#72 A conversation on BigQuery and GA4 (with Johan van de Werken @ GA4BigQuery.com and New10)

The Measure Pod
The Measure Pod
#72 A conversation on BigQuery and GA4 (with Johan van de Werken @ GA4BigQuery.com and New10)

This week Dan and Dara are joined by Johan van de Werken, creator of GA4BigQuery.com. They chat about how GA4BigQuery started and where it’s going, how Johan moved from letters to numbers, how the GA4 BigQuery course on Simmer was designed and developed, and we hear about his punk rock cover band!

Check out Johan’s website GA4BigQuery.com. And Johan and Simo’s Query GA4 Data In Google BigQuery on demand training course over on Simmer.

In other news, Dan gets ‘on deck’ and Dara plays a video game!

Measurelab is hiring! Head over to our careers page to see what positions we have open and apply.

Follow Measurelab on LinkedIn.

Intro music composed by Confidential – check out their lo-fi beats on Spotify.

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Let us know what you think and fill out the Feedback Form, or email podcast@measurelab.co.uk to drop Dan and Dara a message directly.

Quote of the episode from Johan: “Even if you can write perfect SQL, if the syntax is valid and there’s a little green check mark in your editor, you can still get pretty shitty results”

Quote of the episode from Dan: “…it could be this time in six months’ time, we’ll have a different opinion entirely with this ecosystem.”

Quote of the episode from Dara: “…rather than it being a kind of an evil plan, if it’s more of an acknowledgement of the kind of shift in the industry itself…”


The full transcript is below, or you can download the transcript file here.


[00:00:15] Dara: In this episode, we’re joined by Johan van de Werken from GA4BigQuery.com. We chat to him about his motivations for setting up that domain and what he’s up to these days.

[00:00:25] Daniel: We talk about all things Google Analytics 4, BigQuery, and we find out what kind of things you would want to change with the data set, if he could wave a magic wand. We’ll also link off to his course he’s done with Simo Ahava’s Simmer platform, so there’s a lifetime membership for learning GA4 BigQuery data exporting and querying over there. And we’ll send off links to his own GA4BigQuery website where you can get free resources and also check out the subscription he’s got over there too. Lots to look through, lots to listen to, I hope you enjoy the show.

[00:00:52] Dara: Hello and welcome back to The Measure Pod, a podcast for people in the analytics world to talk about all things data related. I’m Dara, I’m CEO at Measurelab.

[00:01:02] Daniel: I’m Dan, I’m an analytics consultant and trainer at Measurelab.

[00:01:05] Dara: We’re also very happy to be joined this week by Johan van de Werken, who is a digital analyst at New10. But we know of Johan from his great work at GA4BigQuery.com. But Johan, I’ve partly broken my own rule here. Usually we get people to introduce themselves so I have given a little bit of a spoiler, but could you just tell our listeners a little bit about your journey into analytics, maybe leading up to what you’re doing today.

[00:01:29] Johan: Yes, sure. As we speak, I’m employed as a digital analyst at New10, which is a subsidiary of ABN AMRO bank in the Netherlands, like a top three bank. But I ended up in the analytics space via, well not a very common route, I would say. Because I started my career as a journalist and so I studied journalism, worked for about 10 years in journalism. And eventually I thought it was time for something else, so I was very language minded and now I turned into, well, a digital analyst, a data analyst you could say. And the main thing I care about nowadays is numbers. So from letters to numbers, that’s basically my journey.

[00:02:11] Daniel: There’s something oddly poetic with that, Johan, I love it. Everyone’s got a unique journey into this industry and yeah, I think that has to be up there, I think that’s one of my favourites.


[00:02:19] Dara: So, Johan, as I mentioned, we obviously know of you, we haven’t met before, and it’s really nice to have you on the podcast and we’re definitely looking forward to kind of getting to know a little bit more about the, you know, the motivations behind GA4BigQuery and some of the other work that you’re up to as well. But that’s where we know from, and you’ve got some big fans at Measurelab who love the website and love it as a resource. I’m going to state the obvious first, which is, it’s an amazing domain, you must feel very proud to have got your hands on that domain name. But tell us a bit about the kind of, you know, maybe the starting point, what the motivation was and what the kind of beginning of that journey looked like.

[00:02:52] Johan: Yeah so the domain name, I was quite happy with that myself. Well, where it all started was in 2019, I guess, when I was still working on the Universal Analytics BigQuery export data. Back then, I was a consultant at a digital marketing agency in the Netherlands. I really struggled with that data, so I was used to crunching the numbers in Google Sheets, using the add-on the export add-on from added GA API to Google Sheets. Basically all the magic I did was happening in well, Excel formulas. Then I dabbled a bit into the export. I was working for some enterprise clients, because obviously only enterprise clients could access the BigQuery export for Google Analytics back then. So that’s where my first steps into the data warehouse world happened. And then I found out it was really hard to get my hands on some proper example queries for that data set. And what I saw in the export tables, it was completely different than a lot of stuff I saw in the user interface of Universal Analytics.

[00:04:00] Johan: So basically I dove in, I think six months later I woke up, had a lot of knowledge all by trying and failing and just querying myself. And I decided to write a Medium article about it with a lot of example queries. And so basically the documentation I was, I would like to have had, but it wasn’t there. Google had some queries, but it was very basic, and all the documentation was not really great I would say. Also the definitions were fake or non-existent. So I figured with my background as a writer, I could share some of my knowledge for the community, I got a lot of views on that, on that page.

[00:04:39] Johan: So by the time GA4 was announced, back then it was called App + Web properties. I think that’s like two, three years ago now, 2020 or something, maybe a little earlier I don’t know. Then I thought, yeah okay, this is probably becoming a different data set because I already knew it was, it would be event based. So I could guess that the whole data set would be radically different I think because I was working at that agency, I had access quite early, we’re a Google partner, so I could play around with the data and of course it’s also the same, more or less the same as the Firebase Analytics export data set.

[00:05:20] Johan: So I could play around at will, and of course I did the same thing I was used to, just document queries, share it with the community and write it down. That was still happening on Medium and then I was thinking, what if I could create like a knowledge hub somewhere on the internet. Let’s claim a domain name, let’s bring everything together there. I wasn’t thinking about any monetising strategy back then, I just wanted to create that place where everyone could go. Google was heavily lacking in providing documentation. Once the GA4 name was announced, like Google Analytics 4, I started thinking about the domain names and yeah. Playing around with words was always my type of thing so that one came quite naturally to me.

[00:06:09] Johan: And then I started writing some, yeah, basically some blog post with, mostly it was about dimensions and metrics. Just say, hey, if you want to grab that dimension or that metric, you can use that field, or in case of most metrics, you have to calculate something, you cannot grab out of the box. So probably when you have to get engaged sessions, you need to know what it is, what does it mean, but also which event parameter you need to count a distinct amount of well, session IDs, there’s already like five steps there right, for such a simple task. It sounds simple, but it’s not simple. And of course you have to learn SQL otherwise there is no way to get any information from the GA4 export.

[00:06:54] Johan: So I also wrote a bit about that, then Simo contacted me. He said, I like your website, I’m thinking about setting up a platform for online courses, video courses, and I’m looking for an instructor to design and well, teach a course on GA4 and Google BigQuery. I had a lot of quite specific knowledge already and he had a platform, so that sounded like a good collaboration and we’re still like, quite happy with how it turned out.

[00:07:22] Daniel: That’s amazing, we can definitely relate, especially around structuring learning and how difficult that can be. Where do you even start? If you’re taking all this deep experience and knowledge that you’ve got, especially when it’s something like BigQuery, Google Analytics 4, SQL, the GCP. Where did you start and how did you approach that training course?

[00:07:38] Johan: So we talked a bit about it. There are like a lot of free SQL courses out there, right? So that’s not, that was not the way to go for us. How do you calculate stuff, how do we extract the data, how do you create a Google Cloud project? That kind of stuff. But it’s actually a lot about definitions as well, because just getting access to a data export table with raw event data well, good luck. If you don’t have the Google Analytics scopes in the back of your head. Like, what’s the user, what’s a session, what’s an event, what is an item. Then it’s still not, it’s very hard to get the data that you will need. Even if you can write perfect SQL, if the syntax is valid, there’s a little green check mark in your editor, you can still get pretty shitty results right.

[00:08:32] Johan: So that was another thing, and then we thought about who is our audience for this course. So actually it’s a pretty broad audience, but the main focus is on marketers, right? So Simmer was also, it’s aiming at making marketers, technical marketers, something like that. So we had to assume that our audience didn’t know SQL, didn’t know how to get access to and create a Google Cloud project. And maybe they also needed some help with user scopes, definitions, that kind of stuff. So that’s a lot to offer that, to cram that all in a video course. So I just decided to start, well, at the beginning. How do we set up the export, then just look at a table, what do we see? How is it built up? So every row is what, well, every row is an event. How does that relate to Universal Analytics where every row was a session and why is that different? And then we proceed to talk about what is a user, what is the user pseudo ID? What does that mean? Is that a cookie? That kind of talk.

[00:09:43] Johan: Then we move to sessions, how can you create a session from a table that is structured around events? How does that work? And that GA session ID there, that field, is that a session? Well, no, because it’s not unique. So how can you create a session ID? Well, by combining that with the user ID, that kind of stuff, all need to take that into account before you can really do the magic there. And of course, we end up with the really advanced stuff, at least for technical marketers, it’s advanced. And that’s the analytical functions and all kind of tricks to do stuff like calculate user retention and that kind of stuff.

[00:10:24] Dara: It sounds from what you said, that it’s basically your own learning journey, isn’t it? You’re obviously in the practice of documenting your own learning and a lot of those examples even that you’ve given already, they’re very practical examples of use cases. Of understanding the definition of different dimensions and metrics and what you might want to calculate. So is that fair to say that a lot of this content was actually your own documentation of your own learning journey?

[00:10:48] Johan: Definitely, the articles I write are most often the direct result of something I learned or experienced in the week before. So right now I’m doing a lot of attribution stuff at my work as well, and I know what the limitations are of attribution models, especially with GA4, but obviously there’s a lot of demand, especially from the marketing department to say something about campaigns, right? So I’m still working on optimising the custom models we built ourselves, in our warehouse and that experience, I can like one-on-one use it in my hobby.

[00:11:24] Daniel: Do you find that the more you use sort of the warehousing side of things, the more you use BigQuery around Google Analytics 4 the less, how do I phrase it? Like the less need you have for logging into GA4 or using the Data API full stop, or actually do you find, because I know that there’s fundamental differences in the two sets of data in the kind of UI/API data, and then obviously in BigQuery, obviously made a name in a sense from the BigQuery aspect. But do you still find yourself being drawn back into that world of the kind of pulling in the Google Signals data or the other bits of data and the other bits of events that aren’t exported and going back into the API, do you see what I mean? I’m just trying to think about do you get drawn back into the world of the data that doesn’t exist within the BigQuery export?

[00:12:01] Johan: I do, but to be really honest, when I log into the user interface, I go to Universal Analytics because I’m so used to those reports right. So that’s what I do, and when I’m working on GA4 stuff, I really look at yeah, the results of the models I build myself. Because I’ve seen so many limitations when it comes to the user interface of GA4 that I, yeah I’m really starting to lose some trust there, I guess. I don’t want to sound too dramatic, but once you have experienced the results of the queries, the models you created yourself, you customise it to the needs of your business. And it’s hard to look at a user interface that is far from, not only far from what we were used to in Universal Analytics, but also sometimes I just don’t understand the choices that are made there. So I really hope that’s going to change in the future because I also get reactions from colleagues of mine, from the marketing team that really struggle with adapting and migrating to that new user interface. And they’re not able to use that raw data, they’re more on the well, creative marketing side and not so the technical marketing side. So either they use Universal Analytics or they use dashboards I create for them right, or reports. So that’s where we’re at now.

[00:13:28] Dara: I do wonder, this is moving into speculation, but I do wonder if it’s by design. I don’t think it’s a coincidence that the GA4 interface is less usable and if it’s just part of this bigger push towards the GCP tools. So, you know, Google’s answer would be, obviously you can, you know, create Looker Studio dashboards from the BigQuery data. But I appreciate what you’re saying, it’s the same for some of our clients you know, if they’re working in the marketing team, they don’t necessarily have the knowledge of BigQuery. But it does feel like maybe Google, that’s a, a kind of calculated bet that they’re taking to say, look, we’re actually going to make the interface less usable to push people more into using the cloud tools.

[00:14:08] Johan: Yeah, I’ve read an article as well about this hypothesis. I’m not sure, it could also be just not caring about users of that tool, because in the whole big Google world, the whole Google Analytics stack is a really small part of course. They do care probably about Google Ads a lot more than Google Analytics. So I’m not sure, I don’t think there’s an evil strategy behind that I think it’s, yeah, I think they’re failing to really understand their users. They underestimate how it’s used, how Universal Analytics was used, how different this product is. What they delivered and still, it’s still work in progress. Let’s also not forget it, it is not finished. It’s not a final product right.

[00:14:53] Dara: Maybe another way to think about that rather than it being a kind of an evil plan, if it’s more of an acknowledgement of the, the kind of shift in the industry itself, so maybe it’s more thinking that a standalone kind of interface for looking at web and app data isn’t going to be needed. And that actually more and more companies are going to have multiple data sets and they’re going to be sat in a data warehouse, which does obviously change the requirements of who’s going to be able to access and use that data. But maybe it’s more around, you know, and again, this total speculation, but it could be that they no longer see a need to kind of invest in the interface when actually it’s all of the kind of behind the scenes, the storage and the processing of that data that’s really the, the kind of key.

[00:15:36] Johan: That would be a totally valid strategy, but they seem to invest a lot in the user interface.

[00:15:46] Daniel: I think it could also partly be to do with the target audience of Google Analytics. I think it’s always been, you know, they put it in the Google Marketing Platform and they keep saying that their target audience is marketers, and marketers should use it, and it ties into the Google Ads and everything else. And so I’m wondering if they’re going all in, in a sense on that, and so in Universal Analytics, and Dara is probably sick of me saying this, but Universal Analytics was focused, basically it was a data tool with a marketing layer, like a modular layer that you can plug in. Whereas GA4 is a marketing tool with a sort of analytics layer, data layer. Not a data layer, do you see what I mean, a module. So like in a sense, if you’re a data person, GA4 is going to be less familiar and less useful. Whereas actually marketers, you know, it’s all built to be marketer friendly, to plug into Google Ads, to kind of sync your conversions and your audiences. In a sense, I don’t know if I had to make a on the spot, sort of like a prediction, I can imagine it’s just going to be the audience definition screen for the wider Google Marketing Platform. And in a sense, it doesn’t need to do much more than that because it’s about marketing, as you said, it’s where they make their money right.

[00:16:43] Johan: Yeah it makes a lot of sense, definitely.

[00:16:45] Dara: Just going back to your GA4BigQuery website for a minute. You mentioned earlier about how when you started out you didn’t really have any thoughts on monetising it. So how have things changed now? Because I know you do have some paid content on the site, so have your kind of ambitions or your goals for the site changed a lot since you first set it up. But actually, sorry, I’m going to squeeze it in another question as well, which is, were you expecting it to be as popular as it turned out to be?

[00:17:10] Johan: Yeah, to start with the last question, definitely yes. Back then when GA4 was announced or App + Web at that time, it seemed like there were only maybe myself and maybe some other people, but I really wondered why am I the only one that is seeing what’s going to happen here? Not to sound like a prophet or something but you know that Google Analytics has millions of users, right? So imagine that everyone is forced to migrate to another version, and that in combination with a GA4 export, a native connection to BigQuery that is accessible for every property, including the free users, right? So those two things together, well, I had a feeling that could be a flywheel, so that’s also why I created this domain name.

[00:17:56] Johan: But to be honest, I only started thinking about monetising some content. To be really clear, everything that was on there is still accessible for free, I’m only adding new content in the form of tutorials that I well, sell as premium content. The idea behind it is that I’m interested in the creator economy as well. The idea of, as a content creator, how can you monetise the value you bring basically to a broader audience and how you can skill that. So it really turned out as you could say, a side hustle that also generates some passive income. But it was never the main goal, it just happened to be an opportunity and yeah. It’s also very clear, so everyone that is using the BigQuery export is probably doing that on behalf of a company. Companies have budget to spend, so that was all the part of the thought process.

[00:18:52] Dara: You mentioned that we’ve talked about on this podcast so many times before about like what a big deal it is that the export is available to everybody now because, you know, in the old days when it was only available for 360 customers, it really was quite a small, like a relatively small percentage of overall Google Analytics users and given pretty much every marketer uses Google Analytics, do you think knowing some degree of SQL now at least BigQuery flavour of SQL is going to be an essential kind of part of any marketer’s tool set going forward?

[00:19:20] Johan: Well, if you really want to be future proof as a marketer, I would say yes, you need that. But I also see that a lot of people are really scared to take that hurdle. And that’s not only because I think that’s, it’s not only about learning a new programming language. As I just said, learning SQL is not that hard, it’s actually one of the easiest languages to learn, but really understanding what you are doing especially when it comes to the scope of the data, event, user, session, item, all that stuff, that’s something you can only learn by practicing a lot. Even if you do a training, it’s still really hard to do that without practice, to really understand the concepts of the data you are working with. I think it took me years, to be honest, to get to that point where I’m really comfortable talking about it so, yeah.

[00:20:11] Dara: I agree with you, and I think I read on the, this was on the training course that you’ve developed with Simo on the Simmer platform, but I am I right in saying you can, that course is aimed at people who potentially have zero SQL experience. But you do have to have GA4 experience because as you kind of rightly say, if you don’t understand those kind of nuances with the way GA4 works, you could even be brilliant at SQL and you wouldn’t actually be able to kind of get the most out of, out of GA4. You do need GA4, but you don’t necessarily need to know any SQL before you go on that learning journey.

[00:20:45] Johan: I think we also aim it a bit at, let’s say, engineers. Data engineers that need to extract the GA4 data. So there’s a lot about explaining Google Analytics specific things in there as well, but the main focus is definitely on marketers here. And indeed we start with what’s the select statement, so that’s really basic. The first thing you have to know from learning SQL, right? So it’s a zero to a hero course. But definitely if you’re a marketer, I still would recommend to start in a spreadsheet first. If you never worked with data before, just start in a spreadsheet because basically it’s a data set, right? What is a column? What is a row? That basic stuff, it’s really good to have that first and then well upgrade to SQL. At least that was my journey, I really found it helpful to, to have that background. And also aggregation functions like sum or min/max, all stuff that is not really complicated. It really helps if you use that and recognise it from the spreadsheets, the spreadsheet you were working in before.

[00:21:56] Daniel: So something that’s helped me a little bit with this as well is using the connected sheets sort of feature of Google Sheets with BigQuery. And so like you can still get that Excel vibe in terms of querying the data even though you’re going through BigQuery. So it’s almost like a stepping stone to going straight into the BigQuery interface. Yeah, definitely worth kind of dabbling with if you are like me more familiar with Excel and Sheets and not quite ready to go into the coding interface, you know, where you don’t get to see a live preview of it necessarily without clicking run.

[00:22:23] Johan: I’ve never really properly used that. I think I moved to BigQuery just before that feature was released. It’s still on my list to write about, especially in the context of GA4 of course. I really like that they are trying to remove that hurdle there a bit. And that’s another thing that people can be scared about or worried about and that’s the cost element, of course. That’s also something we talk about in the course. Especially when it comes to feeding your visualisation tool or your BI tool with data from the export, how can you optimise it? How can you make sure you’re not querying the raw data set every time you click a filter in Looker Studio, because that can get out of hand pretty quickly.

[00:23:07] Daniel: That’s the thing is that most companies, they’re quite happy to pay for something, but they need to know how much to budget for in a fixed cost line-item thing right. And so when you say, give me your credit card details and I don’t know how much it’s going to cost month to month, everyone gets a bit nervous, don’t they, when they’ve never done this before.

[00:23:21] Johan: That’s why the BigQuery sandbox is really, really nice invention. You don’t need a credit card for that. You just configure Google Cloud project, you can play around, you can activate the export of GA4 as well, and only if you really want to proceed with it. Then you connect your credit card, set up a billing account, and that’s when the actual billing will start. But in my experience, if you have like a normal website and you take into account a few basic rules, most of the time you don’t even exceed the free tier right when it comes to storage and querying. And even if you do, if you’re not querying like petabytes, then you will be probably somewhere within $50-100 a month or something. So it’s really not expensive in general, but of course it depends a lot on, on the amount of visitors on your website.

[00:24:19] Daniel: If this was a drinking game, everyone should take a shot because ‘it depends’ comes up quite a lot in this industry, right? But I think I completely agree and I think this is the kind of thing we talk to people that we work with as well, Johan, which is almost like just go for it. Don’t touch it, you most likely stay within the free tier just in terms of storage and because it doesn’t back date, you know, when you set up the GA4 BigQuery connection, the export, daily export, the streaming export. So just set it up because your future self, in the future will thank you for doing it when you need to use it, but just get it set up and walk away for now. You might not have an application or a use case for it right now, but you will and you will wish you have had that data there. There’s the call out for the episode, just set it up as soon as you can. You’ll probably, most likely, I don’t want to commit to a definite, but you’ll most likely be within the free tier and by the time you come to use it and figure things out a bit more properly, then you’ll be ready.

[00:25:03] Johan: If you do that, then you might consider setting up that billing account. Otherwise, if you use the BigQuery sandbox, your tables will expire after 60 days, I believe. So that is a thing to consider.

[00:25:14] Dara: So that got you into BigQuery and then you documented your own learning journey, and now it all exists on GA4BigQuery. Have you got any, and I appreciate you might not want to give too much away, but have you got any kind of plans to take that further? Is your own learning taking you deeper into the GCP or are you looking at other clouds and other data warehouse technology?

[00:25:34] Johan: Yeah so while my writing is still very much focusing on the Google ecosystem. My personal journey, thanks to my current job where there’s also a team of data engineers. The choice of the cloud is AWS, so it’s a whole different, I’m actually on a daily basis querying Redshift instead of BigQuery, for instance. So I’m already a bit further, I would say compared to people that start with their first data warehouse today. I still have a strong preference for BigQuery though, because I really think it’s the most accessible, most user-friendly thing out there. And another thing is I’m really working a lot in DBT, and DBT is a data modelling tool that you can well set on top of your data warehouse. And in that tool, you can create, let’s say scheduled queries like you can do in BigQuery that run frequently, let’s say every night, and that will query your raw data. Materialise that data in the form of new tables and those tables that could be aggregated tables, that could be the input for your dashboards for, I don’t know, AI models for analysis.

[00:26:48] Johan: So that’s really where I’m at now in my personal journey. And on the other hand I’m also really interested in that creator economy stuff. I really like to optimise my own website, I see it a bit as my own store, right? You can enter my store, you can look around, but at some point I will ask for your email address as well right? So I don’t run any ads, that’s also because I know the limitations. I’m basically interested in email addresses because you can build a one-on-one relationship with your audience. So I offer a monthly newsletter with tips and tricks about BigQuery GA4, that mailing list is, well, my main acquisition channel at the moment.

[00:27:30] Daniel: So, Johan then regarding the kind of wider ecosystem, especially the Google Cloud Platform, it’s vast, it’s massive, I don’t think anyone knows everything. A question for you then, especially with things like DBT, which is becoming quite ubiquitous within the, at least the analytics space for all those reasons you mentioned, but the Google Cloud Platform they’re always developing in new features, new whatever, absorbing new companies. And especially when it comes to things like, I mean, DBT is quite a hot topic at the moment, but they’ve got their own versions of that. Curious to get your views of like, is something like DBT here to stay or do you see these kind of ecosystems evolving and ebbing and flowing and is Google going to sort of suck up all this business? Or do you think there’s room there for multi-cloud structures, multi-platforms, multi sort of vendors within this kind of ecosystem?

[00:28:12] Johan: I think there always will be a preference from the community to open source, right. So I know Google has its own DBT-clone, you could say, Dataform. So like I said, I think the community will have a preference for open source. On the other hand, it’s hard to predict, right? On the one hand, a tool like data form can become very popular because it’s integrated in the Google Cloud Platform, right? But most companies, I think, use all kind of tools, right? They use airflow to ingest the data in the warehouse. They want a tool like DBT or another tool that is cloud agnostic that they can, where they can model the data. They probably have a BI tool or visualisation tool from maybe Power BI or Tableau, right. So it depends a lot on your tech stack, I would say. I don’t think Dataform will on a short term beat a tool like DBT, because there’s a huge community behind it.

[00:29:10] Daniel: For sure yeah, I’m inclined to agree. I like to kind of ask those kind of questions because it’s so unpredictable, really. Just to get other people’s views but especially with things like Looker and the whole Looker Studio rebrand and how they’re kind of going down that path with Looker in terms of that kind of metrics layer and then the visualisation layer and breaking those things apart. And I find it all fascinating and, you know, it could be, you know, it could be this time in six months’ time, we’ll have a different opinion entirely with this ecosystem.

[00:29:33] Johan: Maybe in six months from now, we will be replaced by AI right? Because that’s also what I’m thinking, that’s also what I’m thinking with the GA4 BigQuery with my platform is like, why am I manually writing all this stuff when ChatGPT will be trained on recent content that will include probably the documentation from my own side, so it will understand the data model of GA4. So what’s going to happen there? That’s really interesting, I really like to think about that as well.

[00:30:05] Dara: I think that’s where the value of your domain name will come into play because anybody could replicate the volume of content, potentially using ChatGPT, but they’re not going to have the GA4BigQuery.com.

[00:30:16] Johan: True, but maybe no one will click to a website anymore right? If Google and Bing just give you an answer, then you don’t have anything with the landing page, it doesn’t matter anymore.

[00:30:27] Daniel: My wife’s a graphic designer and a brand designer and I was kind of like going down a rabbit hole with her and kind of, it became a bit scary because she spends her life designing creatives for websites and you know, designing websites and branding. And I was like, there could be a future where no one ever sees the website. You could have an uploaded Google Doc and that could be enough information because you know, people are going to consume it elsewhere. I find that very, very interesting thinking about the future of the kind of how we consume content from websites, we might never leave Google. And I know that’s kind of the same as it is now, but like truly never clicking through to a website that the list search results list might be a thing of the past, you know?

[00:31:02] Daniel: Well look, Johan, I have got one, one question for you if you may. If you could wave a magic wand and you can change any one thing about the GA4 BigQuery export, what would you change?

[00:31:13] Johan: I would start with fixing the bugs that are in there, especially session attribution that is really, really pain in the ass right now. And there’s no traffic acquisition data in the session start event, which is also very annoying. I would start there, yeah. Second thing would be the GA session ID, which is very confusing because everyone assumes that, that one is unique. In fact, it isn’t so because it’s just a timestamp, right. So those kind of things really annoy the hell out of me.

[00:31:46] Daniel: Well, there’s plenty of content for GA4BigQuery though, right, Johan?

[00:31:49] Johan: Definitely, yeah.

Wind down

[00:31:50] Dara: So two more questions for you and then we’ll let you off the hook. The first one, easy one, where can people find out more about you or get in touch with you? Obviously there is GA4BigQuery.com, are you on social channels? How can people get in touch with you?

[00:32:03] Johan: Yeah, so I just created the Twitter account for GA4BigQuery. It’s just posting new articles and I will reply if you have a question, but my main channel, social channel, is LinkedIn. Really works well for me, so please follow or add me and I will also update you on any new content. But the main CTA would be subscribe at GA4BigQuery.com, and then subscribe for the free newsletter. I don’t want everyone to become a premium subscriber. That’s not necessary, although I will donate 10% for every premium subscription to highly effective charities, so that’s the least I can do.

[00:32:43] Dara: Great, and the last question, which some people find the hard one. What do you do outside of work to wind down, your answer might be tricky because when you’re not doing your day job, you’re probably working on GA4BigQuery. So when you’re not doing either of those two things, what do you do?

[00:32:56] Johan: That’s already what I’m doing in the evenings and weekends. And yeah, of course I like spending time with my family, I have two beautiful daughters. But the main thing besides that is I play bass guitar. I like playing in bands, I did it for my whole life. Currently I have set up a punk rock cover band, it’s the first cover band of my life. It’s all about nineties skate punk. So, that is really my thing. And of course the few occasional beers with that.

[00:33:24] Dara: Dan was looking very excited there.

[00:33:26] Daniel: Yeah, I mean, you’ve just described my musical taste as well, so I’m going to have to get a link from you of this band and stick it in the show notes if anyone else is curious. But yeah, I’m keen to listen. Amazing, all right, we’ll load the show notes of the podcast up with links to all this stuff with the Simmer course, the GA4BigQuery and a soon to be musical link as well, hopefully.


Dara: That’s it for this week, to hear more from me and Dan on GA4 and other analytics related topics, all our previous episodes are available in our archive at measurelab.co.uk/podcast. Or you can simply use whatever app you’re using right now to listen to this, to go back and listen to previous episode.

Daniel: And if you want to suggest a topic for something me and Dara should be talking about, or if you want to suggest a guest who we should be talking to, there’s a Google Form in the show notes that you can fill out and leave us a note. Or alternatively, you can just email us at podcast@measurelab.co.uk to get in touch with us both directly.

Dara: Our theme is from Confidential, you can find a link to their music in the show notes. So on behalf of Dan and I, thanks for listening. See you next time.

Written by

Daniel is the innovation and training lead at Measurelab - he is an analytics trainer, co-host of The Measure Pod analytics podcast, and overall fanatic. He loves getting stuck into all things GA4, and most recently with exploring app analytics via Firebase by building his own Android apps.

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