Episode 22: Where Does Analytics Fit Into a Marketing Strategy? | With Dara Fitzgerald

Tuesday, February 7, 2023

How much attention should you be paying to your analytics? And how should analytics be best utilized as part of your marketing strategy? That's what we're discussing today with a man who's been working with Google Analytics for 15 years. And over the past few years, he's consulted, trained, and spoken at conferences about how to optimize your use of analytics.

Podcast 21 Minutes
Where Does Analytics Fit Into a Marketing Strategy? | With Dara Fitzgerald

His focus now is on his business, Measurelab, to become the world's favorite Digital Analytics Consultancy. A warm welcome to the Strategic Marketing Show, Dara Fitzgerald.

[You can find Dara over at measurelab.co.uk.]


Watch the episode via your preferred pocast platform:

Topics discussed on this episode include:

  • How has the role that analytics plays in the marketing technology stack changed over the past few years?
  • How should non-technical marketing professionals interact with analytics?
  • What ongoing relationship should senior, general marketers have with analytics professionals?
  • What are the key tracking opportunities and metrics to be aware of?
  • Analytics platforms can seem complicated - is there an easy way to take key data out of analytics platforms and display them in an easy-to-access way?
  • How are analytics platforms continuing to evolve?

Full transcript:

David Bain  00:50

How much attention should you be paying to your analytics? And how should analytics be best utilized as part of your marketing strategy?

That's what we're discussing today with a man who's been working with Google Analytics for 15 years. And over the past few years, he's consulted, trained, and spoken at conferences about how to optimize your use of analytics.

His focus now is on his business, Measurelab, to become the world's favorite Digital Analytics Consultancy. A warm welcome to the Strategic Marketing Show, Dara Fitzgerald.

Dara Fitzgerald  01:22

Hi, David. Thanks for inviting me on. I'm very happy and excited to be here.

David Bain  01:26

Hey, Dara. Well, thank you so much for coming on. You can find Dara over at measurelab.co.uk. So, Dara, how has the role that analytics plays in the marketing technology stack changed over the last few years?

Dara Fitzgerald  01:40

I think I have to start probably with what's front and center for a lot of users of Google Analytics at the moment, which is the pending sunsetting of Universal Analytics - which is the version of Google Analytics that we've known and loved for the last several years.

In March of this year (so March 2022), Google announced, in quite a big announcement, that they were actually going to sunset Universal Analytics because all of their focus was moving to Google Analytics 4, which has been around for a number of years. But, it was quite a shock to people when they realized that Universal was actually going to get discontinued.

Companies now have until July 2023 before Universal Analytics stops collecting data, which is quite a big deal because Google have never done such a big change before. Whenever they've changed Analytics in the past, it's always been - maybe not superficial as such, but it's kind of kept the infrastructure in place, so nobody has had to worry too much about losing any of their historical data. But this is the biggest change they've ever made, really. This is a complete rebuild; it's an entirely new product.

In terms of how it's changed, this is maybe very specific to something that's happening right now, but I think what GA4 enables marketers to do is have a lot more, I'm going to say “power”. I keep thinking that's not the right word, but it's going to give them a lot more capabilities to actually act on their data, compared to what they would have had with Universal Analytics - which has been the tool of choice for, let's be honest, the vast majority of website owners for the last whatever number of years.

David Bain  03:25

So if you're a non-technical marketer, I guess the first question is: are we currently using Google Analytics? And if so, how is this change going to impact the data that I see?

Typically, how will that actually impact the most important types of data that all marketers tend to want to interact with and track on an ongoing basis?

Dara Fitzgerald  03:49

I think if the migration is managed smoothly, then there's nothing fundamental that will be lost during this process if it's done correctly. One of the challenges (which is something that I kind of alluded to) is that, for the first time, Google are going to stop collecting a certain type of data. And not only that, they're then going to eventually remove access to that historical data. So, one thing companies do need to make sure they're doing is exporting any historical data that they've built up over the years using Universal Analytics. As long as that's happening, then there's no reason why you can't migrate over all of your reports, all of your dashboards, that all feed off this underlying analytics data.

And then, as I mentioned, you then get some extra benefits. You're actually going to be able to have more features, and the main one being (and maybe I'm going to jump ahead a little bit here) there's actually a lot of machine learning-based modeled data in GA4, which is something that didn't exist within Universal. This is part of Google's shift towards using a lot of machine learning to work with the bigger datasets to enable people to actually use things like predictive analytics, as an example. But in terms of moving from the old way to the new way, if that migration is managed correctly, then there shouldn't really be any issues in terms of continuing to report.

In fact, actually - sorry, I'm turning this into quite a long answer, David, but something that we're saying to our clients is: something that we see time and time again, is that people layer up analytics over the years. New people joined the team, they add their own spin on things, they start collecting data that they feel is important or they've collected in a previous role, and over the years you get a lot of bloat. And nobody in the business is really sure who is using which reports, or which set of data. People can have multiple sets of KPIs that they're using that sometimes conflict with each other or people don't understand how that data is actually being collected and processed.

What we're saying to people is actually: almost flip this fact that Universal Analytics will be discontinued. Flip that into a positive and use this as a chance to actually review the data that you're collecting. Check it's still fit for purpose, and almost start - not necessarily with a fully clean slate - but start from the ground up again and think, “Well, actually, let's review what data we're using and how we're using it.” Actually start with a dataset that we're actually going to be able to use to act on, rather than just having metrics for the sake of metrics, which is a trap that's easy to fall into.

David Bain  04:29

I like you talking about the fact that a lot of marketers end up layering up data. Because what happens is, marketers get promoted within organizations, new marketers start, and they have their own preferred way of tracking things. And it ends up meaning that the old ways continue in the background - perhaps they aren't switched off, because they're too scared to switch things off in case I might break anything at all - and they are doing many things at the same time.

Which kind of leads me up to what I was going to ask you as a follow-up question. You began your answer by talking about the importance of exporting data from Universal Analytics. I just want to emphasize the importance of doing that because, obviously, you can only export so much data. So, as soon as you start exporting data, that's the point as to which you can select the data as to how far you can go back.

But, also, in relation to layering up the collection of data, would you advise for a certain period of time carrying on Universal Analytics, and GA4 at the same time?

Dara Fitzgerald  05:34

Yes, and that's what a lot of people have been doing. Because GA4 has been around for a while (I might get this slightly wrong, but it's been around for at least two years, I think). Initially, it was in beta and then it got promoted to alpha, and then the news came out in March, as I mentioned, that Universal was actually going to get discontinued.

The advice has been to run the two in parallel, which would have been the previous advice back in the day, when Google changed from, say, classic Google Analytics to Universal Analytics. You run the two in parallel because there are differences, so you take the time to understand those differences and get everybody, all the stakeholders, up to speed with what you don't have anymore and what extras you have. And when you are comparing, if there's any nuance that you need to bear in mind - because the numbers, the two datasets will never match. No two datasets will ever match. So, the advice is to run the two in parallel. 

Ideally (this is advice after the fact) that process would have started in July of this year (2022) to allow you to have a full year of Universal Analytics and GA4 data side-by-side. So, in July next year, when they discontinue Universal Analytics, you'd still have that for your year-on-year comparisons. I appreciate that not everybody has managed to do that. Some people were a little bit later, for various reasons, to get GA4 up and running. I still think there's some value, if you have Universal already running, in running the two in parallel - just so you have a period of time to compare. But really, the focus now is on having GA4 set up, fully validated, and providing the data that you're going to need moving forward because that timeline is approaching us pretty swiftly.

David Bain  07:17

Am I right in thinking that the main reason why you would want Universal Analytics and GA4 running in parallel, both tracking the same people, is that GA4 is going to spit out the data in a slightly different way? And because it's important to be able to compare and contrast the datasets to give you a better idea of how much more or less GA4 is going to report for the same sort of metrics?

Dara Fitzgerald  09:45

Exactly right. Yes. It's to give you that time to run your own comparisons, because those differences will vary slightly depending on the nature of the website and your particular users. It's worth each business looking at that in relation to their particular website, or websites, to do that comparison and basically make sure they feel comfortable that, when they have no choice but to report on the GA4 figures, that they're comfortable with those figures and that they understand what they're telling them.

For some of the differences, there are some positive reasons for those differences. One of the big features of Google Analytics 4 is that - I mentioned it using a lot of machine learning-based modeling. One of the main reasons why it's doing that is because it's trying to fill in some of the gaps that exist now. Because of the shift in the industry towards more of a privacy-centric approach, it means that the amount of observed data has decreased and is continuing to decrease, because of people not consenting to cookies, for example.

Something that Google Analytics 4 does is, if you use a feature it has called Consent Mode, it will actually model the non-consented users. It will look at consented users and it will look at their behavior, and then it will model that onto the non-consented users. It will give you a modeled view of what your full dataset looks like. So you would, in that case, see more users in GA4 than you would have seen in Universal - because in Universal, if someone doesn't consent, there's simply no data to look at.

David Bain  11:22

Now, there are many enterprise marketers, maybe listening to this recording, that won't necessarily be using Google Analytics. They could be using Adobe Analytics or something else. Are there any reasons to actually consider moving to GA4 from other tracking systems?

Dara Fitzgerald  11:38

I think there are. This might sound like a strange answer from me, given I work with Google Analytics, but potentially it works both ways. Because this change is drastic, in a way, and making people effectively start from scratch, even though they can look to export the data from Universal. Effectively, they're starting with a new product, which is GA4. That might actually make some people consider if GA is still the right tool for them.

It would be wrong of me not to acknowledge that and say that potentially there will be people out there who will think, “Well, actually, maybe now is the time to consider another tool?” But the flip side of that is, why would people come to GA4? I think there are a couple of reasons, probably. I'm not going to do a complete comparison, because my area of expertise is GA, and I'm not completely up to speed on the other analytics tools that are out there.

But I know that some of the reasons why people are pleased with moving to GA4 is, previously you could only export your data to BigQuery if you have a premium Google Analytics (a GA 360) license. If somebody is using GA4, they don't actually have to have that. Potentially, if somebody didn't need an enterprise-level analytics tool (be that GA 360, Adobe, or any other enterprise-level analytics tool) but they did want to have data warehousing capabilities, they did want to store that data somewhere where they could own it and control it, then GA4 is a really great choice because every GA4 user gets the option to export their GA4 data to BigQuery for free. The storage and the processing in BigQuery aren't free, but the export from GA4 to BigQuery is free. That's a big benefit of GA4 that doesn't exist with Universal or any other enterprise-level analytics tools.

David Bain  13:33

So that’s potentially an opportunity to maintain your enterprise-level service requirements, and perhaps actually reduce your monthly outgoings when it comes to spending on analytics.

Dara Fitzgerald  13:47

Potentially. I think one of the other reasons is the modeled data that I keep mentioning. That becomes even more useful when you're actually looking to use the audience data in GA with your advertising campaigns.

Because you can use that rich audience data from GA and you can integrate it straight into Google Ads, DV360, Search Ads 360, you can build remarketing lists and run re-engagement campaigns. You can do that with that enriched data that you have in GA4, which is a lot more difficult if you're running your ads on the Google network but you're using a non-Google analytics tool.

David Bain  14:27

You've got a client, Fred Perry, (that I'm sure many listeners will have heard of) that has fully embraced GA4. What are one or two things that they have embraced and actually been able to gain by doing that?

Dara Fitzgerald  14:42

The first one you probably won't be surprised to hear me say, because I keep mentioning this, but it's the machine learning-based modeled data. Google's using this in a few different ways in GA4. There's the modeling of the non-consented users, which is one, and that's something that Fred Perry are using. They're actually using that and - within GA, you get a choice: whether you look at the data without that modeling (for the non-consented users), or you could look at the data with that included. What they're able to do at the moment is they're actually comparing Universal Analytics with GA4 data without the modeling for non-consented users and the data with the modeling, so they can get a really good view of those different datasets and make a decision around which one that they want to use for their primary reporting.

They're also using predictive analytics in GA4, which is a really great feature. Again using machine learning, it's taking your data for your website, and it's creating audiences for things like predicted seven-day purchasers and predicted seven-day churn. It's actually predicting these behaviors. You can create audiences in GA4 using these predicted behaviors, and then actually push that into Google Ads to create remarketing campaigns or to try and re-engage those users if they're predicted to churn. It's allowing you to do that extra level of reaching these users who Google believes are going to either purchase or churn. Then you can try and push them over the line if it's in the case of predicted purchase, or you can try and re-engage them if it's in the case of churn.

I’ll just tell you another quick one, as well. GA4 also has something called Explorations. This is almost like your analysis space within the GA4 interface, and it's a lot more customizable than Universal. If you're trying to build a picture of how people are behaving on your website - you're trying to look at funnel performance across, maybe, a number of different sub-properties or a number of different country-level sites - with Universal it was quite rigid. You had a set of steps that you could define, and then you would have to do your analysis that way. But GA4 allows you to create these custom Explorations where you can look at things like funnels, but you can also look at things like segment overlap, which is a really nice feature. You can see where two different segments of users actually overlap and what that intersection looks like.

This was something that Fred Perry have been using to better understand how people are using their website, and how different marketing activities are driving different types of users, and how those users behave differently across different sections of the website.

David Bain  17:36

Do you think that senior marketers can rely on Analytics pros to provide them with the data? Or should they actually be diving into Google Analytics themselves to better understand the platform?

Dara Fitzgerald  17:50

That's a tough question. I think maybe the answer is a combination. I do think it's important for senior marketers to understand some of the nuances. One of the things that always comes to the surface whenever we run a training course, or even if we're speaking to senior clients - if you don't understand some of the nuances of how the data is collected, and some of both the limitations but also the benefits. If you don't really understand at least the foundations of how that's working, it can lead to a lot of incorrect assumptions and misusing metrics or trying to compare two metrics that shouldn't be compared.

Having said that, obviously senior marketers, their job can't be to be in GA4 all day long, so I think it is a combination of both. But there's a bridge isn't there? There's a language bridge between the two where, if the people who are ultimately making the decisions based on the data have enough of an understanding to know what GA4 can and can't do, then that's going to better equip them to work with their in-house or agency analysts - who can then be briefed on taking that qualified question, digging into it, and coming back with an answer.

David Bain  19:06

Let's move on from what works now to planning for the future. In your opinion, what's the biggest marketing trend or challenge for marketers over the coming year?

Dara Fitzgerald  19:16

Well, if I can be bold and stick two in, I'm going to try and squeeze two in. This deadline I keep mentioning is obviously a big deal for marketers who are relying on Google Analytics, or specifically have been relying on Universal Analytics to help them understand their campaigns and optimize their campaigns. Given that July 23 is just around the corner, I think finalizing GA4 implementations, migrating those last reports over to GA4, and making sure that the wider businesses understand what GA4 is capable of is going to be a big focus for marketers working specifically with GA as their main analytics tool.

And then maybe the other point that I was going to try and just squeeze in as well is obviously the continual shift towards a more privacy-centered web, basically, and some of these headlines that are coming out about tools like GA being illegal. Sometimes they're slightly “clickbaity” headlines, but the constant shift towards a more privacy-centered approach to marketing. GA isn't excluded from that; it's a big part of it. So that's the other big challenge, I think, for marketers - continuing to have data that they need to optimize their campaigns while also, at the same time, respecting users' choices in terms of consenting to data being collected and used.

David Bain  20:37

I've been your host, David Bain. You can find Dara over at measurelab.co.uk. Dara, thanks so much for being on the Strategic Marketing Show.

Dara Fitzgerald  20:46

Thank you again for having me.

David Bain  20:48

And thank you for listening. Here at IFP, our goal is simple: to connect you with the most relevant information, to help solve your business problems, all in one place. InsightsForProfessionals.com.

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