Difference Between Google Analytics 4 and Universal Analytics: FAQ Webinar 

by | Jun 21, 2022

41 min read

In our latest Data-Driven Digital Community webinar we got an expert panel to discuss the difference between Google Analytics 4 and Universal Analytics. Watch the full webinar recording below.

We covered:

  • The difference between Google Analytics 4 and Universal Analytics
  • Changes: comparing GA4 with UA – what are the losses and gains?
  • Power features: tools to improve every metric, from traffic to lifetime value
  • Reporting: replacing off-the-peg reports with deeper, custom insights
  • Privacy: how will you fare in the cookieless future?
  • Integrations: how GA4 syncs with ad platforms and CRM to analyse, personalise and automate your messaging
  • Data: extra ways to profit from the mass of BigQuery data
  • Timeline: why the next market leaders are taking action now


Watch the webinar now:

Our Expert Google Analytics 4 Panel

In the below webinar you’ll hear the difference between Google Analytics 4 and Universal Analytics from:

Paul Hewett

Facilitator & Host

Paul is the CEO of data-driven performance agency In Marketing We Trust. With a background in marketing data and analytics, Paul has nearly two decades of consulting with enterprise companies on the application of data for marketing performance optimisation. In his previous role as a council chair at the DMA UK, Paul was actively involved in the industries response to the formation of the GDPR.

Benoit Weber

Analytics Specialist

Benoit is an Analytics Specialist and Head of Digital Analytics at In Marketing We Trust. He is passionate about all things analytics, has already migrated many large websites to Google Analytics 4 and is an advocate for data privacy and governance. Benoit has been with In Marketing We Trust for over 7 years helping our clients optimise their performance through data.

Alan Bluwol

Director, Head of Customer Engagement at Servian

Alan leads the Customer Experience practice at Servian. With over fifteen years of experience, he has been delivering data & digital transformation strategies, vendor assessments, solution architecture and personalised, omni-channel capability for some of Australia’s leading brands including Bunnings, Metcash, Country Road, David Jones, Koala, Milkrun, NRMA, Accor, Australia Post, Telstra, BT, Zurich, HCF, Rest Super, Active Super, Pepperstone, Tatts, Westpac, JCDecaux, AstraZeneca and many more. His work has enabled these brands to extract deep, rich and actionable insights from data to continuously enhance customer experience at every stage of the customer journey.

Selina Gough

Head of Digital

Selina is Head of Digital at the performance agency, In Marketing We Trust, Selina has over a decade of experience across all facets of digital marketing with a specialisation in strategy and performance marketing. She has worked alongside many national enterprise clients to align their business goals with their digital strategies to ensure that their business is seeing growth and hitting targets.


Difference Between Google Analytics 4 and Universal Analytics

GA4 has been around for 2 years. The sunsetting announcement is a significant and rapid change for the market. 

Difference between Google Analytics 4 and Universal Analytics PropertiesIn your opinion, what do you think will be the impact of this change on the digital marketing industry?

  • What are the benefits of Google Analytics 4?
  • What do you think will be the main challenges? 


What are the benefits of Google Analytics 4?

  • USER CENTRIC – The depth of information that we gain on users is much greater, due to the measurement model being event-based, not session-based.
  • Event tracking allows for less fragmentation by device or platform, unlike sessions.
  • What this allows us to do is to have better clarity on the user journey and how they have interacted with a site/app and allows marketers to make smarter decisions, especially those who have customer-centric strategies.

What do you think will be the main challenges?

  • Predictive analytics – AI to predict customer actions and value – the AI is only as good as the data that the system is fed.
  • The mindset of digital marketers – SEO needs to look deeper than base-level UX, such as load speed, and instead look at what keeps users on pages, what encourages them to scroll and click through, and generally engage with the site. This means UX and CRO specialists need to work closer than ever with SEOs to develop websites that truly provide an experience that people want to use.


What are the benefits of Google Analytics 4?

  • The holistic view on users’ activities across platforms is in my opinion one of the most interesting features that GA4 is bringing. We can now see unique analytics activities of users across platforms across websites and apps.
  • The second benefit I see with GA4 is its accessibility of the raw data via the native integration with BigQuery. It used to be a paid-only feature (360 clients) and this opens the world to more advanced data techniques allowing companies to combine their analytics data with other first-party data they own (CRM data, Transactional data) or even third-party datasets. Given access to the analytics data into Bigquery will allow people to use other GCP tools such as Auto ML. This will allow us to activate data in ways that used to be 360 only.

What do you think will be the main challenges?

  • Reporting is going to be the main challenge for the industry. Not only will we need to unlearn what used to be but we will also need to educate ourselves on GA4. Out of the box, the available reports are quite limited, so the teams will need to build their own custom reports and dashboards.
  • Historic data: since UA is about to sunset, we will also need to tackle historical data: where to store it, what to save and how to report on it. 


What are the benefits of Google Analytics 4?

  • It will cause the industry to rethink the way they can capture and use customer data.
  • By moving away from the visitor/visit paradigm to an event-based model.
  • Allow the industry to leverage more than just website and mobile app behaviours. 
  • Creating the opportunity to bring together ALL sources of customer data, including back-office system data like sales transactions and other “offline” conversions.
  • If you’ve got a data warehouse and advanced analytics capability, these too can be brought into the mix and tracked with GA4.
  • It equates to having a more complete, sophisticated and unified view of the customer.
  • It will shift the mindset for measurement of digital marketing spend and performance – to see the bigger picture impact of advertising, personalisation and other customer engagements on the overall customer experience.

What do you think will be the main challenges

  • It’s coming hard and fast, and we know there isn’t an out-of-the-box “lift and shift” to migrate over.
  • Because of the shift in focus and requirement for defining your own events about your customers, it will force the industry to be much more data-driven.
  • Many may be caught out trying to “re-created” the world of GA3 into GA4 and miss the immense opportunity in front of them to redefine their approach to leverage more of their customer data.
  • Many may find it difficult to bring the right level of data skills required to properly configure GA4 and realise its full potential.


There has been a lot of discussion about missing features and reports over the past year, prompting some to ask if this tool is ready. 

From your perspective what can users expect from the platform? 

  • What are the important features/reports of Google Analytics 4?
  • What features or reports are missing from GA4? 


What are the important features/reports of Google Analytics 4?

  • Attribution models are a powerful feature. There is now the capability to change the attribution model applied to all your reports. 
  • The number of reports has been divided by 4. UA used to have >80 reports built out of the box, we only have around 20 now. So yes, you will have the impression of missing out on reports BUT they made GA4 highly configurable and the “Explore feature” is one of the most important ones that will enable you to build your own custom reports. The caveat is that people will need to be familiar with the data model, the structure and the semantics of their analytics to be able to properly build by themselves their own report. 

What features or reports are missing from GA4?

  • The basic reports/features are now available in GA4. When GA4 was released (end of 2018) a lot of features were missing but they are catching up at a fast pace. What I have learnt over the last few months is that everyone needs to keep up to date with the new capabilities, reports, dimensions and metrics that GA4 is making available for the team to use. Do not make any assumptions about what is available or not.
    • Ecommerce: Checkout behaviour, Shopping behaviour
    • Content Report: Behaviour flow, content drilldown, landing page reports
    • Events: Event flow
    • Integration: Search Console, Google Ads
    • UTM Content and UTM terms, bounce rate, conversion rate
    • BUT most reports can be rebuilt using the explore reports


What are the important features/reports of Google Analytics 4?

  • The user lifetime report is extremely powerful for search marketers because it lets you create reports that visualise which source is driving users with the highest lifetime revenue — not just revenue for a selected month.
  • Life Cycle Reports – answers how a user enters a conversion funnel and how they behave once in the funnels.

What features or reports are missing from GA4?

  • Bounce rate – this can highlight opportunities for businesses to evaluate their UX and whether there is a requirement for activities like CRO to improve performance.
  • Views – ability to easily filter traffic across multiple views.

The Role of Analytics in Marketing

Google Analytics has always positioned itself as an entry-level analytics tool that is easy to adopt. GA4 is more advanced and appears to be moving into the enterprise analytics space. 

What do you think this change means for the future relationship between marketing and analytics/BI?

  • Do you think marketers will do more or less analysis?
  • Will advanced analytics become a mandatory digital marketing skill?


Do you think marketers will do more or less analysis?

I’ve always talked about the wall that separates the data whisperers (data, analytics and BI people – who speak data) and the data dreamers (marketers, digital, customer service, etc.) that dream of using data to better understand their customers, the business and deliver continuous improvement to operations and customer experience.

In my line of work, we’re all about proposing solutions to break down that wall so that data whisperers and dreamers can collaborate better – surfacing opportunities and actionable insight fluidly across the business.

GA4 is an important step in that direction.

Once established with the right level of data, GA4 will absolutely lift Marketing’s access to rich data and insight and provide greater self-serve capabilities to perform their own analysis.

So yes, Marketers will be working day-to-day in a far more data-driven platform, doing a lot more sophisticated analysis.

Will advanced analytics become a mandatory digital marketing skill?

I’d say that level of analysis won’t quite be what we’re labelling “Advanced Analytics”. 

The built-in AI will take some of the initial heavy lifting of surfacing useful, practical insight for the Marketers. The Marketer will need to have an appreciation and understanding of what the data is telling them, so they can effectively take action.

On the Advanced Analytics side, which we could say is in the realm of the Data Scientist, I’d suggest that this won’t be a mandatory skill for Marketing. GA4 will bring rich, granular data to the Data Scientist (via GCP), who can then surface that insight back to Marketing in a range of ways to support their analysis, reporting and decisioning.

The bottom line – GA4 is working its way to breaking down that wall that I mentioned earlier – creating greater collaboration around data between marketing and analytics/BI teams.


Do you think marketers will do more or less analysis?

  • Marketers will have to rethink the way they were reporting and might need to rely more on analysts than they used to. Especially at the beginning. 
  • Everyone will have to educate themselves on GA4. Do not underestimate how big the change will be and invest in your teams in learning the tool, getting familiar with the terminology and taking the time to properly setup GA4 and taking the time to build your own custom report using the Explore reports.

Will advanced analytics become a mandatory digital marketing skill?

Not necessarily but it will force marketers to define what they are after more clearly to be able to delegate the heavy work to analysts. Defining properly the questions they want to answer, the time frame, and the KPIs they have set based on their objective. They will need to clearly define what they are after before jumping into the data. 

  • Know your data
  • Define the questions you want to answer
  • Define your KPIs and targets
  • Create the mock-up
  • Define the end goal = what are you going to action once you get your answers


What do you think this change means for the future relationship between marketing and analytics/BI?

  • What are the biggest skills gaps you see in companies? 
  • What are your recommendations for closing these gaps?


What are the biggest skills gaps you see in companies?

The biggest skills gap generally is data proficiency across the business.

That is having an appreciation of, and practical skill in:

  1. What customer data is available 
  2. What it means and applicable use-cases
  3. Knowing when and how to use it to deliver meaningful value

As GA4 moves away from a well-known prescribed data model to an open model that accepts any data that you define and give structure to – it’s going to be critically important that organisations invest in uplifting data proficiency.

What are your recommendations for closing these gaps?

  • Make sure there are clear owners of data  – who’s in charge of data at every level of the organisation.
  • Whether it lives in GA4, BigQuery or right back in the source system – there needs to be a go-to person to tap on the shoulder and drive understanding of data.
  • Make data intuitive and accessible – so it can be correctly interpreted by anyone.
  • To create data citizens and data-driven culture – encourage every decision to be based on a story told around data.
  • In the end – it may be necessary to employ skilled data analysts/engineers and embed them within business units to work closely with the business to drive up appreciation and adoption of a data mindset.

Performance Reporting

For many of us, Google Analytics has always been about performance analysis and performance reporting. It is typically one of the first places we go to get answers.

Will the default attribution change impact how the advertising/marketing industry reports on performance? 

  • Who will be the biggest winners & losers?


Cross-channel data-driven attribution uses machine learning algorithms that attribute the credit to the touchpoints in both conversion and non-conversion paths based on probabilistic models. The models are continuously improved, learning from your accounts’ historical data and automatically adapting to changes in the performance of different touchpoints.

Thankfully this mode can be changed if businesses want consistent reporting but even the way that GA4 collects data is different so there will be disparities between UA and GA4.

  • Winners = businesses who have high traffic / high conversions as the ML has the ability to be most informed
  • Losers = smaller businesses with low engagement 
  • Losers = businesses who have not configured their properties correctly 


Do you think there could be a shift in what tool holds ‘the source of truth’ for marketing? 

  • Shifting from GA to CRM/marketing automation Salesforce/Hubspot?


This is the age-old question isn’t it – where is the source of truth?

See, CRM, Marketing Automation, Customer Service, eCommerce, Web, Mobile, etc. – they all have their own ‘source of truth’ within their specific context. UA played the role of primarily holding the ‘source of truth’ for digital tracked behaviours, and it was easily accessible and answered point questions about digital experience and performance – but it was missing all the other data Marketing would like to know about customers.

Servian’s answer to ‘source of truth’ has been to bring the data together, by helping businesses build a data warehouse or data lake and present that view through reports, visualisations and dashboards.

Instead of ‘source of truth’ – perhaps I’d invite everyone to consider reframing it as a ‘trusted view’.

Now that GA4 is being opened up and is capable of storing data about a customer from any channel or system – all of a sudden we’re starting to centralise a highly accessible customer view, which is much broader than just a digital or marketing view. Add to this, the underlying Google BigQuery database, which can be your data warehouse or data lake (if you wanted) and is capable of holding every single data point from every single system in your organisation.

Now we’re talking – two birds, one stone. 

With GA4 – you’ve now empowered the data analytics teams to support marketing teams by being able to blend all that digital, customer and enterprise data to generate deep insights to continuously enrich and serve up a ‘trusted view’ back into GA for self-service analytics and omni-channel activation.


Will the complexity of Google Analytics 4 push marketers away from this tool? 

  • Will the complexity push marketers away from this tool providing an aggregated report and onto ad platform-specific reporting? e.g. Data Studio


Yes, the short answer is yes. GA4 compared to UA will become more of a data collector than a reporting tool. Even though it is configurable and even though you can build your own reports within the interface, most of the users will want more advanced reporting/dashboards that will be done out of the platform itself. And this is especially the case for companies that will export their data in Bigquery and combine it with other data sources. 

It sort of pushes companies to grow their data maturity in a way. Companies will have to define more in detail what they really want, what they need, what they will do with it and how they are going to activate their analytics data. This forces companies to own their data and think bigger than just analytics data coming from GA4. 

Data Integration

GA4 includes native integration with BigQuery as standard. BigQuery is part of the Google Cloud Platform. This seems like an important strategic change for Google which could put Google at the heart of a company’s data strategy. 


How do you see GA4 integrating into the wider data strategy piece? 

  • What can companies do to make full use of the Google Cloud Platform integration?
  • Based on your experience in implementing complex data solutions, what challenges should companies look out for?


How do you see GA4 integrating into the wider data strategy piece?

GA4 starts you off on this GCP journey by streaming raw, rich, granular customer data, unsampled, into Google BigQuery. Which alone already provides instant access to a common interface for all data analysts and engineers to wrangle customer data – backed by auto-scaling compute, infinite storage, embedded ML, programming and visualisation capability – your data strategy is already off to a great start.

But this is just the beginning. 

An organisation’s data strategy ought to outline a roadmap of enablement that includes the way you identify your data, store it, provision it, process it and govern it. With Google Cloud, you’re working with one of the world’s leading cloud and data infrastructure providers with over 100 services to support all the capabilities you may require. If your data strategy outlines initiatives to lift and shift or completely re-architect your core business systems and applications in the cloud – Google’s got you covered with virtually infinitely scalable compute, virtualisation, containers, server-less, API management, networking, identity management, monitoring, devOps, security – resources, secrets and key management – the lot. 

If you’re looking to host and manage your data – Google provides a number of specialised, cost and performance optimised services for a  range of use-cases including integration, transformation & orchestration services, storage services for housing your files (both structured and unstructured) and application data, databases of all kinds for transactional and analytical data processing, message queues, data governance services – the list goes on…

And if you’re looking for advanced analytics using Artificial Intelligence and Machine Learning, again you’ve got a range of options to choose from, pre-built AI APIs to perform Natural Language Processing, Vision, Voice, Video, Translation, Recommendation. 

If that’s not enough and you want customisability you’ve got AutoML, out-of-the-box configurable models you can train for your specific needs. Even all the way through fully managed platforms for ML to build, train and host your own custom models. Most of these services are offered under a consumption model – therefore you can start small and scale as you see value. 

What can companies do to make full use of the Google Cloud Platform integration?

We discussed earlier that you may find limitations in GA4 itself for the things you’d like to do with data that is captured – perhaps it’s around reporting, advanced analytics, etc. As you start to hit these limits, I’d suggest, getting familiar first with what BigQuery can do for you out-of-the-box – because you’ll have that immediately with GA4. 

Then start familiarising yourself with the rest of the cloud services catalogue. There are a tonne of resources available to understand what each of these services brings to the table There are also really well-documented publicly available recipes and solution architecture templates designed to help you get started across different verticals, domains, industries and use-cases.

Your data strategy ought to set out specific use-cases for data across the business – and from there I’d line up the GCP services that are designed to specifically provide the capability you require. 

This is a service Servian provides – we help organisations navigate and architect solutions that leverage the full power of GCP.

Based on your experience in implementing complex data solutions, what challenges should companies look out for?

Architecture is key. You can practically build anything in GCP. But of course, not all designs are created equal. You can absolutely go to town and spin up and run services, scale them, process heaps of data – and rack up an enormous bill!

It is super important that the solution you build is well architected – that is first secure, then can maximise the use of services for the purpose they are built, while being highly optimised from a performance and cost perspective to achieve the desired capabilities.

We’ve helped many organisations embrace the power of GCP – be it migration from on-premise to cloud, cloud to cloud migration, hybrid/multi-cloud solutions and greenfield engineering of brand new products and solutions built native for cloud.

Do not underestimate the importance and value of having a sound solution architecture. Invest in bringing in experts to support you in designing your solution.



The topic of privacy is at the forefront of the digital industry and with the end of cookies (to some extent) in 2023 that is not likely to change anytime soon.

How does Google Analytics 4 fit with a privacy-first digital marketing future?


How does Google Analytics 4 fit with a privacy-first digital marketing future?

  • Due to the machine learning that stitches user paths together, it means that marketers will be equipped for the retirement of cookies.
  • Better ownership of the data and who our consumers are. 
  • We’ll still be able to target relevant audiences as opposed to broader cohorts and relying on things like affinity/in-market audiences.
  • Empowers businesses to invest further into first-party data, if not already.



How does Google Analytics 4 fit with a privacy-first digital marketing future?

The noose is tightening privacy controls – we all know this. The cookie apocalypse is challenging 85% of cookie-based anonymous digital tracking, advertising and marketing solutions in the market – and will likely render them useless in the next few years.

Google trialled this thing called Federated Learning of Cohorts (FLoC) – which supposedly enabled “interest-based advertising on the web” without letting advertisers know your identity. Only Google Chrome intended to adopt this standard – no other browser was going to. So it was abandoned. 

They’re exploring replacing it with another standard: Topics. Your browser may track & learn about interests (capped at about 300 over three weeks) and the browser provider can host a Topic API for Ad Servers to consume. It intends to completely hide user identity, while also giving users greater control over ads or even turn it off completely.

Bottom line – this new world will mean you will struggle to link interests and behaviours of users with your actual customers.

That means that primary, first-party data is going to become the most important asset to digital marketing. This is the data you own in your own systems about your customers.

One of the greatest benefits I see with GA4 is that it lets you take full advantage of your first-party data – by enabling you to pipe those rich customer events from your systems straight into your customer view for use across the broader Google Marketing platform (Google Ads, Display & Video 360, Optimize, etc), and activation into to other channels via GCP services like Looker.

Because GA4 is working with your first-party data, which you can govern and control, it fits in a privacy-first digital marketing future.


There are approximately 12 months to go before UA is turned off. 

Can you talk us through the key steps and considerations that Google Analytics users should do to get ready for this change?


Can you talk us through the key steps and considerations that Google Analytics users should do to get ready for this change?

Get your GA4 property up and running as soon as possible. The sooner you start collecting data the better. Ideally, you would do it before the end of June this year to get 12 months of data. It will give a complete view on seasonality and having more data improves the machine learning models within GA4.

This is an excellent opportunity to review and improve your data analytics.

Depending on the quality of your current analytics, this can be a good opportunity to review fully your measurement plan, validating that you are measuring the right thing, that you have the right integration set up, and that your reporting needs are covered. 

Once the data is in, you will need to invest time in training your teams, building your new dashboard, and reports, and defining the next steps for your companies to activate and use the data at its best capabilities. 


Can you talk us through the key steps and considerations that Google Analytics users should do to get ready for this change?

I’d suggest steering away from thinking you’ll simply try to do a like-for-like lift and shift UA to GA4.

This forced requirement to move to GA4 presents a huge opportunity to make the most of all your available customer data, so…

  1. Bring the business along on the journey – meet across business functions to understand what use-cases are they trying to solve with customer data.
  2. Go on a data hunt – build a customer data tracking plan – find, catalogue and map out every available data point you have access to today, across all your systems about your customers – their details, traits, insights, behaviours, interactions, transactions and more.
  3. Start small by onboarding data to solve your highest value, priority use-cases and when successful, showcase the value of bringing that information into GA4 and get buy-in for the rest of the business to fund, participate and contribute to building out your full GA capability.

Closing Remarks

We’ve covered a lot here.

From your professional perspective what are the 2 or 3 most important points you want the audience to take away from tonight’s discussion?



  • GA4 collects data in a way that gives us marketers greater insight into how our consumers behave & what they’re engaged with – there’s a greater push for consumer-first digital marketing strategies.
  • Performance reporting – evaluate how you’re doing it now and question whether there’s a need for a cultural shift in how you measure a consumer’s journey?
  • Digital marketers – technicians – need a change of mindset. GA4 encourages collaboration from all disciplines to help drive a seamless UX and working in siloed teams will be a thing of the past.


  • Educate yourselves: Spend time learning about GA4, how to use it, learn the new metrics/dimensions, keep up to date with the release, spend time thinking about what you really need and what you are after. Review your current reporting needs and take this as an opportunity to build better analytics and to take full ownership of your data. Having data is great, but activating it is better. 
  • Think bigger: with this new Bigquery integration, the world of data is now open to everyone. 


  • Don’t waste the opportunity to go beyond web & mobile – explore ways to blend in your other first-party data (from offline sources) into GA4 to build a rich, truly 360-degree view of customers for digital and marketing.
  • Whilst the clock is ticking – still invest the time upfront to properly and thoroughly, discover and define the customer data available in your business, and make it as intuitive for digital and marketing as possible.
  • Given GA4 is establishing your GCP footprint – starting with BigQuery – seek to learn more about how you can leverage the wider GCP ecosystem to drive even more value – speak to our experts at Servian who can help you navigate, design, deploy and deliver your next cloud solution.


For more FAQs watch the webinar for audience questions and answers. Thank you for joining us. For more webinars like this, join our Data-Driven Digital Community.


Need help?

Need help setting up Google Analytics 4? Have a look at our expert migration services to GA4 or read our white paper on how to set up Google Analytics 4 here.

Kirsten Tanner

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