#15 When is GA not the answer?
This week Dan and Dara discuss various situations when GA is not the answer. Whether it’s navigating gaps in data collection, or forcing some types of data analysis that just doesn’t work.
The Google Analytics for Firebase upgrade to Google Analytics 4 has until the 15th February 2022 before data is deleted, and 17th January 2022 before new data stops being processed https://bit.ly/3CLTF2u.
The announcement of Google Ads Performance Max campaign rollout and update for local and shopping campaigns early 2022 https://bit.ly/3k0lgph.
In other news, Dan plays another game and Dara sees Dune!
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Transcript
[00:00:17] Dara: Hello, and thanks for joining us in The Measure Pod, a podcast for analytics enthusiasts, where each week we pick an analytics topic, we dive in, it could be a challenge or an opinion, and we try to have a little bit of fun along the way too. I’m Dara, I’m MD at Measurelab. I’m joined as always by Dan, a Lead Analytics Consultant at Measurelab. Dan, what’s new in the analytics world?
[00:00:41] Dan: Hey Dara. So there’s two things I brought in this week. The first one is an announcement from Google Ads that they’re now rolling out something called Performance Max campaigns worldwide. So this is something they’ve been testing for a little while. What Performance Max is, and I’ll put a link in the show notes, but what it basically means is a single campaign that can roll ads out across all of the networks that Google has. So whether that’s the discover, maps, YouTube search, shopping, whatever that is. It’s probably an easy way to reach a lot more people. And it’s probably an easy way for them to make more money there’s the long and short of it. They also noted that shopping and local campaigns, are actually automatically upgraded to Performance Max campaigns as of next year. They always update things like new campaign types, but I feel like this is slightly bigger and pushing more towards this kind of automation across all networks and just letting Google figure it out.
[00:01:31] Dara: This won’t be the only option available, this will just be a choice, right? You could still pick and choose as you can now, you don’t have to use this, or are they going to, do you think they are going to move to a model where this is the way it works?
[00:01:42] Dan: One would imagine you can still keep all the old campaign types. Even if they do do that, it will be a slow process of moving all these campaign types, but that the two that they are moving, or sorry upgrading, to Performance Max are the local campaigns and shopping campaigns. So I think that is the end of those dedicated campaigns. And there’ll be merged into this Performance Max campaign type. Where I’m reading into this is things like Shopping campaigns are going to be across all Google network. So you might see product placement ads across maps, YouTube, discover, search, and everywhere else. It’s now going to be kind of ads everywhere, whether it’s for a website, for an app, a store or a product.
[00:02:19] Dara: It’s quite a big deal, this one.
[00:02:20] Dan: Yeah, I think so. I think so. It feels bigger, that’s why I thought I’d mention it on the podcast. So the second one is slightly different. So we’re now going to go into the Firebase world. We got an email from Firebase, basically saying that if you haven’t or if you don’t upgrade your Google Analytics for Firebase to a GA4 property, you’re going to lose access to all of your data as of the 15th of February next year. It feels again, a big deal. You don’t have to do much, right. It’s just accepting the terms and conditions. But what that does in the backend is that formerly turns a GA for Firebase instance into a GA4 instance, and it gives you access to the GA UI. If you don’t do this, you have the data deleted in GA for Firebase. You won’t be able to use any of the data within Crashlytics, Remote Config, AB testing, in-app messaging. So it feels like a small thing to do, just go in and accept and get access to a GA4 property. But actually, they’re kind of taking that quite seriously and saying, you need to upgrade to GA4 by the 15th of February, or we’re just going to switch it off. It’s what most app devs have done already, because there’s been banners across the top of the screen every time you log in. So hopefully everyone would have done it by then.
[00:03:32] Dara: Right, that’s some chunky news this week, but let’s get onto our actual topic of discussion this week. So what is it we’re going to talk about?
[00:03:40] Dan: This week we’re going to talk about when is GA not the answer. So we’ve done an awful lot thinking about when GA is the answer, I think it’s about time that we discuss when it falls a bit short, when it can’t be used to answer certain questions.
[00:03:54] Dara: I don’t understand GA can do everything.
[00:03:56] Dan: Spoken like a true Google Analytics consultant Dara.
[00:03:59] Dara: One who swears that it more than anybody else. So yeah, no I do, certainly do know the times when GA isn’t the answer. So this is a good topic, let’s get stuck straight in. So when isn’t GA the right thing?
[00:04:10] Dan: Well, to kick things off, I think we’ll probably start with the difference between quantitative and qualitative data or data analysis. I think Google Analytics is really, really good at telling you how many times something’s happened, but it doesn’t really tell you why. This is the difference between a tool like Google Analytics saying 10 people visited this page and moved on to the next page. Whereas something qualitative like survey data or feedback forms. Or even something like SessionCam or Hotjar that are doing heat maps or session recordings would give you a bit of context of why they move to that next page or how many people didn’t and maybe what caused that drop-off?
[00:04:48] Dara: Do you remember the click tracking that was in GA? It was terrible, never really worked that well.
[00:04:53] Dan: Yeah, and it created some weird kind of boxy heatmap
[00:04:57] Dara: Yeah, and it was really clunky. It didn’t actually have a heat map, it was just like an overlay of the page with the click data on it. But there was a problem initially where if there was two links to the same destination page, it would give them both the same percentage.
[00:05:10] Dan: And then they moved it out of the UI didn’t they, because they had some Iframe of your website in the UI you who clicked through to. And then they pulled it out as this, I think it was a Chrome extension I think they moved into. And then who knows? I actually, I have no idea if it’s still there.
[00:05:25] Dara: Which only goes to further prove your point, that GA is for quantitative data analysis or not for qualitative. And that’s where you’re better off using something like Hotjar or SessionCom to get that. And the two work really well together. This that’s probably worth stressing as well. It’s not like saying in that situation GA’s redundant because actually the two work quite well together and you can overlay the two data sets.
[00:05:49] Dan: Yeah exactly, and extending that into things like survey data I mentioned. Let’s say you’ve got a contact form on your website. And in GA you might be tracking how many forms, submissions have happened, maybe how many errors or what happened throughout the form, but nothing around that tells you whether they’re giving you good feedback or bad feedback, or whether they’re really fed up or having a great time. So the thing that the qualitative data gives you is that kind of sentiment, emotion, where that tells you why something’s happening. Whereas Google analytics would just say five things have happened. I always like to think of it as glorified counting.
[00:06:22] Dara: Yeah, I always like to think of it as, GA will tell you if there is a problem and maybe where that problem is, but it won’t tell you what the problem is. And that’s where survey data or Hotjar or something like that will actually give you that extra often most important answer, which is why this isn’t working. Or why this is working and then you want to do more of it.
[00:06:43] Dan: Yeah, exactly. Speaking of different datasets, I think that kind of ties neatly into another area where GA is not the answer. I see this time and time again, working with different companies of all sizes. And trying to align Google analytics to some kind of stock system or finance system. So we always do this when we’re validating things like revenue from an e-commerce website, for example, and understanding that, you know, 5 to 10% difference is completely fine. Trying to fight that battle to align revenue in Google Analytics against a finance system is just an uphill struggle that you’re never going to win.
[00:07:15] Dara: Uh, you’re giving me the heebie-jeebies. I’m thinking of a similar conversation that happens again and again, which is comparing sessions with clicks. I cringe every time cause it’s a difficult conversation to have, and basically it’s a similar principle, isn’t it? It’s not trying to compare two different systems that report in two very different ways. And particularly in your finance example, it’s like you’re comparing the actual truth to a slice of that truth or a, or a version of that truth
[00:07:41] Dan: And the obvious example is things like refunds. There are ways of accounting for refunds in Google Analytics, but in most cases where I’ve talked to companies about accounting for refunds in Google Analytics. I always kind of start asking what would the benefit of having refund data in Google Analytics give you. Because if you are activating the data from GA, if you’re pushing that into audiences or remarketing, it’s kind of real time or very quickly after the fact of it happening. Let’s say someone refunds a product, they got two weeks after receiving it. Does that change a decision that you made back then? No, cause you didn’t even know it will get refunded. It just feels a bit unnecessary to try and fight this battle to automate and systemize and synchronize Google Analytics with these systems.
[00:08:22] Dara: Well, exactly. Cause it’s still going to be wrong, it’s just going to be less wrong. And you’re right, I think it’s about remembering what GA is for, it’s for trend analysis. And it’s for marketing trend analysis, so marketing teams aren’t typically gonna report on final completed sales. They’re going to report on conversions and transactions. It makes me think of this kind of idea of people maybe thinking GA can do everything, or is the place for everything. Something I’ve seen a lot and I’m sure you have too is where people try and shoehorn data back into GA, just because you can. And in some cases it works really, really well and it’s really necessary. But in other cases, people try and push data back into GA just because the option is there. Um, and if that data exists in a CRM or if it exists and nowadays probably it would exist in BigQuery and you can much more easily get the GA data into BigQuery or into your CRM. And then use all of that additional data that you have on your customers or on your products or whatever, as opposed to trying to kind of shoe horn a piece of it into the limited way of getting that data back into GA.
[00:09:27] Dan: It’s just about knowing where the data needs to be. And in most cases like that, especially with things like offline data. Call tracking, as an example, is always one that has a lot of systems that integrate automatically with Google Analytics and uh, face value, that’s really interesting and really useful. But actually it causes a lot more problems than it’s worth, or at least from my perspective that it’s worth. And actually that is the kind of data that you can align in a data warehouse. Give me my call data, I’ll pull that into my data warehouse. I pull the GA data in there, pull the CRM data, the ESP data, and then align it all there. And I think that is a perfect system or a perfect place rather to do that kind of data joining and analysis. Google Analytics is a website tracking tool. And the thing about Google Analytics is it tries to turn everything into some kind of online activity. There’s no such thing as an offline event within Google Analytics. So there’s no offline session, there’s no offline user. If you’re sending data into Google Analytics, it tries to then create the concept of a session and a user. And if there’s no user ID, then it creates a new user. And if there’s no session that we might create a new session. What happens then is if you start reporting just total users and total sessions, you’re going to get this weird set of skewed data. One thing to note on that actually though Dara, is that Google Analytics 4 is a bit more agnostic when it comes to this kind of data. You can just throw events into GA4 and it doesn’t really care if it’s online or offline.
[00:10:51] Dara: I was wondering how long it, would take you to say GA4 is the answer.
[00:10:55] Dan: Going to create some kind of bingo card or drinking game off the back of it.
[00:10:58] Dara: I think you ,definitely owe me some money anyway. Another this, uh, it’s going to say it’s an edge case maybe it’s not actually so edge. But we have had conversations with people before where they’re basically high volume websites, so they’re big traffic websites, but they don’t necessarily need the extra features that GA360 offers. So it might be, for example, that if they’re one of those few companies that have the luxury of not doing lots of advertising, or at least not lots of advertising on Google, but then they don’t benefit from the integrations with the Google ad platforms. If you just are a high traffic site, you may not want to use GA360, cause you might not want to pay the price just to be able to track more data. And in that case, you might want to go down a different route and actually look to user a different analytics tool.
[00:11:49] Dan: Yeah, that’s a really good point. We’ve definitely had those conversations with clients over the years, and it comes as a bit of a surprise or a shock when they find out how much GA360 is, when a lots of people, it might even be fair to say most people. When they start using GA they’re using the free version, and there’s almost this expectation or this understanding that it’s free, and it’s not just a free tier of a paid solution or a full enterprise level solution. And so just for the sake of having more than 10 million hits a month, all of a sudden you might get contacted to start paying the cost of GA360, which probably has never been budgeted for within the organization. And then they’re like, well actually, I don’t need this. They then have to make a decision of is GA worth this much money to us. Do we invest in it, the people or whatever to make the most of this to consider when are spending this amount of money on a tool, or do we find a different tool? And there’s plenty of other tools out there that do that.
[00:12:47] Dara: I’m going to steal your line. GA4 is the answer.
[00:12:50] Dan: It can be, yeah. W w why Dara? Go on, this is testing you now. Why GA4 an answer?
[00:12:55] Dara: Because it’s the best at everything. It’s newer, therefore it must be better. Now because you don’t have the limitations on data collection that you do with GA3. Is that what we call it? Universal Analytics.
[00:13:08] Dan: I think the GA3 shorthand is, whether Google likes it or not, is definitely come into the mainstream. But on the same train of thought, as that though, if you’re considering whether or not you need Google Analytics, there is always a question around whether or not Google Analytics is maybe overkill for what you need. Is it too much, is it doing too many things for what you actually need it to do? When you’re getting close to that threshold for GA360, it’s really a good time to question that of understanding. Is it worth it, do I need it to do all this stuff? What Google analytics does is data collection on your website and then processes all that data. It aggregates it into different ways and it creates this UI, this visual platform for you to interrogate with an API as well, that you can pull data into Data Studio or Tableau or whatever you’re using. But let’s say, and this is situations we’ve come across before, but let’s say you don’t need that. Like, I’ve got my own way of aggregating data. I just, I just get the raw data route through maybe a big query connector or some other way. And I reprocess my data my own way. And I’ve got Looker, or some other tool that is kind of like replacing the UI element. And I don’t need the connectors to the ad platforms either, I’ve got that sorted elsewhere. So if I’m just using GA as a data collection tool, it’s overkill, it’s doing too many things. It’s kind of bloated with this extra features that you don’t need. And so why not just do your own data collection. Pull the data directly into a BigQuery data warehouse. You don’t need to go through this whole machine, this mechanism that also brings things up around like data storage locations. You know, it’s all stored all over the world across Google data centers from GA. Whereas let’s say I needed it to be stored in the EU or the UK. If we created our own way of doing that, then we have full control where we store the data, how it’s collected, how we process it, how we aggregate it. So a bit of a rambly one I think actually, but it’s around just GA. Is it overkill for what you need? Do you need more control? Is it doing too much? In which case then maybe you just do the one thing you need and sack off all the other stuff that you don’t need.
[00:15:03] Dara: Well, it’s almost like it’s either in this, in these kinds of scenarios, it’s either overkill or under kill. So it’s either doing lots of things that you don’t want it to do, or it’s not allowing you to do enough with it in the case of if you wanna have a really customized data collection. And it’s the benefit, and I guess the drawback of something like GA, where what they’re going for is wide adoption. So it’s meant to be a, almost like a one size fits all. Which means for people with very specific use cases and needs, it’s probably not going to be quite right. Whereas it’s going to work for the vast majority of website.
[00:15:40] Dan: Yeah, they just care about making it work for the 95%. And that’s where they probably stop optimizing for.
[00:15:45] Dara: Well, Yeah, exactly. And that’s actually a good way of putting it, because it’s almost like w to answer our question of when is GA not the right solution, it’s a probably if you’re in that 5%.
[00:15:55] Dan: Yeah, that’s a really good point. Um, and, and there’s, we don’t always have to choose another tool, right? It was saying before you can just build it yourself, collecting data, um, pushing it into a data warehouse. There’s loads of open source stuff for you to build this yourself. I mean, even if you go back in the days of web logs. Collecting data from your website has never been a marketing tool’s job. There are lots of different ways of doing that. Google Analytics comes with bells and whistles, and if that’s what you’re after then great, use those bells and whistles. If that’s not enough, it’s not giving you what you need. Why make do, why settle, why, why keep using it? Um, so I think, you know, this overkill under kill scenario is definitely a good point to think about when GA is not the answer. Is it too full of features you’re never going to use, or does it not have enough features, image, case, try and find a tool or build a tool that does.
[00:16:40] Dara: Okay, I think that’s a nice natural conclusion. So, what have you been done to relax outside of work Dan?
[00:16:50] Dan: So recently I bought Far Cry 6 and I have just left it unplayed since it came out. I got it on the pre-order and just never turned it on. So I finally switched it on, I’m in for the ride. I’ve been playing every morning, every evening, and I’ve been a bit obsessed actually. But it’s a really good game, it’s not groundbreaking. If you’ve played any of the other Far Crys, it’s just another Far Cry. But that’s quite all right in my eyes. I like to stick a podcast on and shoot some people.
[00:17:17] Dara: I’m holding out for number seven.
[00:17:18] Dan: Oh, is that it is that your foray into video gaming is going to be from what was that game called again?
[00:17:23] Dara: Flimbo’s Quest.
[00:17:24] Dan: Flimbo’s Quest to Far Cry 7.
[00:17:27] Dara: Best, best game ever. You can’t improve on Flimbo’s Quest.
[00:17:30] Dan: Alright, how about you Dara. What have you been up to this week?
[00:17:33] Dara: Well, I’ve got an update, and it’s not snake related this week. I said I was going to try and read Dune before watching the film. And I think when I said that, I didn’t realize that the film was very, very soon about to come out. Um, so I’ve actually seen the film. So I only, I only probably got a chapter into the book and then I went and saw the film. But it was brilliant, so, so good. I really, really enjoyed it and I can’t wait for the next one. So I’d recommend it to anyone.
[00:18:02] Dan: Amazing. Are you going to continue with the book now?
[00:18:04] Dara: I ah, I don’t know. I’d like to, yeah, I would like to. But I sometimes feel like if I don’t read the book first, I’m not likely to read it after seeing the film, but we’ll see. I, I plan to, but we’ll see what happens.
[00:18:18] Dan: Well, there’s 21 books, right? I think there’s 21 or around 20. I don’t know if they’ll ever get to doing the 21 films, so you could always read the second book in prep for the second film.
[00:18:26] Dara: Or just jump to book 21. Alright, that’s a wrap for this week. You can find out more about us as usual over at measurelab.co.uk. Or you can get in touch with us via email at podcast@measurelab.co.uk, or just look us up on LinkedIn. And please do ask us any questions or suggest a topic or better still, if you want to come on the show and discuss a topic, something that you feel strongly about, please let us know. Otherwise, join us next time for more analytics, chit-chat. I’ve been Dara, joined by Dan. So it’s bye from me.
[00:18:58] Dan: And bye from me.
[00:18:59] Dara: See you next time.
Daniel Perry-Reed
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Further reading
Customer Data Platforms (CDPs)
Grand Designs: “The Warehouse to CDP conversion”
