Understanding and using GA4’s default reports

The reports section in GA4 is where you will do the majority of all your day-to-day reporting. It has a number of perks such as never sampling your data (unlike in explorations), and having all your historical data (regardless of your data retention setting).

Although the reports menu can be completely customised per property, the out-of-the-box reports hold a lot of value and benefits. The ‘vanilla’ version of GA4 has the following sets of reports:

GA4's UI showing the reports menu and all the avalible default reports

You may see more or less than this, and that’s absolutely fine! Depending on what you’re tracking, what accounts you have linked and what’s been changed, this can be unique for every property.

Before we look at each section, it’s worth explaining that there’s two types of reports in GA4:

  1. Overview reports – a dashboard consisting of summary charts and tables
  2. Detail reports – a few charts and a detailed data table

Reports snapshot

This is the ‘landing page’ for the reports workspace and is an overview report. It does a decent job of giving an overview across all the data streams and events you’re collecting into the property, but nicely includes plenty of links to the detailed reports to drill into more detail as and when needed.

Possibly the most useful charts on this report are the top three. The first is the trend for some key metrics such as total users, engagement time and revenue:

GA4 line chart showing users, new users, engagement time and revenue by day

And the other two charts are a sample of real-time data and the automatically generated insights.

GA4 real time chart and insights automatically generated from GA's machine learning


The real-time report does what it says on the tin – well sort of. It looks at the last rolling 30 minutes of data that has been collected. The reason I say ‘sort of’ is that there can be a short delay in some data getting into GA’s servers, so although it says it is ‘real time’, it’s not as real time as it could be!

Other than the interactive map (which can be fun and interesting), the main thing to see on this report is the views by page, and events by event name:

Two GA4 charts looking at real time data - one looking at views my page title, and the other looking at event count by event name

The views by page can be useful for seeing what pages are being viewed, especially interesting if you push a new campaign live, send an email, etc. to see what pages are being seen almost instantly.

The events by event name is the star of the show though. As this is a view of what events are being collected, it can be one of the most useful ways to check that a new bit of event tracking has been set up correctly, and is working.

Life cycle

The life cycle collection contains the largest set of reports by default in GA4. It is designed to give a full view of the users from how you got to your website/app, what they did on them, how/if you made money from them, and whether or not they came back again.


This set of reports is designed to explore how you brought the users to your website and/or app. What marketing channels were used, what worked best, what converted and what brought the best results in the long run.

The traffic acquisition report is by far the most used report in this section.

GA4's UI showing the reports menu with the life cycle > acquisition section expanded

The line chart at the top of the report gives a great view on the trend of each channel, and can identify any peaks or troughs, or even seasonality by channel.

GA4 line chart lookin at marketing channel traffic by date

The data table is the main reason for using the detail reports though. And in this report, we’re looking at the performance of traffic by marketing channel (although we can drill into the campaign, etc. too).

A valuable metric to see in this report would be the engagement rate. This gives a great measure of the quality of the traffic you’re receiving from each marketing channel, campaign, platform, etc. There is no ‘good’ or ‘bad’ engagement rate, but viewing this metric in context against the other channels is a good way to see what works better and worse for your audience.

GA4 data table showing the average engagement time by marketing channel

For example, in the data above we can see that email is highly engaged with, yet paid social is not. This could be due to a number of factors, such as that the paid social ads could be better targeted for our engaged audience, or that the copy could be clearer or improved to prevent people clicking through that might not be interested in what they have to offer.


The engagement reports are looking at what the users did on your website/app after you acquired them. What pages/screens did they see, what events did they trigger and did they convert or not.

GA4's UI showing the reports menu with the life cycle > engagement section expanded

The two main reports in this section are the events report and the pages and screens report. The events report is pretty much the nuts and bolts of GA, and as close as we get to seeing the raw data in the UI.

GA4 data table showing the event count and total users by event name

Any event that GA collects will be shown here with a count, users and count per user. Each line of this report has a different context – the event count for the page_view event is the total pageviews, and the event count for the session_start event is the total sessions for example.

Almost all reports in GA can be made from this single report, however it can be a bit of a chore at times. That’s why there’s a default report for the pages/screens to save us the time!

GA4 data table showing views, users and engagement time by page title

This report nicely includes things like the average engagement time to see how long people spend engaging with each page on average. As well as the number of views and view per user can help build a good picture of what pages are being seen, and engaged with from your audience.

Note: This report defaults to using the page title, but you can swap this out for the page path easily if you prefer seeing the page data that way.


Monetisation is a generic term for three ways to earn revenue from your website/app:

  1. Ecommerce – selling stuff
  2. In-app purchases – selling stuff via the App/Play Store (iOS and Android only)
  3. Publisher ads – earning money from serving ads on your site

Each of these three ways of earning revenue have their own detail report, but not all properties will have data for all three. Or you may be a B2B business and have nothing in any of these reports!

GA4's UI showing the reports menu with the life cycle > monetisation section expanded

Each of these reports have their merits if you earn revenue that way. But I have to call out the ecommerce report and it’s scatter chart at the top that can help quickly see big changes in add to basket rates by product:

GA4 scatter chart showing each ecommerce item by product views and add to carts

And of course the data table that ultimately give a view of the product funnel – from view, to add to cart to purchase:

GA4 data table showing views, add to carts and purchases by ecommerce item/product


The retention report is a single report and sometimes appears as “Retention” or just “Overview” for some reason in the menu.

It’s just an overview report, but it does have some valuable charts to look at – the user retention and user engagement specifically:

Two GA4 charts showing user retnetion over time for the last 42 days - one looking at pecent of all users, and the other looking at the engagament time of returning users

The user retention chart shows the percentage of users who return to the site/app each day in their first 42 days after visiting for the first time. Personally, I’d have excluded the 100% user retention on ‘day 0’, but hovering on the chart shows the percent of all users that return to the site/app. Here you can see how things like basket abandonment emails after 2 days affects the likelihood of a user returning, or if there is an organic seasonality such as people doing their grocery shopping on the same day every week.

The user engagement chart shows pretty much the same thing, but now looking at how long the returning users spend on your site/app when they return. Do your users invest more time the more they come back, or does it tail off?


The user collection of reports has two sections, each containing an overview and a detail report:

  1. Demographics – geography, age, interests, etc.
  2. Tech – device type, operating system, browser, etc.
GA4's UI showing the reports menu with the life user collection expanded

I’ll just straight into the detail reports, as I find these the most useful in this section. Starting with the demographics details, which is a good place to come for understanding the location of your users. For example, you can include the secondary dimension of ‘Region’ for a breakdown of each country. You could include ‘City’ but there are some accuracy issues in that data (not just a GA-thing), which means I tend to steer clear of using.

GA4 data table showing the traffic by country and region

The tech details report has a few hidden but very useful surprises that can be valuable to use from time to time. For example, if you are collecting data from websites and iOS/Android apps, the combined dimension ‘Platform/Device category’ is a must-use. It can be an easy way to see how many of your users are using the app versus the mobile version of the website:

GA4 data table showing users by platforma dn device type - highlighting where mobiole users are using the app or website

And other not so used dimension in this report is the screen resolution. There’s likely to be a lot of variations in this report, but even just looking at the top 10 rows can give you a strong sense of how big the website/app is being seen as. For example, should you be primarily designing for smaller screens, or larger.

GA4 data table showing users by screen resolution

You can also tell if your website/app is being seen in portrait or landscape – something that can be more easily looked at in Looker Studio using a simple formula.

Written by

Daniel is the innovation and training lead at Measurelab - he is an analytics trainer, co-host of The Measure Pod analytics podcast, and overall fanatic. He loves getting stuck into all things GA4, and most recently with exploring app analytics via Firebase by building his own Android apps.

Subscribe to our newsletter: