Unhappy with GA4 and want to look at other options? Let's talk about it.

Google's impending forced migration to GA4 is right around the corner (July 1!!!), and a lot of marketers and analysts aren't happy about it. In fact, many are considering moving away from Google Analytics all together.  We chat with Jason Packer, who recently published "Google Analytics Alternatives, a Comprehensive Guide", and discuss some of the pros and cons of other analytics tools.

Jason's Book:

https://www.quantable.com/analytics/google-analytics-alternatives/

TRANSCRIPTION:

Roy: Hey everybody. Welcome to Real Marketing. This morning we're going to be talking to Jason Packer. Jason runs Quantable Analytics. It's a small consultancy focused on growth-stage companies looking to mature their data practices. Prior to Quantable, Jason held a wide range of jobs in IT, unix, CIS admin, ISP, network tech, SEO specialist, and front-end engineer, and currently, Jason has recently published a book on Google Analytics alternatives that takes a look at 15 of the top choices in the space and how to choose between them. Which if anybody has been using Google Analytics 4, I'm sure they're ripe for looking for other products. So Jason, how are you doing? And thanks for joining us. 

Jason: Yeah, I'm doing well. Thanks for having me on the show.

Roy: Happy to have you. Like I said I think a lot of people right now, or especially analysts, who've been used to Google's products in the past because they're free. At least the free version that Google 360 obviously isn't free. But they got very used to a certain type of platform, and GA 4 is a significant change from what they're used to. There's a lot of bugs still. There's a lot of inconsistencies in how the data's presented and the reporting and it looks like Google is actually trying to push people towards paid services by only giving them, 14 months back data throttling Looker Studio, formerly Data Studio, so that you have to use BigQuery to store your data, which is obviously a paid tool. So I think there's a lot of industry frustration with Google right now. And this move to GA4. Are you seeing the same thing with your clients and using it yourself? 

Jason: Yeah, I think a lot of the confusion and a lot of the upset comes from just the idea that it's GA 4, you think, oh, it's going to be like GA 3, but just a little different and maybe I can click a button to upgrade and instead it's really a completely different type of product.

Jason: It's, I consider it more of a product analytics product more than just a traditional web analytics product. People that are coming from using universal analytics in a history of implementing and working with that data are confused and a little frustrated. A lot of people are out there saying oh, GA 4 is a terrible product. I can't believe Google will put out something so awful and I'm not one of those people. I don't really think that GA 4 is a bad product. I think it's pretty good, or at least that it has a lot of potential to be good. But most of my frustration and a lot of my client's frustration comes from just how different it is.

Jason: If Google put out, I say a lot of times in the book, if Google put it out GA 4, they didn't call it GA 4, they called it Google product analytics and UA continued to exist, there'd be a lot of people going oh wow, this Google product analytics platform is great. I can put data straight into to BigQuery without having to pay for 360. I can better unify my mobile and my web stats. It's got a really powerful data collection method. But that's of course not what they did. I feel like most of my complaints are really about how they have been rolling it out and the fact they are discontinuing universal analytics before a lot of people are ready for them to do that.

Jason: And of course, they have given a lot of advanced notice, but still, people just aren't believing that it's actually going away. 

Roy: Yeah, we've seen that where people have just ignored it and they're still, scratching and clawing and using the universal analytics and not moving over. And I agree with you. I think one of the big things that we are seeing is that it's just not as easy to get to some of the data, or it's not as intuitive, I should say, about how to get to some of the reporting and data. Or the necessity to actually build, explore reports to really get and drill down to the data that you want. That is so different from what they're used to with the universal analytics. There has definitely been some bugs that we've run into, obviously with trying to do reporting that certain metrics are not available in Looker Studio, for instance, that are available in the regular reports within GA 4.

Jason: Yeah. I agree. It isn't really just that is just different. It's also with the rollout that, it's not exactly ready. I would still consider it borderline beta because things are changing really quickly. They're adding a lot of features, a lot of changing metrics, and things like that. You'd like to see that happen before they announced the switch, right? Instead, if you're not already using GA 4 for your primary reporting at this point you're pretty far behind the curve here because, July 1st, you're not going to be able to A/B your results and be like, oh, something is wrong. Let me check on UA and see if it's a problem where the problem is. So it all just happened on a very compressed timeline. And like I said, part of that is, is Google's communicating with that but part of that is people's unwillingness to believe that things are really going to change.

Roy: Yeah, well Google does have a history of kind of changing course and doing things by surprise. I think the other issues are that there's a lot of the definitions in the data are different so you can't really compare year over year unless you already had GA 4 implemented back in July of last year or before that so that the definitions about what a session is or a user and all of those things are different. So I think that that's a little off-putting for some people.

Jason: The product is not, especially if you're dealing with like small, medium businesses which a lot of my clients are startups or people that are in the growth stage and they don't have dedicated analytics teams, and if you don't have somebody like, oh, I've got somebody on my team that knows BigQuery and is building out, these Looker dashboards that's one thing but if you're a small business and you like mostly deal with analytics in a reactive way, like you're going into to UA , oh, something, my sales are down. I wonder what's up. I'm going into UA and like doing more ad hoc analysis, and I'm not in any sort of stretch a specialist in analytics for GA 4. Just that's not necessarily the product for you and that's what I was trying to do with my book is to say move away from considering GA to be the default for everyone.

Jason: GA4 is still going to be obviously very widely used, and it's going to be a good solution for a lot of people. But I don't like the idea that that's what you install, right? You set up a website and you install GA. I would try and to encourage with my book people to say, I haven't got a website. What's the right fit for me? Just like any other tool, what's the right tech stack for me? What's the right CMS, what's the right web host, or whatever, rather than just not really thinking about the decision and going straight to GA.

Roy: No, I think that's a great point and most of our larger clients, are enterprise-size clients are using Adobe Analytics and have for years and, formerly Omniture back in the day. I think I'm dating myself by pulling that name out. 

Jason: Oh, yeah, that's not too bad. I was just having a discussion, made a LinkedIn comment, talking about the Mosaic browser. So I've been around too.

Roy: A lot of our enterprise clients are in the Adobe sphere using lower of the Adobe products. Obviously, for most small to medium-sized businesses, the pricing for that is way outside what they're going to spend or would be willing to spend. What did prompt you to start looking at alternatives? Was it a need from your clients or just tired of that default for Google Analytics? 

Jason: Yeah, I'd say it was a mix of things. I've definitely used a lot of these alternatives before in the past. I've used Matomo and Clicky and some of the others that I talk about for, you know, in production in the past.

 Jason: So it wasn't like, there's the UA turn down and then oh, let's consider alternatives. I had been considering some of these alternatives for years. The sort of, the impetus for the book was this desire to get a sort of unbiased, deep view into what the field of options was.

Jason: Because on the one hand, there's so many options. There's hundreds and hundreds of different options, and it feels like every week there's a new one. It's not hard to build a simple, light gene alternative type product. So every week there's a new one coming out, but when I started the book, if you tried to do that research, you would really only come up with a few different types of reporting on this. You'd come up with people that are vendors talking about their, lists of here's 10 great Google Analytics alternatives. Oh, ours is number one.

Jason: But we're totally unbiased. Or people just doing it for SEO purposes where they would list, here's the top 30 GA alternatives, and they've just, they've never used any of them and they're quoting from marketing company from those sites.

Jason: I wanted the research from actually someone that actually had used the products and was independent. And I was like, okay, why not me? I can do that. So that's how the book started and it just seemed like a timely, timely subject.

Roy: Absolutely. Yeah. So talk to me about that many of those products are paid products, right? That's the appeal of Google Analytics historically is that it's a pretty highly functioning analytics tool that is free, essentially. Did you have to go pay for a lot of those tools to test them? And what was that process?

 Jason: Yeah, I did. First of all, I paid for a couple of websites. I wanted to actually run, this on real websites with real user data rather than sign up. Even some of these that have trial versions that you can use with some sort of example data, that example data is not really as real or it's the best case scenario for our tool. So I wanted to run this on real websites, but I didn't want to be like, Hey, client, I'm going to install 15 different analytics tools on your site. Hope you're cool with that. I started this whole process by buying a couple of websites through Flippa, which is an online business brokerage.

Jason: I bought a couple of sites that had a decent amount of traffic. Then I bought some of these products. Some of them I used the free trial for something like Snowplow, there wasn't really, an option and it's quite expensive and it's, more of an enterprise tool. So I use the trial for that versus some of the others like Matomo and Plausible that don't have trials at all. I just paid for the product. Yeah. 

Roy: What, how did, what was the selection criteria? When you were looking at say the top 15 tools? Is it just the ones that have the most kind of visibility or how did you make that selection?

Jason: Yeah and this is a good question cause this is a really important part of my process. I wanted to have a method, a rigorous methodology in order to pick these tools rather than being like, here's three that I'm familiar with. Here's three that are popular in the industry and people are talking about.

Jason: And so that's why I worked from what was most used currently. I used stats from BuiltWith and that spider the internet and say okay, here's all the sites that are using Matomo because I've detected their sensor on the page, their tracker on the page. So I started from  a list of all the top ones by usage, and then I filtered it down a little bit. I excluded ones that didn't have any way for me to get into the product without going through enterprise onboarding, which didn't really make sense for me. That's why I don't include Adobe, which is the one that most people have requested that I don't have. Like, why didn't you include Tool X? Is definitely the most common feedback that I've gotten.

Jason: Even though I do include quite a few tools. There are a few like Adobe and Piano analytics that didn't have any way to get into the product other than, buying the full enterprise version and going through enterprise onboarding and things like that, which is not something I wanted to do. Then I did also exclude Yandex and Baidu cause I didn’t think it was appropriate to include those. The methodology I used is just like anything that has more than 0.1% installation base within the top 1 million websites. 0.1 doesn't sound like a lot, but you’d be surprised to some of the ones you hear people talk about frequently that don't even have that level of installation base.

Jason: I wanted to be pretty rigorous in terms of picking which ones I used. So like I didn't miss things. For example, I reviewed Chartbeat even though it's not one that you really hear people talk about because it’s kind of a niche product for the publishing industry but if you're in the publishing industry, it's like I gotta have one. I didn't see a reason to exclude it, so I included it. I talk in my review about how like this only really, this is a particular tool that's geared for the publishing industry geared for real-time analytics. If that's you, then great. Check out this product. If you're an e-commerce site, then it's totally irrelevant to you. I still consider that to be somewhat of a general tool enough to include it. But it isn't one that I would've included if I was just like, Hey, name the top 10 or 15 tools out there. Yeah. So that's basically how I picked. 

Roy: What are you seeing as some of the major differences? If you use Google Analytics as the baseline that most people would be familiar with? What are some of the major differences, some of these other tools bring to the game that might be better or might even be worse than what people would be used to with Google?

Jason: Yeah. I broke things down into three different categories of products. So I broke them down into like traditional web analytics tools, things like, universal analytics and I also put Matomo and Piwik Pro in there; and these are things that like really match the page view based likethe  paradigm that we're used to.

 Jason: That can be like, really still good for a lot of people. There's a lot more development in product analytics and that's my second category, product analytics. That's things like Amplitude and PostHog, things that are event-based. Then the third category that I have is simplified analytics, which are things like Plausible or Fathom or CloudFlare that are like really very basic. And the thing that, I see when people talk about Google Analytics alternatives is that people say, oh, what's the best Google Analytics alternative? And there isn't really one answer for that.

Jason: There's the what's the best for your particular site and use case. And that could be like Piwik Pro if you're doing something where Universal Analytics was a good fit and you're a bigger website, that could be your best alternative and that's still very much in that, that universal analytics mold versus, if you're a small content website, if you need a like my own website for my company, it's just a few pages of content and some blog articles.

 Jason: I use Plausible for that and that's a great fit because I don't need more data. So there are others, real sort of trends where what was once like, oh everybody used Webtrends. Everybody used Omniture or Urchin or GA that were all, they're all similar and now, there's, the web does so many different things and there's so many different types of tools that specialization has occurred and we've got a lot of different possible paths to go down and GA is just one of those.

Roy: I know Google has done a lot of work, especially with some of the data restrictions and laws in Europe and California and places like that. They're doing a lot of work with data modeling to try to ensure a more accurate reporting. Are you seeing that kind of investment or functionality with some of these other tools?

Jason: Yeah, I feel like that's a two-part question. The first is when you talked about regulation and the EU, like that's been interesting with the book is that it's really been much more popular in the EU even though I'm obviously based in the US and American and that's where most of my contacts are, but there are a lot more people looking to switch in the EU because of regulation. Everyone's asking oh, is Google Analytics illegal? That's a kind of hard question to give a yes-no answer for but it does mean that if you're in, under GDP or in the EU, of course then you could say that people in the US are under the GDPR as well in some ways, but it's a much bigger concern there. So the idea of using something other than Google is a bigger issue and a more pressing issue.

Jason: But as far as your specific question about modeling happening on other platforms, yes and no. Again, that's a sort of multiple paths question where you've got some of these tools that are focused on tools that don't need consent or likely don't need consent.

Jason: I hate to say it like, you don't need consent at all but something like, again I'm not talking about Plausible that it uses user agent and IP and then hashes that, and then like rotates the salt that they use for the hash every day. So there is really no concept of a recurring user beyond that one day and so they don't really need to do that kind of modeling because they're able to capture most of the data to start with. They're still subject to ad blockers, of course you can work around that but that's not as big a thing as some of the other ones where they're the ones that are cookie-based and likely do need consent.

Jason: You do see that trend, but I think Google is in the lead on that, for better or for worse. I don't love the idea of defaulting to data driven attribution within GA4. I think that's going to bite a lot of people after that switch happens and they don't realize some of these changes that have been made for them.

 Jason: Even if you could, you might argue that, hey, like these modeled conversions are more accurate. Web analytics data has always been directional. We've always been missing some of the data, whether it was back in the day people didn't run JavaScript or if it was people running ad blockers.

Jason: Now it's people, those things, plus people that haven't given their consent. We've always been, it's always been directional data. It's always been missing information and so like this idea of, oh now we're modeling based on what we think the missing information is. You're introducing more complexity to something that's already pretty complex.

Jason: I would, I personal preferences to when possible use like the quote-unquote real numbers rather than the model numbers. As you're talking the model numbers or you're like this is a modeled number, but it's actually only based on some of the data anyways. You're just adding caveat on top of caveat with some of this stuff. I understand why it's being done and it is necessary I think but my preference would be instead of trying to collect more data and then modeling what you miss, try to collect less data in a way that you can collect a larger percentage of the data and use other numbers.

Roy: Yeah, for sure. I think anybody who deals with data on a regular basis is also just inherently skeptical of modeling, just when it's a black box, you don't know exactly what's going into it or what the elements are and it just doesn't smell right sometimes. 

Jason: And people that have been dealing with Google Ads have been seen working with this kind of model data for a number of years now and comes up a lot.

Jason: The idea of, what is 0.2 of a conversion? What does that mean? That can be tricky and ours talk about this idea of having confidence in your data, right? Like when you know stakeholders, once they hear a certain number of caveats, then they just lose faith in the data itself which is really a problem. You want people to be able to make data-driven solutions, but in the back of their minds, if they don't understand all the why these caveats are there, then you get in a situation where they just don't trust the data. So we don't trust the data because we know how many caveats there are, but we don't trust it but yet we also know that it is true, in which ways it's true and useful. So when you have a situation where what is this? What does this modeling mean exactly? Oh well, it doesn't include people X, Y, and Z. How can this be accurate at all? And then you just give up on the whole idea of data-driven decision-making. That's really a problem. 

Roy: Yep for sure. And we run into that problem too with clients and executives who if you have two analytics tools on your website, say you have Adobe Analytics and Google Analytics, and they look at the numbers and try to compare them their automatic assumption is that something's broken.

Roy: It's like you have to go through that process of explaining these different definitions. They use different models, they're implemented differently. 

Jason: Yea, leet me explain hyper log to you. 

Roy: But that, their initial knee jerk is that this must not be accurate because they're both not the same. How do you have different reporting with tools that are on the site? 

Jason: Yeah and that's something going to and continue to be a problem. I think segues into this time that we have people running multiple tools. In the day of Universal Analytics heyday, it was ubiquitous. It still is pretty ubiquitous. It was the main source of truth for a lot of places. Now, what is that? If we're running like GA4 and Amplitude and maybe something else, like they're never going to match. That's just the way it is like you say.

 Jason: But how do we get teams communicating when they're not even starting from the same metrics? So they're starting from the same ideas. If the marketing team is starting from GA4 and they're looking at the way things are defined in there, and the product team is starting from Amplitude and looking at the way things are defined in there it makes communication and collaboration really hard.

Jason: It's going to really require a greater degree of education in terms of what these tools do. But then also I would hope a certain amount of trying to extend that particular tool rather than immediately jumping to another tool. And that's something I want to make clear with my book and this idea that I'm reviewing a bunch of tools. I've always been interested in tools and I think it's an interesting thing to talk about and a lot of people do but it's really more about how you use the tool and if you're running three different tools and they're all just stock installed and you got three different teams using three different tools, you're just setting yourself up for trouble versus maybe you have one tool and it can't do a hundred percent of what you want, but you've extended it and customized it for you, and all your teams are using that tool. You're just, you're going to get a better result from that and it's going to be cheaper. 

Roy: What are some of the hurdles that you've seen for people that are used to or could potentially be in place for people that are used to Google Analytics and they want to explore some of these other tools, what are some of the cautions that you'd have?

Jason: It's the same as dealing with GA4, right? GA4 is so different than UA you have to really learn a lot about how each tool works at a fundamental level but again, depends on the tool, right? If you're moving from universal analytics to Piwik Pro, it's actually going to be an easier migration than UA to GA4 because it's pretty similar versus if you're moving from, a UA to Amplitude or UA to PostHog or something like that, then you know it's going to be more of a learning curve. I think that probably the biggest things I would say is related to how you get support and how you learn things.

Jason: No other alternative has the community of GA. It's so much bigger than all the others that like, there's no SEMO or Java out there for publishing great content on, a weekly basis for a tool other than GA. So if you're using one of each other tools, you're going to rely more on the vendor and that's going to mean probably that you're going to want to pay. People have to get used to the idea that analytics probably costs money. If you're paying like money for your analytics team, why aren't you paying money for your analytics tool? GA has really warped our idea of how this should work.

Jason: That something that collects billions of hits and stores data forever, of course GA doesn't store data forever but UA did, and it's free. We gotta adjust our ideas about that. Then if you're working with a vendor, a lot of the knowledge sits at that vendor but that vendor also is likely to give you better support than Google did because Google doesn't really give you any.

Roy: Support is pretty non-existent for Google products.

[00:31:17] Jason: Yeah. Even if you're paying, you get good support if you're paying for 360, you'll get support from the person that the agency that sold you it, but you won't get anything from Google. Versus if you purchase, I keep using the same examples, but if you purchase from Amplitude you're going to get good support from Amplitude. That one, in particular, has a growing community but it still has a lot less out there in terms of the recipes, the pre-built stuff, the deep dives on blog posts for particulars about that.

[00:31:59] Jason: That's not going to be around if you switch. You're going to want to pay for support, probably. You're going to want to work with an agency that has a lot of experience with that particular platform. Yeah, I guess that's probably the biggest thing.

[00:32:16] Roy: Now I know that one of the great things about GA and I think that people become dependant on is the integration with Google Tag Manager in making it easier to implement across different types of sites. Especially with GA4, that integration is really tied into being able to use Google Tag Manager (GTM).

[00:32:42] Roy: What are some options for deploying these other tools that you've used? Theoretically, you probably could use Google Tag Manager for some of the deployments but is it more of a manual process? 

[00:32:54] Jason: So for all of the tests I did, I actually did deploy through GTM. Some of them I also deployed directly on the site for testing purposes and to see how it worked.

[00:33:08] Jason: But you certainly could use GTM for pretty much any of these. It doesn't have, some of these have built-in templates in GTM either pre-built or more likely in the community but a lot of them have official ones in the community that you can use. You can pretty easily deploy most of these through GTM still, you don't get a level of integration. Some of these do have their own tag managers; such as Matomo and PiwikPro have their own tag managers that you can use to deploy it. I wouldn't necessarily recommend, if you're using switching to those for example, if you're going to switch to PiwikPro and you're already using GTM and you've got a whole bunch of tags in GTM, I would recommend for those people that they stick with GTM and deploy PiwikPro through GTM rather than switching their whole tag management basis over to PiwikPro.

[00:34:18] Jason:. Versus if you don't have a whole lot in GTM, if GTM is really just your GA tags, then that makes switching over to a different tag manager a lot more reasonable. Then some of these again, like Matomo and Piwik have more and better tools available as far as things like consent management. Rather than using an external CMP, you could use one of these tools built in CMPs and have everything in the same place.

[00:34:55] Jason: Some of the others more in the product analytics space, if we're talking to something like Snowplow that's going to require more work on the instrumentation side. That can be pretty challenging to implement and I would say the same thing about many of the ones in the product analytics space.

[00:35:317] Jason: We've been talking about Amplitude and Amplitude in a situation where somebody wants to switch to Amplitude and they drop the tag on the site and then they expect data and it doesn't work that way. You've got an instrument, you've gotta build reports. It doesn't come with things out of the box.

[00:38:39] Jason: Some follower may even say even more so be prepared to do some work for instrumentation. If you were dealing with most of these product analytics ones, some of the ones do have auto-event tracking like PostHog has auto event tracking.

[00:36:03] Jason: So everything that you click on is generating an event and then you're defining which events you want to do reporting on, but there's still instrumentation work in that. Even though you're not having to define what all the events are, you're still having to say: what are the events that I want to use for my reporting.

[00:36:22] Jason: One of the things I talk about in the book that I would like to see in theory, is this idea of doing more in the data layer. Especially if you're using multiple tools. Imagine if you're using both GA4 and let's pick a different product like Heap.

[00:36:45] Jason: Then and if you want to take these events rather than instrumenting twice, you want to instrument once in the data layer and say if it's an add to cart button, your add to cart button pushes an event into the data layer. Then in your tag manager, say GTM, you pick that up and then you fire off whatever events to whatever your analytics tool is. So you're moving, you're taking that instrumentation. It's a little more work to instrument, but you're taking that instrumentation logic and you're making it more configurable. You're making it more independent of the particular implementation platform.

[00:37:34] Jason: Rather than, when we think of GA events, we might think of the GA Universal Analytics GA functions, right? GA blah, blah, blah to fire an event. I'm saying do that with data layer, pick up the event in GTM, and then fire that off to GA4 and Amplitude.

[00:37:58] Jason: I'm not sure, I haven't seen a lot of people do that. There's still different sorts of standards for the GA data layer versus Adobe's definitions. We're ways off from that but that's a way that I would like to see and the end could make your implementation more tool agnostic.

[00:38:19] Roy: Talk to me a little bit about dashboarding and reporting. One of the nice things historically with Google has been its integration with Looker Studio, formerly Data Studio. Obviously, most companies have gotten used to free dashboarding and not having to go buy something like Tableau or something like that to do their reporting and dashboards.

[00:38:45] Roy: Do most of these tools have some sort of integration with Looker or do they have a similar Looker Studio type of interface that they can build custom reporting? 

[00:38:55] Jason: Kind of varies. Most of them do not. This is again an advantage that Google has, is this whole old, GMP and the Looker Studio and Looker and are ubiquitous integration everywhere. Some of the tools, like the simplified tools, don't tend to have that. If you need reporting that you're usually going to have to get it directly out of that tools dashboard itself. Some tools, some of the more commonly used ones do have integrations with Looker Studio.

[00:39:39] Jason: Some of the connectors, like you might have to buy the connectors. You might have to buy it from Supermetrics or something. But a lot of them do have those connectors. So you could continue to use Looker Studio and that's probably what I would recommend for most people.

[00:39:58] Jason: For the very simplified ones, I would just suggest just go get it directly from the dashboard cause you're probably doing more ad hoc reporting rather than creating these dashboards that bring data together from three or four different places. So it is going to be more difficult and there isn't much Homo Dash or something that's similar. There's not like a clone of that or a clone of Looker Studio. I still really want to call it Data Studio every time. 

[00:40:39] Roy: I do all the time. It's taken, I've had to literally consciously make myself call it Looker Studio. Especially since the URL is still Data Studio.

[00:40:48] Jason: Oh, I thought they updated. Is this still?

[00:40:50] Roy: I don't think so.

[00:40:56] Jason: That's going to be a challenge, but depending on the tool, like if you're in Piwik Pro that's more similar to Universal Analytics, you may not necessarily be wanting to create an external dashboard. You might not need it. 

[00:41:13] Jason: Versus if you're in Snowplow. Snowplow has no, there is no reporting interface. The reporting interface I think I say in the book, the reporting interface is an S2L prompt. That's a tool for somebody that's already using, Tableau or Power BI or something. Or they already have some sort of practice where they really just need the data collection part of the ecosystem. 

[00:41:50] Jason: So yeah, a lot of these tools, they don't really have a big impact on the dashboarding side of things. Whatever tool you pick, you will want to check to make sure that it does have that integration since unlike live Google not everything has that integration and you aren't going to find that everywhere. 

[00:42:15] Roy: Yep. All right. So I'm going to ask you a really unfair question and prefacing with it that most of these tools, some of them have very specific applications, they're not necessarily right for every company. What are your top two favorite tools that you were working with?

[00:42:32] Jason: So in the book, I label a few favorites per category. In the sort of traditional web analytics category PiwikPro is my favorite. If you've worked with Matomo, it's somewhat similar. If you've worked with UA, it will feel similar. 

[00:42:57] Jason: In the simplified area, Plausible is my favorite. I mentioned them before too. I use them on my own website. There's not much to it. A lot of people talk about oh, I just switched to Fathom or Plausible or whatever. Then you really didn't need all that was in GA to start with because you went from 500 dimensions to like 10. It's a simple product, but, sometimes simple is good. I think that they've been doing a good job. 

[00:43:37] Jason: In the product analytics realm, PostHog and Amplitude are my two your favorites. For different types of companies, Amplitude is more on the enterprisey side if you have a big website with a lot of different functions. Like if you have need of the product analytics thing and you've got mobile as well and you're willing to do the work and you're interested in collaboration. Like you have a whole team of analysts, then I think Amplitude is really excellent and really a high quality product.

[00:44:25] Jason: And then I like plug sorry, I like PostHog also in that category. For say, if you're a SaaS startup and you want product analytics and some other stuff as well. PostHog has other things in it like a session recording built into the platform. They call it, I think they call it like a product OS platform.

[00:44:50] Jason: It's got not just the basic web analytics and product analytics stuff, but it's also got things like the session recording and having that all under one roof. Like I mentioned before, it has auto-event capture, so you don't need to do a lot of work to set it up and tag things.

[00:45:11] Jason: It's a smaller company and it's a newer product, so that's maybe not the best fit if you're talking enterprise. But if you're like, I see that as a great tool for something in the SaaS startup that has a product and they want to track users through that product and then connect that to session capture or something like that. That could be a really good fit there. 

[00:45:40] Jason: So yeah, those are probably the, I think you said name three, I named four. Don't make me pick.

[00:45:47] Roy: Right? Yeah. That's like picking a favorite child or something. Yeah. So you've mentioned your book. Where can our listeners go get it? 

[00:45:57] Jason: GAalternatives.guide is the URL net.

[00:46:03] Jason: That's our redirect, my quantable.com website. It gives you the options to buy it from Amazon or buy it from Gum Road. Gum Road has the ebook and PDF versions. Then Amazon, if you want a printed copy you can also get it on for Kindle on Amazon. Yeah, that's where you can get it.

[00:46:27] Roy: And we will also link to that information in our, when we post the video on the podcast as well, so that way people can get to that. Really appreciate you taking some time today to talk to us. This is very interesting. Obviously, this is an area that's near and dear to our hearts. We're always looking at other options for our clients and for the teams that we work with and obviously, like I said, there's some frustration with GA4 right now and I think a lot of people are looking at what is out there that could work for them. 

[00:46:57] Jason: Yeah. A topic, obviously, that I have a lot of interest in. So great to be able to talk a little bit about it.

[00:47:05] Roy: Well great. And like I said, thank you very much for joining us today and we'll, as you get more data and collect other information about tools, we'd love to have you back and talk about those in the future as well. 

[00:47:15] Jason: Yeah. The future versions of the book where I continue to evaluate more and more by version, five, I'll be up to a hundred different options or something. I don't think so. 

[00:47:24] Roy: Right, especially as the market keeps going crazy. Yeah. 

[00:47:29] Jason: Sounds good. 

[00:36:44] Roy: All right. See. Talk you, Jason.