#33 What to do as the sun is setting on Universal Analytics

The Measure Pod
The Measure Pod
#33 What to do as the sun is setting on Universal Analytics
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This week Dan and Dara talk more about the announcement from Google on sunsetting Universal Analytics in 2023. They discuss what the timeframes really mean, and what you’d need to be doing at each stage.

The key takeaway is DO NOT PANIC! Just focus on getting GA4 setup up to a good level before 1st July 2022, and we can think about how to get at the UA data after 1st July 2023.

The PIVOT framework to help get GA4 set up HERE. And check out episode #7 for the deep-dive of PIVOT with the author George Mendham.

Details on the Data Studio update to have up to 50,000 rows in tables – https://bit.ly/3NMljCn.

Simo’s 4 recommended Custom Dimensions to be able to pull out the hit-level data from UA (from 2015… damn I feel old) – https://bit.ly/3sEwNPI.

They also mention a few tool such as Funnel (https://bit.ly/3uOUy7q), Stitch (https://bit.ly/3u81MED) and Fivetran (https://bit.ly/3x2z5dZ) to help aid in transferring data out of your analytics and marketing tools into a data warehouse or dashboard.

Check out on LinkedIn:

Music from Confidential, check out more of their lofi beats on Spotify at https://spoti.fi/3JnEdg6 and on Instagram at https://bit.ly/3u3skWp.

Please leave a rating and review in the places one leaves ratings and reviews. If you want to join Dan and Dara on the podcast and talk about something in the analytics industry you have an opinion about (or just want to suggest a topic for them to chit-chat about), email podcast@measurelab.co.uk or find them on LinkedIn and drop them a message.

Transcript

[00:00:00] Dara: Hello, and thanks for joining us in The Measure Pod, a podcast for people in the analytics world. I’m Dara, I’m MD Measurelab. I’m joined as always by Dan, who is an analytics consultant also here at Measurelab. Hey Dan, what’s new in the analytics world?

[00:00:31] Daniel: Well, other than the elephant in the room that we’re going to be talking about today in terms of the sunsetting of Universal (Universal Analytics), spoiler alert I know. There was a small change in Data Studio that I don’t want to say noteworthy, but it’s worth noting at least. And that is that they have updated the row limit in their table visualisations, which might not seem like a huge deal, but it’s gone up quite significantly. So before you can have a maximum of 5,000 rows and now you can have 50,000 rows and the application alludes me to why this is super valuable. However, I know a lot of people, clients that is that are using Data Studio almost as a UI replicator or replacement and having access to a greater number of rows to then potentially be able to interrogate or export even to a spreadsheet, is going to be valuable to them rather than just being limited to the top 5,000, especially if they’re using it as a tool to batch pull out and backdate data. So I think the applications might be more edge case, but I can imagine it can be quite useful for those people using Data Studio as an interface of sorts, to be able to access this raw data.

[00:01:31] Dara: Yeah I’m with you, I’m a bit cynical. I think if you need to have 50,000 rolls in a dashboard maybe you’re not using a dashboard in the spirit of how it’s intended to be used, but you know, each of their own. So that is probably a useful update for some people. But like you said, a bit of an edge case and nowhere near as significant as the recent piece of news, which we’re going to do a bit more of a deep dive into in this episode, which is of course the announcement that Universal Analytics is going to be no more. So it’s going to be sunset or sunsetted. I don’t know what the correct way to say that is. It’s going to disappear, and we have a timeline for that. We did a little bonus episode a few weeks ago, got a blog post about it but this is our first chance to take a bit of a deep dive into it and give a little bit more detail around what’s happening when, what we’re doing about it, what you might want to consider doing about it.

[00:02:24] Daniel: And I’ll start at the top by apologising because I got a slightly carried away on the last time we mentioned this and I said, quite definitively that we have six weeks. We have six weeks left to do everything to do with GA4, but obviously that’s not entirely truthful. We have a, well, it has a recording and we have three months.

[00:02:39] Dara: Nothing wrong with lighting a fire under people.

[00:02:42] Daniel: Yeah, I got all the times and dates muddled in the excitement of things. So apologies for anyone that listened to me and thought we had six weeks, we’ve got a little bit longer, but actually not too much longer. It’s not a wildly out. If you get this all done in six weeks, then you’ll be better for it. But you do have until the 1st of July, 2022. So that’s the date coming up pretty soon to have GA4 implemented to then by next year’s July the 1st you’ll have year on year data available in your GA4 property, and that’s the whole point, so making sure you have year on year data in GA4 that’s the whole point of why they announced it when they did is so that if you did it now, you will then have year on year data come the date next year. So apologies, and at the same time, why not get it done in six weeks if you can?

[00:03:26] Dara: Sounds like half an apology, you’re sorry, but also try and get it done in the next six weeks.

[00:03:31] Daniel: Yeah, no I am sorry, I’m sorry if anyone took that as gospel, however it’s not.

[00:03:36] Dara: Just to recap on the announcement itself and just to kind of clarify on the timescales. So what Google announced is that from the 1st of July, 2023, Universal Analytics will no longer collect any new hits. So it’s going to carry on as is for the next year and three months and then from that date, 1st of July 2023, no further data will be collected into Universal Analytics properties. And you will, from that point on, have no choice, but to use GA4. So, as Dan said, the importance of that now is getting GA4 set up and implemented as close to parity with your Universal property as you can, to give you that year of GA4 data before Universal (Universal Analytics) stops collecting so then if you need to be still using Universal (Universal Analytics) as you start to educate people internally, as you start to transition reports and dashboards over from Universal (Universal Analytics) to GA4, it just gives you that time.

[00:04:32] Dara: So you would have a year of GA4 data in parallel to your Universal Analytics data before Universal (Universal Analytics) stops. And then you, at that point would have to rely solely on GA4.

[00:04:44] Daniel: Yes, exactly. There’s one slight caveat and that’s if you’re on a 360 contract at the moment, and if you’re on a GA360 contract now you’ll have a three-month grace period. So what that means is all the timings will stay the same, except you’ll stop processing new hits in Universal Analytics on October the 1st. So the timelines are shifted by three months, also, if you are a 360 customer at some point this year when your 360 license comes up for renewal, you’ll probably be asked to go over to the new GA360 that is GA4 focused. One thing with that is that you would have to kind of talk to your Google rep or your reseller around that, but quite often that’s GA4 only, and doesn’t account for Universal Analytics.

[00:05:21] Daniel: So we need to make sure that if you wanted to make it up to the 1st of October with your 360 data, you’d need to make that a standard or old 360 contract, I suppose, whatever they want to call them so that there are some nuances there that you’re not guaranteed to get 360 data up until then you need to make sure that it’s within contract as well. So it’s slightly fuzzy or a grey area on a 360, because I think Google and thus their minions, their representatives, their sales partners probably want to get you onto the new contract as soon as possible if they can, before that date.

[00:05:48] Dara: Just another argument to get familiar with GA4 sooner rather than later really.

[00:05:53] Daniel: Yeah, exactly and the other thing they mentioned is, so there’s a lot of talk about this date, right? It’s almost like D-Day, you’ve got the, let’s just call it July the 1st for argument’s sake, but we know that there’s a three-month grace period for 360. But July the first is the day they stop processing data then what, well at least what they’ve said in the announcement is that you have at least six months to access that data. So Universal Analytics isn’t going anywhere. You’ll still be able to log in, do your reports, do your analysis, do whatever you’re doing. It’s just that, it’s almost like the tags are removed from your website. They’re just going to stop adding new data in from the 1st of July. So you can still access and do all the same stuff you’ve always been doing to the older dataset. It’s just that new data going forward. So that’s the, where we say you have to be using and transitioning to solely using GA4 as your source of truth. That’s what we mean, it doesn’t mean that data’s going anywhere.

[00:06:36] Daniel: So it says you have at least six months of access to do that, and I think the idea there is that you have six months to do what you need to do before it’s gone for good. Or do what you need to do in terms of pulling that data and extracting that data out in somewhere that isn’t going to get removed. So pull it into even a Google Sheet or a spreadsheet or BigQuery or a data warehouse somewhere, but do what you need to do before access is removed. But we don’t know, I think that the big thing is it says at least six months, so at least six months to do something. Who knows, come six months, they might decide actually we meant twelve months. Actually data is never going to be deleted we actually don’t know what they mean when they say at least six months. So it might be a bit fear-mongering, saying as of July the 1st go start exporting all your data, start backfilling it into a data warehouse when it could be futile after all we just don’t know.

[00:07:22] Dara: Well, I guess the key point there is the urgency on getting the data out of Universal (Universal Analytics) isn’t there at the moment. The urgency now is getting GA4 set up and configured in advance of July this year, so that you then have the 12 months of GA4 data running in parallel with UA (Universal Analytics) for when that age where it stops collecting hits between now and that date in July next year, we might have clarity on what’s going to happen. Is it six months? Is it more than six months? Is it going to not be available in the Universal UI, but is it going to be available somewhere else? Is there going to be an option to export it at all? Hopefully there’ll be some clarity, because there’s no need to rush out and start exporting your Universal (Universal Analytics) data now, if you’re not already doing that. You’ve got that time period to see if Google give a little bit of a, well, a less vague statement about what’s going to happen beyond that six month period.

[00:08:15] Daniel: Yeah, exactly just don’t panic I think, don’t even think about it for now, and we’ve got well over a year before we even need to consider it and even then we’ve got plenty of time to figure it out next year. So after July the 1st we can even start figuring out, then we don’t have to even think about it for the time being, as you said, for now the thing we do have to give the time, energy and attention to is the implementation and setup of GA4.

[00:08:35] Daniel: One thing that you mentioned earlier is around the idea of getting parity to Universal Analytics, and yes I agree with that and also no, I don’t. So I’ll try and explain, so first of all, there in a lot of cases, isn’t parity between GA4, but that doesn’t have to be a bad thing. So the terminology, the phrasing that Google are using is that they have reached GA360 or GA4’s 360 has reached parity with Universal Analytics this year. So right now, if you have the 360 version of GA4 you can have parity, and I think that’s because of things like roll-up properties and sub-properties because there are no views in GA4 which is a big annoyance or blocker for a lot of people. So I would say don’t go in with an expectation that you’ll be able to have free GA4 and free Universal Analytics parity if you have six properties with 10 views per property and all sorts of different configuration setup. I would suggest that you kind of go in with a blank piece of paper and start mapping this out from scratch, because it’s not a one-to-one mapping from Universal Analytics.

[00:09:32] Daniel: So yes, try and aim for parity. In some cases you won’t achieve that, but in other cases it will surpass parity. So there are a lot of additional features in GA4 that Universal (Universal Analytics) have never had. So it’s not a one for one replacement, it’s a, you’ll lose something over here, but you gained something over there it needs to be considered separately to be honest.

[00:09:51] Dara: No, that’s a really good point, and actually parity wasn’t the best choice of word to use. What I was thinking was you’ve got that time to set up GA4 in an equivalent way to how Universal is set up now, but you’re absolutely right. It’s not going to be, I shouldn’t wrongly give anyone the impression that it’s going to be exactly like for like, because obviously it isn’t. There was another good point in there as well, which is about almost starting with a clean slate or at least reviewing it with fresh eyes maybe put it that way, because it might be that a lot of your UA (Universal Analytics) implementation is legacy anyway, and you don’t want to carry it across to GA4, so this is a good opportunity to look at your implementation in general and think, do you know what, we’re going to have to implement GA4, let’s rethink this and think are we actually collecting the data we need and are we doing it in the best way? It might be a good chance to leave a bunch of stuff behind that belongs in the past and have a cleaner and more up-to-date implementation that gets the best out of GA4.

[00:10:48] Daniel: I think every setup I’ve ever seen it’s always got some legacy event trackers that no one even looks at anymore, and we’re kind of scared of turning them off because just in case, but actually no one looks at them anyway, but we can’t prove that. There’s a lot of different ways around that, I mean, we did it recently actually Dara with the Measurelab website. We moved to GA4 but we didn’t transition all the events, no one really cared, and because they weren’t using them in the first place. So again, it’s a good example of where you can have a fresh slate and it’s a good opportunity to start thinking about it again also recently, again, we moved to server-side tracking and again, we just, we didn’t migrate all of the events and again, not many people if any noticed at all.

[00:11:21] Daniel: So it’s a really good chance to, in that beta phase where you’ve got it sort of like the initial base config tag set up, and you’re doing just the automatically collected events. Start there and see if anyone’s really noticing any difference and then layer in on top of the kind of core events, especially things like some of the recommended events like e-commerce trackers and things like that. Those kinds of events of course we don’t have to see if we can get away with not tracking purchases, but it’s those peripheral like click events or CTA click or timers on blog pages or like random buttons that probably don’t exist from a campaign that was run three years ago. Those kinds of weird and wonderful events that are in your data schema in Universal Analytics, you just probably don’t need them not to mention the schema is different, right? That’s the other big difference, technically speaking, that is.

[00:12:05] Daniel: The event category action labels, just a legacy archaic approach to tracking any object, actually. Whereas now you have a completely different way of doing it. So there is not a map, a mapping table from the Universal (Universal Analytics) event category action label and value, to the GA4 event, name and parameters, you’ve got a better way of doing it and objectively better way of tracking events, but you just might need to rethink the way you’re collecting data and how that kind of appears in your reports. Even if it doesn’t feel like it right now, I promise you it will be better. It’s just a change of perspective that needs to happen.

[00:12:36] Dara: In terms of implementing GA4 we’ve actually got a framework that was developed in-house here at Measurelab by George who joined you on the podcast to talk about it, so this is our PIVOT framework. So I think it was episode seven that George joined you, Dan. I was away and you talk through the PIVOT framework for implementing GA4, this is something where we’re practically using now with our clients. So probably a good opportunity for us to recap PIVOT and talk through the, well summarise the steps I guess.

[00:13:06] Daniel: Yeah, for sure. The PIVOT framework has been really handy . Actually and it’s got a bit of love from our clients and staff and random people on LinkedIn as well so that’s really nice to see some positive feedback. So it works and the PIVOT is just an acronym and it stands for plan, implement, validate, onboard, transform. And so it’s just like any of this, take it with a pinch of salt, but it’s a good framework to think about your implementation and transition to GA4. So the plan step is because quite often we see people jumping in without even thinking about it. This is not a Classic to Universal Analytics upgrade where everything stays the same, pretty much with an additional feature. This is a different product that you’re implementing here. So having a good plan and idea of how it works before you go in is essential. The implementation phase kind of speaks for itself, kind of get the tracking live and there’s all sorts of nuances there especially across Android, iOS and web will have their different nuances.

[00:13:52] Daniel: Validate is an awkward one because you need to validate that it is working however, with gaps in data from unconsented users and Google Analytics Fours new modelling techniques, they’re layering in which Universal Analytics doesn’t have makes it quite difficult to do. However you can validate certain aspects, especially top level, page views, sessions, users, those kinds of things. So I would highly recommend spending a bit of time in the validation area, even though you can’t get a hundred percent validation, you’ll have to get it within the threshold that you’re happy to accept.

[00:14:20] Dara: It’s an understanding isn’t it, it’s validating within the limitations, and probably more importantly it’s getting it to a point where everyone in the business is using the data, understands it to a point and understands maybe where it’s different from previously collected data.

[00:14:34] Daniel: Which leads perfectly into the O for the onboarding and the onboarding we mean within your organisation onboarding the product. Because through that, as you said, Dara, through the validation process, there’s differences in the definitions between sessions and users and things. So understanding the difference there when you’re validating, but the onboarding is then embedding that. So it’s about training, it’s about support, it’s about documentation. It’s making sure people know what they’re looking at, how to log in, how to get the data they want to get. If you built a data warehouse off of a Universal Analytics, can you onboard GA4 as an additional source within that warehouse? Can you add it to your kind of business as usual processes, day-to-day tasks? Is it a tool that can be accessed by the same people or different people? Is this a good opportunity to reset and rethink who has access and why, those kinds of things.

[00:15:16] Daniel: Finally the transform is kind of leaning into the strengths of GA4, at least the bits that GA4 goes above and beyond Universal (Universal Analytics). And it’s then looking at transforming what you have using that data. So that is including things like the BigQuery daily exports and sometimes the intraday or the streaming export as well, and then how can we pull that backwards and forwards from our CRM transforming the data within Google Analytics, but also activating outside. So not just through the Google platforms with the conversions and the audience sharing capabilities. But externally to that, can we connect that into the business, can we transform our data sets elsewhere. So it’s a bit broad, we have details on each of those steps, but broadly speaking, it’s a really good framework to say, have we planned, have we implemented? Have we validated? Have we onboarded? Have we started thinking about transformation because as always, that last point is that business as usual, right? That is the reason why you’ve got GA4, that’s the bit that’s going to be built into the day-to-day.

[00:16:06] Dara: Yeah as mentioned earlier as well, it’s detailed on our blog and we can share a link to it in the show notes and also it was discussed in detail on episode seven where George, the creator of the PIVOT framework joined Dan and talked through it.

[00:16:19] Daniel: Yeah great, and just to shift gears slightly, I just wanted to touch on the export again. So in Universal Analytics, a lot of time has been given to exporting the Universal Analytics data, or what do we do with Universal Analytics data? How do I get potentially 10, 15 years worth of historic data out of this tool before potentially it gets removed, deleted, access is revoked or whatever happens. Let’s say in the strictest of situations on the 1st of January 2024, there won’t be access to any of this data. Obviously it’s a, from six months in the wording they gave us and we don’t know what that means, but let’s just assume worst case scenario. 1st of January 2024, we won’t have access to any of the 10, 15 years worth of historical website data.

[00:16:59] Daniel: So there’s a couple of things I wanted to highlight. So first of all, again, don’t worry, don’t panic. This is not something we have to figure out, even start thinking about until at least the 1st of July next year. And again, as you said, Dara, hopefully we’ll have a bit more clarification what at least six months means. There might be solutions that mean we don’t have to worry about this at all. There might be solutions, they might say actually, yeah, six months get to it in which case we have six months, which is plenty of time, but there’s a couple of things that I’ve noticed that a lot of people don’t really take into consideration.

[00:17:26] Daniel: So first of all, the biggest thing is the data retention period or the data retention policy that’s built into Google Analytics. So in GA4 the default is two months, the default data retention period is two months and you can optionally set that to 14 months. In Universal Analytics you can optionally set it to do not expire, which means it never deletes data however, the default is 26 months. So that was just a bit of context of what this feature actually does because it sounds quite severe, it sounds like it deletes data after 2 months or 26 months or 14 months. It does, but what that means is it deletes the raw underlying data set, it doesn’t delete your data. It doesn’t delete the daily summary aggregate data. So in Universal Analytics and GA4, it’s the same feature. This is not a new GA4 feature, the only difference is the windows.

[00:18:08] Daniel: So what this means, let’s say you’ve got the 26 month window set the default in Universal Analytics. After 26 months of your customer data, not the customers or users even last 26 months in modern technology. But after 26 months, the raw hits level data is deleted, so that is the page views and the events. What that means is you can’t then access those for doing things like Segments and Audiences and any kind of deeper analysis. It doesn’t delete the totals, so total sessions per day, users by day, conversions by campaign, revenue, transactions, goal completions, this data is never deleted.

[00:18:42] Daniel: I’m always going to classify this as you’ve got two types of data in GA (Google Analytics), you’ve got your aggregate summary data, everyone has that, that’s never deleted. And then you’ve got your detailed level, hit-level data, which depending on the data retention window you have a rolling window of X amount of months worth of that data.

[00:18:57] Daniel: So first of all, with the aggregate summary data, you can use the API to pull that out into a Google Sheet, Data Studio. You can build your own pipelining tool using apps scripts, or you can do something like a funnel or Stitch or Fivetran. Any of the tools out there you may have heard of, you can use any of those to connect to the API, pull that data out. It might even be fancy and do it in batches so you can export all your historical data. Again, not something we have to think about now, but there are hundreds of tools out there that can do this for you come the 1st of July or beyond next year. The other side is that detailed level data.

[00:19:27] Daniel: So if for some reason you would like access to the raw data, you might be able to access that. First of all, I didn’t caveat this we’re talking about the free GA (Google Analytics) users here. If you’re on 360, you have access to the BigQuery export in which case use that. This is a silly way of accessing that data If you are 360. But on the free version of GA (Google Analytics), there is a recommendation that we followed in terms of best practice, and this is actually from an article from 2015 can you believe? Recommending on four custom dimensions to use as best practice. Implementing those four custom dimensions is the key to exporting this raw hit level data, and those four custom dimensions I’ll link off into the show notes, by the way, all of the links we’ve referenced today, we’ll put into the show notes, but the four custom dimensions are client ID, user ID, session ID, and hit ID. By implementing these four custom dimensions that are pretty straightforward actually in tag manager, there’s some copy paste stuff in there for you to do that means you can still use the API, but you can export all of those raw events and pages out from the data. Again, using the API, you can pull them into a sheet, data warehouse, BigQuery using Stitch, Funnel, Fivetran, your own script it’s entirely up to you.

[00:20:32] Daniel: So I know I’ve spent a lot of time talking about this now, but two types of data available in Google Analytics, your summary data, that’s your aggregate data. That’s by day, by campaign, that’s your sessions, users, transactions, conversion rates, that kind of data will never be deleted. You can export that, everyone can do that. If you want access to the raw data, you need to have these custom dimensions in place first. So if you don’t already have them, get them done now and then this time next year, you can then export that data.

[00:20:57] Daniel: If you already have them in place, it then depends on your retention window. So if for some reason you have a two month retention window, you only have access to two months of that data. If you have a 26 month retention window, you have 26 months of that data available to you. So check your data retention window, check to see if you’ve got these four custom dimensions set up if you would like access to this raw data. If all you’re going to be doing is aggregating up to daily totals in a Data Studio dashboard anyway then it’s probably not worth your while, not worth the time, effort and money it will take to export and then store that data permanently. In which case you’ve got access without having to do a single thing to those daily totals. Did I explain that well enough Dara? Is that pretty clear?

[00:21:35] Dara: I think so. I think to summarise it’s all about whether you need that raw access to that raw data. If you do then get those four custom dimensions and check your data retention is set to be long enough to make use of that. If not, don’t worry about it and you’ll just get the aggregate data out through your choice of Funnel, Fivetran, whatever your tool of choice is.

[00:21:56] Daniel: So I appreciate this is a one-way communication channel. My LinkedIn profile is in the show notes or my email address as well. If you wanted to just reach out and have a quick chat about what I actually meant and what you need to do, happy to chat, I’m happy to advise. I think this kind of stuff is slightly nuanced for every implementation. What we said about is the broadest setup if you want this, then go do these custom dimensions, but there might be nuances there. So if you get it, great, there you go, all the resources are in the show notes. If you’re unsure, or if I am most likely just not explaining it very well, then just hit us up on LinkedIn or email and I’ll try and do a better job of explaining it real time.

[00:22:31] Dara: Somewhat linked to something we said earlier about looking at this as a chance to review the data you’re collecting. Maybe not quite start from scratch, but start with a fresh pair of eyes and look at what you’re collecting and how it’s being used. In the same way when you said about having 10 or 15 years of data it made me tense up a little bit, and obviously there will be people who are going back that far and maybe if it’s a very established website or app, whatever is being tracked, and it hasn’t changed so much over time that it’s made that completely irrelevant to compare, but by and large, I think going back anything beyond probably two or three years, and this is even bearing in mind the last two years of course are skewed because of COVID. But going too far back there’s probably not that many use cases for most businesses to go back and do any kind of analysis or any comparison against four or five, six years ago. So obviously this would be a big decision to make, but if Google don’t provide a way to continue to access that UA (Universal Analytics) data, think about how much of the historical data you actually need. You don’t necessarily need to pull all ten, fithteen years of your GA (Google Analytics) account. If you know you’re not going to use it then you’ll make the job easy for yourself.

[00:23:41] Daniel: Yeah, you’re quite right. It’s like a comfort blanket, people would like the fact that it’s there, even though they’ll never actually need to use it. And I think this is just putting that into the spotlight a little bit and they’re becoming a bit uncomfortable, just like you are actually, I could see it on your face as we were talking about it, but it’s like all of a sudden, it’s almost like your entire record of how well you’ve been doing as the marketing manager or the e-commerce manager or the website owner is going to be gone, but actually there’s no need to have it in the first place, but you kind of liked the fact that it’s there. This kind of conversation comes up a lot, actually, as we do what we do Dara. It’s a lot about whether or not it’s important, you having it in Google Analytics or not, or even having it at all. If you think about where Google positions the products and it’s a marketing product, it’s then the Google Marketing Platform, the intention of Google Analytics is built around the idea that you can action your marketing data, measure the performance of your marketing campaigns and kind of do something with that.

[00:24:29] Daniel: Even if you think about something like refunds. I have the same conversation with clients about refunds. Yes, of course refunds are important, but because Google Analytics is not a financial record keeping system. What’s the point If it can’t be actioned through your marketing campaigns, and let’s say someone refunded something two weeks later, if that doesn’t change any decision you would’ve made on your marketing campaigns at the time, what’s the point of that effort and the money and the time it takes to get this feed set up.

[00:24:52] Daniel: So I always have to ask myself, is it important enough to keep in Google Analytics or actually, is it not? The same thing is the same with Google Analytics data itself is, do I actually need this data in my dashboard or in GA (Google Analytics). Let’s say there’s a magical situation where Universal Analytics have a way of getting that kind of aggregate data into GA4, would that be better or would you just feel better about it? Is it a nice to have, or is it actually going to be fundamentally different to the way you use the product. It’s probably no different and it’s probably not going to change the way you use the product, and it’s definitely not going to change the way you run marketing, right? I don’t think, and I can’t speak for everyone, but for the majority, I don’t think it’s going to make a difference. I think again, it’s that comfort blanket of like, I like to have my refunds in GA (Google Analytics) although I can’t take the numbers at face value because it’s not the right number, but also I never use it, it’s kind of like a vanity project, and I think this feels like one of those.

[00:25:39] Dara: I think we’re pretty close to wrapping up for this conversation around it. I’m sure we’re going to talk about this more, especially if there’s more clarity provided from Google about what’s going to happen post January 2024. A final point around, and this goes back to your apology at the beginning. The six weeks was turning the screw a little bit too much, but we were having a conversation internally today where George who worked on the PIVOT framework estimates and obviously it’s different depending on requirements and individual cases, but it could take 12 weeks to do a comprehensive GA4 implementation and we’re basically 12 weeks away from that 1st of July 2022 date, which is when you would want to have GA4 implemented to a good standard to allow you to have that full year of GA4 data in parallel to UA (Universal Analytics) data when the 1st of July 2023 comes around. So there is an urgency, if you don’t have GA4 set up currently, or if you have it set up, but it hasn’t been configured correctly, it really does need to become a high priority to make sure you’re at a point in July this year where you’re happy enough with the GA4 implementation bearing in mind you’re going to be relying on that data over the next year.

[00:26:53] Daniel: Yeah, absolutely. Don’t worry about Universal Analytics, don’t panic. We’ve got over a year to figure that stuff out, but do focus your time, energy, attention, on GA4 now. Right now it’s all about the plan, implement, validate section of the PIVOT framework. I think we can think about onboarding, so the training, the education, the upskilling, the comfortability using the product, I think all of that can come over the next year, there’s no rush for that. But getting it ready so that you have parity that year and your data is important that you have a plan and implement it against that plan before July the 1st this year.

[00:27:25] Dara: Okay I reckon let’s leave it there on this hot topic for now, but almost certainly to be continued. So what have you been doing outside of work lately Dan to take your mind off the urgency of GA4.

[00:27:39] Daniel: I went to the cinema, I went to see The Batman and I highly recommend anyone to see the Batman. Any question marks about Robert Pattinson being Batman, I think are completely gone. I think he’s awesome, he’s a wicked batman. And the film just from a visual perspective is so beautiful. Like you could take a screenshot at any moment and it can be like a painting on a wall. It is such a lovely film, the story is awesome too. It’s still a Batman film, so there’s still some odd, you know, not cartoony, but like comic elements to it that you can’t avoid, but it is a darker, grittier, brutal version of it. It’s beautifully shot, the actors are amazing. If you get an opportunity to see it before it comes out of the cinema, then I recommend it. If not, I’m sure it’d be on the streaming soon.

[00:28:18] Dara: I haven’t seen it, but I saw friends for dinner the other night and they said they liked it, but they felt that there was too many characters wedged into it that it could have done with maybe a little bit more detail on a fewer number of characters.

[00:28:32] Daniel: Yeah, if you’re into Batman, I’ll say into if you’ve seen even the other Batman films, you’re okay. I think if you’re fresh into this, you’re like, there is a lot of people. I thought it was good because it doesn’t assume you’re an idiot because this is a, what they call a year two film. So this isn’t an origin story, but it’s also not old man Batman. So he’s basically a new Batman, they’re not going to bore you with another origin story, kind of jumps you straight in and you’re just like, yeah okay I get this. It’s like, how many times do we need another Batman or Spiderman or Superman origin story? I think we will get it by now right? And it’s really well done.

[00:29:01] Daniel: All right, Dara, what have you been up to?

[00:29:03] Dara: Well my updates lately have been very non-active so I’m happy to say I’m a bit more active again lately. I mean I always run, but I kind of go through phases where it’s just a little versus a lot. So I’m getting my training back on track. I’ve got a half marathon coming up in the summer and then a full marathon, hopefully towards the end of the year. So it’s getting me out there as the weather’s starting to get a bit better, which is nice, and it keeps me out of trouble, so it’s good.

[00:29:29] Daniel: Awesome, that sounds good, sounds good. I bet getting those marathons booked in now as well is a motivation enough of like you’re setting yourself a deadline, you have to get ready for it.

[00:29:38] Dara: Yeah and it’s less Netflix marathons and more actual marathons, which is probably a positive change.

[00:29:46] Daniel: Awesome well, looking forward to the update when it comes close to the day.

[00:29:49] Dara: I’ve said it here now so I’ve kind of made a public commitment.

[00:29:52] Daniel: Exactly, that’s assuming anyone listens to this far, but let’s assume they all do.

[00:29:57] Dara: I might be safe. Okay, that’s almost it from us, but quickly before we go, Dan, where can people find out more? I mean, you mentioned this earlier, but just to reiterate, where can people find out more about you?

[00:30:07] Daniel: LinkedIn is the best way, it’s the only social of platforms that I’m present on, and also my blog so dananalytics.co.uk, all links are in the show notes. What about you, Dara? Where can find you?

[00:30:18] Dara: LinkedIn is best for me, look me up if you want to reach out to me, LinkedIn is the best way to find me. Okay that’s it from us for this week. As always, you can find out more about us and you can even find all of our previous episodes if you miss the first time around, or if you didn’t miss them, but you want to listen to them again. You can find them at measurelab.co.uk/podcast. If you want to suggest a topic, or if you want to come and join Dan and I on The Measure Pod to have a chat about your chosen topic, then best thing to do is to find one or both of us on LinkedIn and just let us know, but you can also email podcast@measurelab.co.uk. Our brilliant theme music is from Confidential, links to their Spotify and also their Instagram are in the show notes if you want to check them out. I’ve been Dara joined by Dan, so it’s a bye from me.

[00:31:04] Daniel: And bye from me.

[00:31:05] Dara: See you next time.

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Daniel is an Analytics Innovation Lead at Measurelab - he is a trainer, podcaster and overall fanatic. He loves getting stuck into all things GA4 and anything new and exciting.

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