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How GA4, data modeling and Google Ads interact

Theres a whole lot going on in the wonderful world of Google Analytics 4 at this time, as July 1 continues to obtain closer.

Earlier this month, Google introduced a fresh, more flexible tag created to work seamlessly with GA4 and Googles suite of ad platforms, including Google Ads.

Google may have indirectly acknowledged that advertisers have too much to process when it recently announced that cookies could have an extended shelf life on Chrome than previously reported.

This short article will breakdown how paid search marketers have to approach the analytics shift:

  • The philosophy.
  • The differences and how exactly to adjust.
  • The timing for migrating.
  • And a reporting workaround to displace some insights youd otherwise lose in moving from UA to GA4.

A fresh age of marketing analytics

iOS14, CCPA, GDPR most of these acronyms have put fear in the hearts of marketers in the last couple of years.

Collectively, theyve moved the marketing world into an age of user privacy by severely reducing things such as automatic cookie tracking and in-app activity tracking in marketers data portfolios.

To create up for losing reliable data collection mechanics and tying actions back again to specific users, Google is moving quickly to another of data modeling.

Essentially, the internet search engine uses AI to complete data gaps left by privacy regulations, browser limitations and obscured cross-device behavior.

Data modeling in GA4 doesnt include any offsite data if you don’t take your time and effort to implement it (more on that in a little), nonetheless it does include all resources of traffic and engagement, not only Google sources.

One attribute of Googles analytics shift is that its made to be flexible and really should be not too difficult to adapt based on the way the landscape shifts.

GA4 relies heavily on first-party data, that is something you possess and will continually be in a position to access.

Its a far more flexible, customizable reporting setup than UA (that is both bad and the good in that you will need more resources to create it up, but its got much more prospect of rich insights).

Combine that with the brand new tag, which doesnt require nearly just as much code or customization, and you will note that Google is establishing another where marketers can self-serve to obtain all sorts of data that will help them optimize their campaigns.

One big data difference: Events vs. Goals

If youre making Google Ads decisions predicated on data like sessions and pageviews, its time and energy to shift your strategy.

GA4 is replacing people that have Events, this means secondary metrics like bounce rate (once we know it), time on site, and pages per session wont be accessible for you for a lot longer.

Instead, GA4 is introducing new metrics including Engaged sessions, which at this stage often means anything from the session longer than 10 seconds to a session that ended in a conversion to a session where in fact the user bounced backwards and forwards between screens.

WHEN I see it, which can be directionally useful in determining whether a channel includes a relatively high or low proportion of engaged users.

Another new metric, that i consider about as significant, is User engagement, which Google describes because the average amount of time that the app was in the foreground or the web site centered on the browser.

Other differences in data

When youre getting ready to migrate your audiences from UA to GA4, understand that not absolutely all dimensions will translate.

For example, session-related dimensions like next page path wont port over because GA4 is measuring sessions differently.

Having said that, GA4 was created to enable you to customize the dimensions you discover important, so youll have the ability to recreate those insights by yourself.

Yet another change to notice, while were on the main topics audiences, is that GA4 is limiting each property to 100 audiences, an enormous reduction from UAs cap of 2,000.

Ive personally never pulled a lot more than 200 audiences per property, but when you have, say, a huge amount of remarketing audiences built around GA metrics, you might have to consider spending money on GA360. (EASILY had to guess, Id say this wont be considered a widespread issue, or Google wouldnt have already been so aggressive about curtailing the limit.)

Next steps: 3 things paid search marketers can perform now

1. Choose a complete data picture

Overall, marketers ought to be orienting their analytics around business outcomes, not really a conversion firing on a full page.

Its best if you start measuring when it comes to things such as revenue and just how much it is possible to attribute to advertising.

For that, regardless of how good your setup in either GA4 or Google Ads, you have to integrate offline conversion data and ensure that your CRM data is section of the puzzle.

Im currently establishing testing how effective it really is to import offline conversion data into GA4 via device ID or user ID.

My suspicion is that it wont be perfect yet, and you will have data gaps, however the exercise of establishing the various data sources can pay off as time passes because the data modeling improves.

2. Get your migration on

Marketers dont like change any longer compared to the average bear, but theres no sense in postponing the inevitable.

The earlier you create GA4, the earlier youll be capable of geting a comparatively clean year-over-year comparison in 2023.

The problem wont rear its head immediately. You would like to arrange it now and that means you wont have a data gap for Q4 2023.

You can still compare GA4 to UA data next year in the event that you really found yourself in a pickle, but youd want to do plenty of work in Data Studio, also it wouldnt be apples to apples.

So arrange it now to obtain all of the Q4 data for YoYs sake.

3. Create new reporting

One advantage of digging into GA4 now could be that youll have the ability to scope out the reports you should re-build.

I noticed pretty quickly, for example, that you cant create rules in GA4 to eliminate non-Google UTM tracking (like HubSpot parameters), and that means you have to get Data Studio involved to completely clean up a website landing page report so youre not muddling through a large number of rows (each unique parameter breaks out a full page).

GA4 wont enable you to strip tracking info from URLs and calculate CVR, whether predicated on users or views. But achieving this cleanup enables you to see top-converting LPs, for paid traffic or all traffic.

So rather than this legacy view:

Screenshot of legacy data in GA4.

you obtain something much more useful:

Screenshot of cleaned-up data in GA4.

To generate the clean website landing page view:

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

I guarantee thats the end of the iceberg the more we experiment, the more well realize were either missing or get the chance to boost in GA4.

The saga continues

As it is possible to tell, were still studying the full capacity for GA4 and how exactly to reflect it in Google Ads campaigns.

On the coming months, because the July 1, 2023 deadline approaches and much more marketers muster up the courage to start out the transition to GA4, I expect more guidelines to circulate.

Opinions expressed in this post are those of the guest author rather than necessarily INTERNET SEARCH ENGINE Land. Staff authors are listed here.



    Laura Schiele, Head of Paid Acquisition at Jordan Digital Marketing, has nearly ten years of experience in paid media strategy and execution in both agency and in-house accounts and uses advanced analytics skills to scale growth within efficiency goals across Google, LinkedIn, Facebook, and much more. Laura manages a big team of paid media experts remotely from her home in Burlington, VT.

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