How GA4, information modeling and Google advertisements paintings together

There’s a lot going on in the world of Google Analytics 4 right now, because July 1st keeps zooming in.

Earlier this month, Google introduced a new, more flexible label created to work seamlessly with GA4 and Google’s suite of advertising platforms, including Google Ads.

Google may have implicitly acknowledged that advertisers have a lot to process when it announced this recently cookies will have a longer shelf life in Chrome as previously reported.

This article will break down how paid search marketers need to approach the analytics transition:

• Philosophy.
• The differences and how to adapt.
• Time to move.
• And a reporting solution that will replace some of the insights that would otherwise be lost in the transition from UA to GA4.

A new era of marketing analytics

iOS14, CCPA, GDPR – all these acronyms have struck fear into the hearts of marketers over the past few years.

Together, they’ve moved the marketing world into the era of user privacy by seriously reducing things like automatic cookie tracking and in-app activity tracking in marketers’ data portfolios.

To make up for the loss of reliable mechanisms for collecting data and tying actions to specific users, Google is moving quickly into the future data modeling.

Essentially, the search engine uses AI to fill in the data gaps left by privacy regulations, browser restrictions, and stealthy cross-device behavior.

Data modeling in GA4 doesn’t include any off-site data unless you go out of your way to implement it (more on that in a bit), but it does include all sources of traffic and activity, not just Google sources.

One of the features of Google’s analytics shift is that it’s designed to be flexible and should be relatively easy to adjust as the landscape changes.

GA4 relies heavily on its own data, which you own and will always be able to access.

It’s a more flexible and customizable reporting setup than UA (which is both good and bad, since you need more resources to set it up, but it has much more potential for rich insights).

Combine that with a new tag that doesn’t require nearly as much code or customization, and you can see that Google is preparing a future where marketers can self-serve to get all kinds of data that can help them optimize their campaigns.

One big difference in data: events vs. goals

If you’re making Google Ads decisions based on data like sessions and page views, it’s time to change your strategy.

GA4 replaces them with events, which means secondary metrics like bounce rate (as we know it), time on site and pages per session won’t be available to you for a long time.

Instead, GA4 introduces new metrics, including “engaged sessions,” which at this point can mean anything from a session longer than 10 seconds to a session that ended up converting to a session where the user bounced back and forth between screens.

As I see it, this can be purposefully useful in determining whether a channel has a relatively high or low proportion of engaged users.

Another new metric that I think is roughly important is “User Engagement” which Google describes as “the average time the app was in the foreground or the website was focused on the browser.”

Other differences in data

As you prepare to migrate your audiences from UA to GA4, know that not all dimensions will translate.

For example, dimensions related to “session” such as the path to the next page will not transfer because GA4 measures sessions differently.

That said, GA4 is built to allow you to customize the dimensions you find important so you can recreate those insights yourself.

Another change to note while we’re on the topic of audiences is that GA4 limits each trait to 100 audiences, which is a huge reduction from UA’s cap of 2,000.

Personally, I’ve never gotten more than 200 audiences per brand, but if you have, say, a ton of remarketing audiences built around GA metrics, you might want to consider paying for GA360. (If I had to guess, I’d say it won’t be a widespread problem, or Google wouldn’t be so aggressive about limiting the limit.)

Next Steps: 3 Things Paid Search Marketers Can Do Now

1. Decide on the whole data picture

In general, marketers should focus their analytics around business outcomes, not just about driving a conversion on a page.

It’s smart to start measuring based on things like revenue and how much you can attribute to advertising.

To do this, no matter how good your setup is in GA4 or Google Ads, you need to integrate offline conversion data and make sure your CRM data is part of the puzzle.

I am currently working on testing how effective it is to import offline conversion data into GA4 via Device ID or User ID.

I suspect it won’t be perfect yet and there will be data gaps, but the exercise of setting up different data sources will pay off over time as the data modeling improves.

2. Start the migration

Marketers dislike change any more than the average bear, but there’s no point in delaying the inevitable.

The sooner you set up GA4, the sooner you can get a relatively clean year-over-year comparison in 2023.

The problem will not appear immediately. You want to set this up now so you don’t have a data gap for Q4 2023.

You could still compare the GA4 and UA data next year if you really got into a pinch, but you’d have to do a lot of work in Data Studio and it wouldn’t be apples to apples.

So set it up now to get all the Q4 data for good YoY.

3. Set up new reporting

One of the benefits of diving into GA4 now is that you’ll be able to choose the range of reports you need to rebuild.

For example, I noticed pretty quickly that in GA4 you can’t create rules to remove non-Google UTM tracking (like the HubSpot parameters), so you have to include Data Studio to clean up the landing page report so you don’t have to wade through thousands of rows (each unique the split page parameter).

GA4 will not allow you to remove tracking data from URLs and then calculate CVR, whether based on users or views. But with this cleanse, you can see the LPs with the most conversions, for paid traffic or all traffic.

So instead of this inherited view:

… you get something much more useful:

To create a clean landing page view:

1. Select Add Dimension > Create a field.
2. RegEx and enter REGEXP_REPLACE(Page path + query string,'\?.+', '') in the formula field.
3. Pull in Views and Conversions.
4. Create a calculated field for your conversion rate. I used Views and Conversions (Conversions/Views).

I guarantee this is the tip of the iceberg… the more we play, the more we will find out where we are missing or have an opportunity to improve in GA4.

The saga continues…

As you can see, we are still learning about all the capabilities of GA4 and how to reflect them in Google Ads campaigns.

In the coming months, as the July 1, 2023 deadline approaches and more marketers gather the courage to begin the transition to GA4, I expect more best practices to circulate.

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The opinions expressed in this article are those of the guest author and not necessarily those of Search Engine Land. Staff authors are cited here.

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