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With Google announcing that Google Analytics 4 is going to become the main analytics tools from July 2023 I have replicated my Google Analytics 3 audit for Google Analytics 4. When working on my free mini audits back in 2020 during redundancy, the feedback received was positive on the GA3 + GTM audits.

The whole purpose of an audit is to look back at the set-up and provide recommendations into making improvements. With Google Analytics 4 being a very new tool into market that is being adopted, the structure of GA4 audit will provide a guide into getting the best possible set-up.

The Audit Structure  

The structure behind the audits came from the balanced scorecard approach to provide a concise view in understanding and improving the set-up with an audit score to make clear what the next steps are.

The GA4 audit is structured in the same way as the GA3 audit:

  • Split into 3 categories:
    • Business Critical Requirements.
    • Business Minimum Requirements.
    • Business Advanced Requirements.
  • The scoring areas were split into 3 levels:
    • 1 – Not implemented.
    • 5 – Partially implemented.
    • 10 – Fully implemented.

Google Analytics 4 audit has a total score of 200. The overall scores are split into 3 levels:

  • Google Analytics 4:
    • Good – 85.
    • Very Good – 80 to 150.
    • Excellent – 150 to 200.

(Download GA4 audit)

Understanding the Audit

The audit is split into 3 categories: critical, minimum, and advanced I will look to explain below each of the scoring areas.

Business critical requirements

Deployment of GA4 via GTM:

Ensure that GA4 is deployed via GTM or any Tag Manager. Yes, there is an option of adding the GA4 global site tag to your website code. Using GTM or any TMS will provide huge amount of flexibility to enhance your tracking with ease.

Correct data stream set-up:

Ensure that the right data stream is set-up. Example for the below is for my own blog (web).

Can have a total of 50 data streams within one property and a max of 30 app steams.

Once you have set-up the data stream the following options are available:

Enhanced Management provides the opportunity to control your data and enhance your tracking.

These are the automated interactions that are tracked. Any of the 5 can be disabled at any time.

Under the more tagging settings it provides more control in the configuration of GA4.

Property settings and access management:

Ensure the property name aligns correctly to the business. Getting the time zone right is important as you don’t want to be changing it after. For business who work with multiple currencies, only one currency can be selected.

Access levels have never really been governed in the right ways with GA4 there’s a variety of roles and restrictions to provide more control. It needs to be reviewed on a regular basis, at least quarterly if not monthly and there should be couple of handpicked users who provide internal and external access.

Data Collection:

This is a hugely important set-up as it covers Google signals which is required to set-up audiences that can be shared with the linked Google Ads accounts. Google signals also provides the demographic data within GA4 as well.

Under the advanced settings icon you can control collection of location, device, and geo data.

The last data collection setting is all around privacy and data collection agreements.

This section needs to be collaborated with someone within the business who is closely working on data privacy. Any changes made need to align with the business view on data privacy.

Data Retention:

There are only 2 options, either 2 months or 14 months. Recommendation would be to go for 14 months. In GA4 360 the max is 50 months.

Changing the retention does not impact the standard reports, but it does impact the reports within the exploration.

Data Filters:

The filters are limited now with only being able to apply two types: internal and developer traffic.

Reporting Identity:

There are two options in how Google Analytics can identify users depending on the business model and the view on data privacy.

There are 3 ways to identify users:

User ID – if it’s enabled (and collected via dataLayer)

Google Signals – if enabled (need monthly average of 500 users per property to activate Google signals)

Device ID – web and / or app device ID

User ID is the most accurate way to help identify users across multiple devices. Google signals is also likely to have a positive impact in it’s ability to recognise users.

Attribution Settings:

This setting is very powerful and provides the flexibility that was not available within GA3.

Attribution model – Currently there are 6 different models available, need to decide which model is the right one for the business. Google recommends the data driven model, which may not be necessary the right one for the business. Any change will be applied to historical and future data, don’t want to get into a habit of constantly changing the model.

Any changes will impact conversion and revenue data.

Lookback window – Need to think about the user journey which will help dictate the lookback window which will vary for every business. Any changes made will impact all data going forward.

Makes it extremely important to make these decisions early on when setting up GA4.

Campaign Tagging (UTM):

The insights that can come from solid campaign tagging can be hugely powerful, need to strategically think how to best approach it to provide the required data.

Key business KPI’s are tracked and marked as a conversion:

With the use of GTM or any TMS ensure that all key business KPI’s i.e., leads, sales, sign ups etc are tracked within GA4.

Need to ensure that the selected KPI’s will be seen as events within GA4 and those KPI’s need to be marked as a conversion.

Business minimum requirements

Connecting to Google Ad products (Google Ads + Search Console)

Connecting to other Google products, Google Ads and Search Console being the most important ones and the integration is seamless. It provides the ability to look at Google Ads and Search console data with the richness of GA4 data.

Big Query linked:

Connecting to Big Query is very easy and the real value of GA4 comes with getting access to the raw data in Big Query, it can be merged with other data sources and then visualised in Google data studio.

Key Events tracked:

Outside of the key business KPI’s what additional key events need to be tracked, i.e., add to cart, newsletter signup, 100% video watched etc.

When setting up GA4 tracking every event is not required, start of by thinking which events are imperative to understand the user journey.

This is only looking at the tracking of key events, not the modification of events etc.

Error Page tracking:

This is one of the most important tracking features but it’s very underutilised.

I would highly recommend in setting up error page tracking when setting up GA4. It will provide huge number of actionable insights to improve performance. I would look to deploy this via GTM or any TMS then using the automated tracking features within GA4.

(download GA4 error page tracking GTM container)

Custom Alerts:

This is not currently available within GA4, am hoping it’s a feature that will be released soon in a better form then how it was in GA3. Would be great if there was a text provided when custom alerts are triggered + notification if you have the Google Analytics app downloaded on your phone.

Business advanced requirements

Custom Dimension / Metrics:

The enhancement of the GA4 data model will come in the form of custom dimensions and custom metrics. It will require some thought in what dimensions and metrics are needed but there is more flexibility with 50 of each available. In GA4 360, 125 of each are available.

Any configuration will need to be done within GTM or any TMS and in GA4 as well.

Calculated Metrics:

This is not currently available within GA4, am hoping it’s a feature that will be released soon.

Within GA3 it was very powerful, as you can build metrics that got you closer to the business language then sticking to metrics and language that Google Analytics provided. It can be built in data studio but do hope it’s a feature that is bought into GA4 especially with the powerful exploration reports.

Exploration Reports:

With a growing gallery of templated reports from funnel exploration, segment overlap and user behaviour there are reports that can be utilised by all. The gallery is only going to keep on growing so finding the best reports and visualisation is key to unlocking insights.

The value in the reports will come from a solid GA4 set-up and the richness of data available.

Channel Grouping:

This is not currently available within GA4, am hoping it’s a feature that will be released soon.

Once the UTM tagging is nailed down it will provide the opportunity to build out channel groupings i.e., Organic Paid Social, Paid Social etc to better understand how different channels are performing and not focus on source / medium which provides limited insights. Creating bespoke channel groupings will resonate with stakeholders outside of analytics and gain more trust in the data.


At this moment segments created cannot be saved and It’s only available within the exploration not standard reports. Hopefully this will change over the next few months.

With the data available in GA4 + enhancement of custom definitions, you can build some powerful segments to provide deep insights. It should help bridge the gap in being able to answer business questions that was not possible within GA3.

The segments created can also be turned into audiences which can be shared with other Google products such as Google Ads and DV 360.


When setting up GA4 it should be done in phases which align to the 3 categories: business critical, business minimum and business advanced requirements. The business critical is the most significant phase in the setup of GA4 and getting close to a perfect setup score of 100 will provide the foundations to build on. For Business minimum outside of the product integrations getting key events tracked and error page tracking should be high on the priority list. Business advanced is all about enriching the data and generating insights through better reports and visualisations.