And the reality is that it's just a different way of measuring these things. So average time on page only captures data. When someone looks at a second page on your site, if they only look at one page, nothing is captured. The bounce rate is looking at people who only looked at one page and then left, even if they spend 20 minutes on that one page reading it by default. That's a bounce. But we know now in 2022 that and GA forwards build around this right getting someone to spend 33 seconds if they're on their phone, imagine this, they get an email, they click a link to your site. They hit a button they click a download. They scroll real quickly through a news update right if you get 33 seconds of their engage time and so Google is actually, you know doing the slightly creepy thing is like watching now was your webpage in view. Was it obscured by other windows. Was it actively on screen on the phone or on the on the computer. That's what that engagement time is measuring. It's just, we start a counter when they come to your site. And then we turn that counter off and they leave. And that's that's the numbers you're getting so ostensibly GA for is measuring a more accurate engagement number. And that may be really useful for for looking at at your metrics. And in fact, there's a scroll depth option, which again used to be a customization. And it's now available out of the box with with GA for so you can tell how far down the down the page someone scrolled right. If you're content producer if you're writing long form content. That's incredibly valuable, because you might care less about people who spent 20 minutes and just sat at the top of the page. And you might care a lot more about people who spent 10 minutes and made it to 50% of the page. And then you know that they're probably more engaged and the people just didn't really do anything you just had it up on the screen, right. So, you may be thinking to yourself is GA for right from my organization. And then you may also be thinking, well, do I even have a choice. And realistically, yes, you have a choice in whether you stay with Google Analytics, or you go to another platform. So let's talk about some of these these big differences these big shifts that you may see organizationally here. Universal analytics is organized around properties and views. So this allowed teams so allows because it's still running for a year allows teams departments stakeholders, even just a single individual to kind of focus the data down to only what they want to see. The variation here that I'll jump from universal to do for right. So now GA for property and view are one in the same filtering. As you used to do with the views in universal analytics, that's going to permanently alter your data for everybody. It's gone. It's no longer collected because you filtered it out. Before you could filter these things and you just, you didn't see them because they weren't important to you. That's not that that's not available as simple views in GA for so it's going to take a lot more know how a lot more training to build this out. If you have people who are trained to use the customer reporting options in GA for they can absolutely get get those view level pieces where they look at just what's relevant to them in the form that they that they want to see it. This other big difference here. Google Analytics right now universal analytics you log in. There's almost infinite default reports. There's there's too much for a lifetime really of so many different things that you can click on and learn about your data. They have built this up obviously over 10 years and so there's there's a lot there. The options are kind of limited though. And for that you might want to export to another tool especially Google Data Studio very popular one because it's free and it integrates really well with the universal analytics and that export is free and the data. What you capture in Google Analytics you get out of Google Analytics when it's more talking about universal analytics in GA for we have a lot of changes here. There's very minimal default reports everything is customized and there's it's a it's a robust tool to use within GA for to build out those customer reports you can get a lot of stuff. But you have to know how to use them. And it's, I don't need to tell you obviously it's brand new people are still figuring this out that there is not a lot of built up knowledge. So just dropping this into your organization is going to be massive because people will click in and look for some default reports look for things they used to just get by clicking a button or two. And they're gone they're going to have to build them, or they're going to need someone in your organization who's building them, building the reports for them. And, you know, a key point here, data is more locked in and shorter lift. Right. So, as part of this, the privacy concerns GDPR, etc. There's an expiration of a lot of data that gets collected. You could. That was technically still a thing in universal analytics, but a lot of people with disabled, because Google said, Sure, yeah, we'll just keep your data forever. We deal. Now there's lawsuits about that. So, not only can the data expire and you can do nothing about it. Other than export at the big way. The data is, is more locked in. And so I talked about Google Data Studio, a free kind of dashboarding report. It gives you access only to, I believe, less than half of the dimensions that are captured natively in GA4. So, where with universal analytics you capture all kinds of data, go to GDS is all there for you. Right now, you set up GA4 the way you want to capture all kinds of data, you go to GDS Data Studio, and it's just not there. In fact, things are disappearing by the day because we built something for a client to about three weeks ago. And then one day it just stopped working and we looked at it, it was because the dimension we were pulling in, no longer available from GA4 so very much still in flux. Very much still a learning curve. It's going to be a big learning curve for everybody. I've been BigQuery a number of times now. This is another Google product. There are some free tiers, we'll talk about that in a minute, but it's almost required, required additional product. If you're not only going to live in GA4 and kind of build out reports that way, if you want dashboards, you're going to need BigQuery. And even some of the services, the third party services that used to pull data from Google Analytics Supermetrics, for example, seem to be pulling like aggregated data and not kind of the full data set the way you might expect if you're used to using data studio now. So that was a lot. That was what we might call a fire hose of information. So I'm going to take a quick break here and we're going to, I think, put out a survey because I'm really curious how people are using, what people are using right now. You might still be relying on GA3 universal analytics entirely. You might be using them both and getting GA4 set up. This has been the recommendation from Google for about a year now. Start pulling in the data even if you're not using it actively because it's there when you want to do some gear up for your reporting. Some of you might be using GA4 as your main source of analytics now, which is great. I hope it's certainly great that you're kind of ahead of the curve there. Some of you may have migrated to another platform entirely and said, okay, we're done. We're done with the Google ecosystem thing. Let's move on. And then, of course, obviously some of you are here because you're just curious about analytics and you want to learn what kind of possibilities are out there. And I've got information for all of you. Don't worry. Yeah, let's see. I would see the poll numbers coming in. It looks like the vast majority of folks are still relying on universal analytics and didn't click the but GA4 is set up. Huge call out for you all, please. And you'll see this in our next steps slides coming up here in a little bit, but get GA4 set up as soon as possible, even if it's not the platform you wind up going with, even if you wind up migrating off of it. It is free to just turn on and start collecting data. And that way you have it. And you can look back and when you can, but that whole deadline thing we don't want is to get to June of next year. You're just starting on GA4. And people say, well, let's look at the past three months of data. Let's see the differences in universal analytics versus GA4 and how those metrics shifted and you just starting from scratch. Do not want that at all. It's can't get a full year of data at this point because we're already in September. If you turn on now, you can at least get most of a year's worth of data and start pulling that in. Let's see, I guess we could. Oh, goodness. Thank you for sharing the poll. So, yeah, you all can see that 64% still relying on universal analytics, mainly using GA3 but GA4 is set up is actually 25% of folks. So that is good to hear. And we actually have, it looks like just one person was using GA4 as the main source of analytics, which again, great. Good job being ahead of the curve there. And you're getting what you need out of it. We'll talk a little bit more about that in a minute. And then just a couple folks who are not using any analytics. Let's see. So, this is good. And I think this is a good place to move into what's in store and how can you prepare. So here are some some big shifts that we want to watch for. Because we already see them kind of coming down, coming down the line algorithms versus DIY analysis GA4 is really universal analytics actually had a number of kind of algorithmic analyses that were that were put in place. And they were neat. I think some people kind of use them and, you know, they just provided some quick insights. But the algorithmic approach has been greatly expanded in GA4. And it's really trying to be a tool that saying don't don't bother looking at your data. We're going to tell you what you should pay attention to in your data. And certainly if you don't have a lot of staff capabilities staff resources there. That can be helpful to have you know some some data is better than none but also the wrong data can be very dangerous. And we'll talk about that in a little bit just in terms of data strategy. And yeah, and then the DIY analysis part, as I mentioned before, you're going to somewhat the GA4 is actually a more robust tool for for building those reports and and looking at those those things inside of there. But it's from a very analyst perspective it's not from let's put together a nice pretty some charts at a dashboard report. It's more of let me dive into the data and get the answers I'm looking for. And so if that's a good direction for your organization go you've got the staffing for that or you're planning to hire for that GA4 is is probably a really good option. So first towards big query. If you want your data you may have to pay for it. As I mentioned earlier, you know we started with here's Google Analytics free way to measure your ads please pay us for ads, we're making money on ads. Google Analytics is such a big product now. And BigQuery is also a big product that this is I think Google's time to kind of say, All right. And now it's time that you will actually buy into this and certain certain things are paying for this data a little bit. So, fortunately, right now, we've already seen changes in this because you'll see that's my next bullet. But for right now there are some free BigQuery limits that seem to work well for most people, and it seems like most smaller orgs are not hitting those limits and are able to get what they need to add a big query, able to configure Data Studio to use BigQuery to pull all of the data out of GA4 instead of just a limited amount the normal connector gives you. So this is hopeful. And, you know, I think Google may see the light as this continues down I've noticed a number of blog posts from Google lately saying this organization or this company used to spend thousands of dollars a month on big query queries on data storage, and we help them get it down to $200 a month. So I think they're already kind of ramping up this marketing messaging around, it doesn't have to be expensive. As maybe some bigger organizations are expecting it to be. And so I think they have a obviously vested interest in keeping as many people as possible on GA4. So hopefully those big query limits will continue but changes are still happening weekly and what you can do capture and report on today may not be available tomorrow. A good example is custom dimensions which last year Google was like you've got 100 of them. You had 20 universal analytics now you've got 100. Go ahead and capture all kinds of custom stuff. And that's already gone. There's now a limit of 50 or 25 depending on what type of dimension you're setting up. And so like these things are already being kind of pulled back and scaled back. And, you know, obviously since changes are still happening weekly the entire industry is learning is on a learning curve right now. There's not. You can't expect to have infinite access to just hire a consultant or hire anybody and have them had 10 years of experience with Google Analytics. Try and test solutions is how I wrote it there but we're all still learning and adapting. And it's all still kind of being tested and developed as we go. And another thing, you know, to call out there. And we'll talk about this with the impacts on the sector thing. This slide here. There's four big areas where we see significant impacts across the sector. But the one I keep kind of touching on is if you hire an intern if you hire someone who to manage your email you had someone who managed your website anything like that. They've probably had Google Analytics experience, they can probably go in there, start answering some questions, run some quick reports. It's, it's been ubiquitous for about a decade now right. That's gone. Unfortunately, as of, you know, July of next year. You can't just say, well, let's let's hire, you know, a younger person who's maybe managed social media stuff before, and they're going to just have this built in baked in knowledge around analytics and everything. Your current staff and maybe well very familiar with universal analytics, a new staff you hire for the next couple years are just not going to have that baseline experience with GA for where you could just expect that oh well it's a standard. Everyone kind of uses it. I don't have to spend too much on training. I think the budget for training, rebuilding reports, especially in the first year, and, and exporting the data is going to grow. I think you're going to see, need to really start investing in analytics here, if you were using, you know, a totally free setup before I don't think that's, that's going to fly at this point. And also go back to the top metrics. There's new metrics that may or may not be in line with your strategy. And, you know, because of that ubiquitous nature of Google Analytics, and the way this has gone the past decade, I think there's a, there was the sense that, well, this is the way it's done. So this is the way we should capture our metrics. And realistically that's never been true, but it's especially not true right now with GA for if it's not in line with your strategy with the way that your organization talks about your content talks about your goals. If it's not collecting data that answers your organizations, you need questions. Then it's, it's not a right fit, maybe it needs to be customized, maybe in a different platform. But that strategy question, and how data strategy works in your organization is going to be huge. There's going to be need to be conversations around that. There's also going to be many new conversations just around. Oh, I suddenly have access. I think GA for is democratizing access to kind of everything at your organization. Now we're not restricting things by view. It's not easy to say only look at this, only look at this part of the site only look at this part of our portfolio. If you have GA for access, you see it all, it's all in there, which is good and new expertise will be built, but it's going to take time. And, as we said, it's going to take some budget for training and really getting people brought up to speed. And all of that collectively kind of coalesces into this performance bullet here. It's going to be difficult to compare the past impact. And that's, you know, again, a big thing right now, please get GA for turned on as soon as possible so that you can start looking at how are our numbers going to change how are our reports. To grantors to funders to the board to our constituents how to our teams, how is all that going to change and how are we going to talk about that internally. And if you don't have enough kind of overlapping data it's going to be really hard to compare to past impact, you're going to be looking at totally different numbers in 2023 than you are in 2022 and 2021. And it's going to, it's going to be really hard to say, here's how we've been doing on a five or 10 year scale, right. Hopefully, the shift gets organizations to start asking what analytics means to them and how data can be better used to drive decisions. So, key things to do, and I think there's already a number of questions in chat, as I'm seeing here. Yeah, number one created new GA for property if you don't already have that if you do, if you are using universal analytics, you can go in and under the admin section under property. There's a GA for setup assistant that'll walk you through the whole thing. And it'll ask you if you want to create a new GA for property and you do just remember that your data is starting from scratch from when you click that getting started button or actually, once you click getting started. If you're using I think g tag the JavaScript version. It should just be able to click that automatically start collecting. If you're using tag manager, you'll have to go in and create a new tag. That will be a little bit more extra work there, enhance measurement initially for whatever reason was not on by default, because GA for was like hey that's totally extra data to want to, you know, see your paid views, which is obviously coming from universal analytics, pretty bizarre, GA for has taken a lot of the customizations that used to happen that people were doing on their own, and now just made it as simple as looking at switch of we'll start looking at how many people view videos. We'll start looking at downloads start looking at scroll depth and put them all under this category of enhanced measurement. I believe it is now on by default, but great to take a quick look and just make sure that it's, it is turned on and it's configured the way you like. That goes the same for e commerce and ads. If you're already using those you want to spend a little few extra minutes to get everything there set up and linked in. This is as well as soon as possible document your current analytics usage and your current customizations really take a look at what is your organization doing right now how are people using it on a daily weekly monthly yearly basis. What's happening and what might you possibly lose by moving to a new platform. When I say lose I mean what might you have to recreate when you move to a new platform. Also, get a get a rough sense of how well your current setup aligns with your organizational strategy. Is it collecting data in a way that makes sense to your organization. Is it collecting data in a way that it's just Google's way of by default and and you have to kind of bend and flex the organizational strategy to look at metrics that aren't quite what you wanted. Just get a sense of what's the temperature there is it is it totally off the rails is it like no this is this pretty much aligns. You know what you can save save yourself a lot of time and effort by using our self service toolkit. I don't know if if that link has been shared but now is the great time to share that link. Excuse me and I'm going to drink some water here. Get my voice back. Right, so we at parts and to go I've set up a self service toolkit. You can jump in. You can get all kinds of information. It'll walk you through a number of these questions that I'm talking about. Things that I'm saying to document things that I'm saying to get a rough sense on it will ask you direct questions. Help you get answers to the to help you find the answers to those within your organization. And then make recommendations of saying, you know what j4 is a really good fit for you, or actually you may want to consider these other platforms. Let's get this into the coming months. Key things to do moving forward. Number one, start using both universal analytics and GA for when you're exploring the your regular site performance, doing your, your regular routine content reports and things like that. This way you can spot discrepancies early on and start addressing them to the, the audience for those reports. You can start kind of building a story of how we're moving from universal analytics to GA for how we're getting more accurate and more, more custom or custom fit data to organization. So dive in a bit more deeply to data strategy within your organization. Look for problems and opportunities and explored questions. And a question that I always love to ask folks and we're starting these conversations out or what kind of questions that you and your teams wish you could answer and it's amazing if you sit someone down. And just say, what kind of data do you look at, you know, in your, in your normal week, normal month for you. And then you ask, what kind of questions you wish you could answer. And they'll probably have two or three things right off the top of their head that they'll say like, I wish we could know at a high level, you know, what types of pages people are viewing. Can we set, can we find audience segments by content types right and this is things you can set up. But when you ask them the kinds of questions they wish they could find answers to that's going to explain a lot about data strategy for you. So I'm just tracing out current external reports and dashboard with g4 data we get a little screenshot here. This is from data studio. I wouldn't recommend taking a report and just switching it right away to GA for I would make a copy because it's probably going to break, and you probably want to play around with that. And you may. Again, I said less than half of the dimensions are available. So depending on what you're doing in data studio, or another tools like that you may wind up need to go with BigQuery and start playing with that as well. Again, do this early so that you're not right up against the deadline, start getting insights into into the tools themselves the platforms themselves, how our reports going to change, what what do we need to do differently. And yeah, last but not least, definitely consider other analytics platforms that might better fit your needs. And again, our self service tool is a great way to do that. We can make all kinds of recommendations there you can start kind of getting the data. About your organization, looking at that. And starting to get a better sense of where you should be heading. And that's yeah, we can help. There you go. So, when we talk about data strategy, and actually let me let me pause here and just see if there's any big stand out stand out questions about about anything that we didn't get to see. Okay, link to the toolkit has been shared so yeah please click that. And another thing I wanted to mention on that toolkit is that there is, if you go to that site and read through there's a link where you can book a one on one call. I think, eventually that will be a paid opportunity for people to. We'll have a number of products that that can help one being we can come in and kind of do all this documentation for you and come up with a plan of how to migrate. One is that we can also do technical services we can do a lot of the setup and streamlining that can get you moving quickly do some of the customizations as well. And then last but not least are those one on one calls of just less chat for 30 minutes. Let's let's hear what your concerns are where you're stuck what you're thinking about. And it looks like yeah that that link is just going out there. If you look at those migration services right now those one on one calls are are free. So, feel free to book one. If you want to chat with, I believe, believe it's Stefan who's our head of data here at barson TKO. You can get 30 minutes with him and chat about your questions and your concerns and you know anything you had your plan to do with these things so take advantage of that. So at the end of the, at the end of this, I'll share a couple other places to go resources to look for we have a lot of free help to be we provide the our website. Let's see, and I'm just, I'm just looking here. Okay, yeah, I think we've got. I think our questions questions have been answered so let me just kind of dive through here a little bit and talk a little bit higher level about data strategy and what we mean when we when we say that. As you look across your organization, you were platforms, your portfolio, your own digital properties, all of your architecture even your internal systems and everything. So I'd be paying attention to the mission and goals and strategies of your organization. We should be documenting how data is used, how fresh and accurate data is, and who owns the data. We want to be looking for strategic opportunities. Who's in a position to change course, based on data insights, who needs to see this data. When do they need to see it. Data dictionaries, you know, if I'm new to the org, or I'm changing departments, or I'm just doing something I've never done before, where do I go to learn about the data. Obviously that fits in with documentation but it also, you know, speaks to that the data is is actively maintained and and watched over here. We have about 10 more minutes so just quickly. To talk a little bit about parts of TKO and how we how we look at this data strategy. When we do data strategy work, we find that most folks get stuck in numbers two and three, right, they're looking at tracking and technology they're looking at just the technical pieces setting it up make sure it's running. Reporting an analysis, I want to see a nice chart, I want to see it every 30 days. Email me that put it in your, your monthly report slide deck, etc. But what gets missed are numbers one and four, the front and back of this right. That strategy definition, as I was just talking about. If we don't take time to plan what gets tracked and what gets reported. Then that that really gets hindered. We might not be collecting the right data might not be collecting complete data. We might be reporting on the wrong data or misrepresenting the data. I remember my point about bounce rate earlier. How many people were reporting on bounce rate and thinking great this tells me how many people aren't really actively engaged with the site and didn't know that actually it's mostly just reporting on people who came to view one page and then left. Like many sites, if that was your primary way of measuring engagement. And the primary way people interact with your content is just coming in looking at one page. Then, wow, you have a definition problem. You need to capture events on the page and start doing some of the things that g4 is doing to know how people are actually interacting on that single page visit because universal analytics isn't set up with that by default. And then on the flip side adoption and optimization. Another thing we really need to be paying attention to here. And what I've kind of been cautioning you against. It's easy. There's a button to click, you know, there's the setup was it in g4 or universal analytics. Yeah, let me just set up this new g4 property great it's there. It's collecting data. No problem. If you don't spend time and invest the time and the resources into adoption and optimization. You're just collecting data. And you don't know what it does. And, and maybe even worse, you might be collecting the wrong data and people might come through a year from now and look at it and say oh I guess this is accurate because we've been collecting it. And it was never defined was never, you know, understood or tracked fully. Now you've just got these these holes in your in your reporting scheme, because it was never fully adopted was never fully documented it was never fully optimized i.e. Let's look at the report collect better data because that didn't quite answer our questions. Let's keep going let's keep a full. Let's keep the data fresh and accurate. And with all that in mind, then we kind of want to say here is that some thoughts on resource allocation for g4 if you decide to go that route. Really thinking that at a minimum, you're going to need one person on your staff with 10 hours a week to spare those bare minimum. Not just to get the setup to keep it maintained to keep it keep the data fresh to make sure it's getting used properly throughout the organization. And the tech tech stack maintenance perspective. If you want more than just basic g4 which as I've been noting here for nearly an hour now, you probably will. You were going to want someone reviewing the data quality making updates road mapping new customizations and you know again bare minimum 10 hours a month can be the same person but it's probably going to be an extra 10 hours. If you're reporting, you know, just remember that GDS dashboards, if you're using those Google data studio will need to be completely rebuilt and probably using big query, which means you'll also need to be setting up big query and additional product, which has its own workflow, and can wind up costing money if you don't configure it properly. If you're reporting moves to GA for you to spend a lot of your budget and training time, making sure your staff knows how to go in and get the answer so looking for because it's not readily available the way it was with universal analytics. And again, you know, they won't have had past experiences to rely on, because it's, it's not industry standard. It's, it's too new. And just some notes that other, you know, other tools that you may be hoping will work are also still in flux I think I was just looking at Tableau, where they still have not fully turned on the GA for connector. And so, you know, if Tableau is what you're using. I don't think you can just pull the data and without going into big query. So, as I said, it's a near requirement. If you're doing anything besides GA for that you also have to be using big query and so that's obviously going to add more time more budget, maybe more staff to to manage that workflow. And this is slide I'll get to in a minute of just, you know, some of the things that we can offer but let me let me flip back to the questions here. Let's see, when the ability to create different views for different teams to appear with universal analytics. Let's see, do you recommend setting up different properties or reports as a substitute in GA for that is, that is hard to say. I don't know what the limit on properties is going to be. Let's see then, if you get into multiple properties, you get, it gets a little bit dangerous because you're not sure if both properties are one to one, did they start collecting data at the exact same instant. Did they, do they have all the same customizations on them all the same things like that it's a, it can be a management and documentation nightmare. You know, if you're talking about two or three things, and we just want to restrict it to certain sites and people know very clearly how good the data is, it might not be, it might not be a bad idea. But, but, you know, certainly what might be better is just taking the time to learn the tools within GA for to get to get those answers. Are any, are there any WordPress analytics plugins you recommend. There's a main one I will see if our engineer is on the call here. I think he knows the, what that recommendation is what we have used in the past and whether it's good for GA for as well. I think, I think what we've used is actually just a, we tend to prefer GTM which is Google Tag Manager. If you're already using that, you know, it's it's pretty easy to just add a tag for GA for. And I believe the some of the plugins there will work. I think it may need to have that in here. Second, I'm thinking here any other questions I can circle back around to that one. But, yeah, the, the, I think we generally prefer GTM it's a little bit of a nicer managed experience but I WordPress especially should have a basic GA for plugin to think about. Let's see the other one. Does it make sense to set up at set up a consultation if my organization is just beginning to think about our data strategy. Absolutely. That is a great time to set up a consultation. We would love to talk with you at this time, because you know, there's a little bit of that, you know, don't move my cheese aspect, we come in and start talking about data strategy to organizations who put a lot of thought into it. And are, you know, somewhat somewhat hesitant sometimes one department owns it or, you know, one individual owns it. And there's some hesitation to kind of open up and have an org wide conversation about it but certainly if you're just getting started, we absolutely want to be involved there. And as you can see here some of the those major changes we, we can help you navigate our data capture data retention data reporting, not just what questions do you need to be asking of your data but also what's the best tools to use. What's the, you know, how can you focus on adoption how can you tie it into meetings you're already having, etc, etc. So yeah, is there are there any other questions there. I guess with that I'll just flip to this slide real quick here. Please take our free content at barson.co.com. We have more events like these. We have podcasts talking with some luminaries in the in the industry in the sector. We have many training videos and panel discussions, past webinars, things like that. We also have a lot of articles and obviously the, maybe we should share in the chat again. Just in case anybody missed it that that decision making tool that links to a blog post on you know deciding if g4 is right for you. I feel like setting up a call if you don't feel like going through the whole toolkit and answering those questions there's a little blog post that you can just read through. I say little, it's actually quite an in depth blog post that you can read through but yeah so a number of options specifically around g4, where you can learn about services we offer, you can use that self service toolkit it's totally free. You can set up a call with us and we'll help talk you through it, push you through it, whatever you like. We're here to help.