The deadline to switch to GA4 is approaching, are you ready?
Businesses of all sizes and industries are faced with navigating how to best prepare for the inevitable GA4 migration. And while it is somewhat of a steep learning curve, it isn’t all doom and gloom either. This updated version of Google Analytics is better geared toward marketers and carries with it a number of customer-centric measurements for you to understand your audience more accurately.
Two Octobers’ Head of Analytics Nico Brooks walks us through the details in this recording of a webinar from August 2022.
The original announcement that Google made about GA4 was in October of 2020. They’ve since said they’ll call current version that everyone is using, “Universal Analytics,” to differentiate between the version that we’re familiar with and GA4.
Google will stop processing new data to Universal Analytics July 1, 2023. That means that you’ll still be able to log into your account and see data collected up until that date, but you won’t be able to see any data after July 1, because it’s not being collected in Universal Analytics. That’s a huge deal. The purpose of collecting data is to understand how people are engaging with our website, and the things that we want to know all benefit from historical context. A lot of what what we use analytics for is to understand trends over time. If you want to see trend data, there’s a lot of pressure to get up to speed and get your GA4 set up properly.
2005. The very first version of Google Analytics was launched in 2005. It was invite-only, and based on a tool bought called Urchin. It didn’t look anything like the Google Analytics you know.
2006. In 2006 everybody could have a Google Analytics account. The version that launched in 2006 looked very much like what you know: the layout, the color scheme and a lot of the standard reports were very much like what you’re familiar with.
2012. What they now call Universal Analytics launched in 2012. It included a pretty big change in how tracking worked as well as a refinement of the UX. If you were used to using Google Analytics, you didn’t need to learn the new interface; there were just some reports that hadn’t existed before. Plus, data collection capabilities really improved. But as a user, you could have been completely unaware of that launch.
2020. GA4 is announced. This is the first time that they’ve made a change where you must upgrade on a timeline.
GA4 really is a profoundly different tool than Universal Analytics. While the use cases that it helps to solve—understanding who your audience is, understanding where they come from, what they do on your website, how your marketing channels perform—are the same, how it works is profoundly different.
A lot of the work that will go into setting up GA4 properly will be here. Shopify ecommerce, Calendly sign-ups, ticket sales, integrating tracking with third-party tools installed on your site can get complicated to track in GA4. But if you just have a WordPress site where you’ve got a lead form, and maybe a few videos, setting up GA4 is a piece of cake.
I’ve mentioned some good new things, some things that went away that are a little unfortunate. Something that I like to say is: Google Analytics is one of the most powerful tools you have on your computer that’s available to you. And it’s free! I think most people don’t appreciate how powerful it is. Because you don’t have to pay anything for it. Organizations are typically not motivated to invest a lot in setting it up and learning how to get the most out of it, but there are really a remarkable number of features, especially for something that’s free.
You are going to need a person or people with advanced expertise in Tag Manager, Data Studio (now Looker Studio) and GA, or a lot of interest and the aptitude to get there. Getting it set up properly is not for non-technical people. With Universal Analytics, it was possible to at least to get page view tracking working pretty well if you were not technical.
For a website that’s just WordPress with a few forms and maybe some videos and a couple of other lightweight interactions is going to be a really quick setup, especially if you know what you’re doing. But it could be a serious undertaking, if you really want to take advantage of the power of GA4 for specifically creating custom events, custom dimensions and metrics based on those. And if you’re using Data Studio a lot, it will take a lot of time—GA4 doesn’t translate at all. A Data Studio dashboard set up using Universal Analytics data must be completely redone—you can’t just point to a new data source.
But if all you do is just get it set up, you’ll get immediate benefits: multiple attribution models, user dimensions, some really interesting new metrics related to ecommerce, automatic events like scroll tracking and video tracking. But most of the power of GA4 is going to take time and investment to reach.
Gartner put together an analytics maturity model. The idea is that as an organization, or for a project, you can assess analytics maturity. On the left, we all start with descriptive analytics, like being able to understand what happened via analytics. Then we get to diagnostic analytics where we use the analytics data that we’re collecting to understand why things happen. The next stage is predictive analytics, where we start to use this data to create predictive models to understand what will happen. Finally that leads to prescriptive analytics where, for example, if you want to increase revenue, you start to predict changes in data, which can then inform a marketing strategy to get ahead of the game, and reach people based on on seasonal behavior. Prescriptive analytics is the goal at the end of the rainbow from a marketing standpoint—we’re using the data to create predictive and prescriptive models to say, if we do this, we’re going to be able to increase revenue, customers, or whatever the outcome it is that we’re trying to maximize.
We all want to get to prescriptive analytics. And in fact we have to get there if we want to compete in the world that we live in right now—many organizations are investing in predictive and prescriptive analytics, so just to keep up, we need to be there. GA4 is a much more powerful platform than Universal Analytics for descriptive analytics, because it has complete flexibility in what you’re tracking. How important are page views, really, to your business? Unless you’re a publisher, and you have a revenue per page view model, probably not very important. Page views doesn’t explain any kind of engagement; you can get a high number of page views by having blog posts that are irrelevant to your business, but have a lot of appeal and maybe have been around for a while. That’s what Universal Analytics is. Page views is the first thing it was built to track, and it’s the main thing it tracks still today. GA4 is much better at supporting the things that happen on a website that you care about.
GA4 also has better diagnostic analytics tools built in. Machine learning tools start to give you a feeling for trends like worth pointing out and anomalies. It’s not going to answer the question of why, but it’s going to get you a lot closer by highlighting changes, and the dimensions that correlate closest to why those changes have happened.
For predictive analytics, what’s valuable is the link into BigQuery, which is a very powerful platform for creating models around predictive analytics. You can create machine learning models directly in BigQuery to build predictive models, in addition to a variety of other capabilities. If you don’t use BigQuery, you can easily create a conduit from BigQuery into Snowflake or something else to do essentially the same thing.
Descriptive analytics is the foundation for all of this, because it’s what everything else is built on—when it is accurate and complete. I look at hundreds of analytics accounts a year, and I would say only occasionally do I come across one that is set up well, where I don’t, within a few minutes of auditing, find obvious problems with how data collection has happened. The analytics maturity model is wonderful. And we’ve had the tools to be there—you could have done so with Universal Analytics. It wasn’t the tool wasn’t the thing stopping you, you were the thing stopping you. And I know that sounds condescending and preachy. It is a little preachy, I apologize; it is a subject I’m super passionate about. It’s not like not like the Two Octobers Analytics account is set up perfectly, so I should not be casting any stones.
Now! Honestly, it’s that simple. You can run Universal Analytics and GA4 side by side. A year from now will be August 2023. Universal Analytics will have stopped collecting data in July and you will no longer have a year’s worth of data if you’re not already up to speed on GA4. There’s no reason not to do it, you’re going to have to make the investment at some point—you should do it now, so you’re collecting historical data.
Final case for investing in analytics. Let’s do some quick napkin math. Let’s say you spend $10,000/month on marketing and you optimize your marketing to conversion value (because of course you do—because we should all be doing that). But your measurement of conversions is off by 20%. You’re wasting approximately $24,000 a year because garbage in garbage out—you’ve got bad data that you’re building everything on.
Of course whatever data is incomplete doesn’t mean that everything you’re doing is wrong. But nonetheless, just think about that math. We get people all the time that wouldn’t bat an eye at spending thousands of dollars a month on Google Ads, but haven’t invested much at all in getting their analytics data collection accurate. A lot of the money that they’re spending is wasted.
Two Octobers helps marketing teams feel confident in their website, lead, and revenue tracking. We offer GA4 migration services, one-on-one and small-group Google Analytics training, and build marketing dashboards for better real-time insights. Contact us to build a better foundation for your marketing programs.
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