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Find things in the GOV.UK GA4 data

This page is a work in progress.

Google Analytics 4 (GA4) is used to collect data on the usage of GOV.UK. There are a variety of different things you can learn from the GA4 data about pages and users on GOV.UK.

This page provides some guidance on how to find commonly requested information in the GA4 data.

More information on the data source itself can be found on the GOV.UK GA4 data source page.

Page views

There is a report in the GA4 interface which shows views by page path. In explorations and in Looker Studio, you can get numbers of page views either using a count of page_view events or using the ‘views’ metric (which also includes screen views if you have an app).

A count of page_view events in GA4 should provide you with a similar number to the total pageviews figure in Universal Analytics (UA).

‘Unique pageviews’ no longer exists as a metric in GA4, but the ‘sessions’ metric is conceptually similar, telling you how many sessions contained a visit to this page. However, the definition of a session has changed in GA4, so the figures produced here will deviate significantly from those in UA.

Page views by page path

We recommend using ‘page path’ over the ‘page location’ dimension as ‘page location’ is compatible with fewer other dimensions.

The ‘page path’ is the part of the URL after the hostname (not including any query strings) of a page.

Method - using the views metric in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Page path and screen class’ dimension and the ‘Views’ metric
  2. If you would like to only look at page view data for certain pages, filter the data using the ‘Page path’ dimension to select the paths of the pages you are interested in. For example, if you were only interested in ‘browse’ pages on GOV.UK, you could filter down to Page path contains ‘/browse’
  3. Change the date range and sort the table however you like

Remember to check the data quality icons when using reports or explorations in GA, and to keep an eye open for the impact of our high cardinality data in Looker Studio.

For an example in Looker Studio, see the ‘Top pages’ table in this sample Looker Studio report.

Method in BigQuery

The following SQL gets a count of page views by page path (cleaned_page_location in the flattened dataset) for the 1st January 2024:

SELECT
  cleaned_page_location,
  COUNT(*) AS pageviews,
FROM
  `ga4-analytics-352613.flattened_dataset.flattened_daily_ga_data_*`
WHERE
  _TABLE_SUFFIX BETWEEN '20240101'
  AND '20240101'
  #Filter to just page_view events
  AND event_name = 'page_view'
GROUP BY
  cleaned_page_location
ORDER BY
  pageviews DESC

Link clicks are now tracked as events with the event name ‘navigation’. External links will be navigation events with the ‘outbound’ parameter/custom dimension set to ‘true’. Internal links (links to other pages on GOV.UK) will not have the parameter/custom dimension ‘outbound’ equalling ‘true’. Not all internal links have specific tracking on them.

These events should all have dimensions such as the ‘Link URL’, ‘Link text’ and so on which should help you identify which links have been clicked.

External link clicks on a given page

Method in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Link text’ or ‘Link URL’ dimension by the ‘Event count’ metric
  2. Filter the data by the ‘Event name’ dimension to equals/contains ‘navigation’. This selects the navigation event which fires when the user clicks a link
  3. Filter the data by the ‘Outbound’ dimension to equals/contains ‘true’. This selects link clicks away from GOV.UK
  4. Filter the data by the ‘Page path and screen class’ dimension to equal the path of the specific page you want link clicks from. The ‘page path’ is the part of the URL after the hostname (not including any query strings) of a page, so by using it here we are selecting the page the user clicked the link on
  5. Change the date range and sort the table however you like

A basic exploration containing external link clicks from GOV.UK can be accessed here. See also the ‘External link clicks’ table in this sample Looker Studio report.

Method in BigQuery

The following SQL returns external links clicked (and how many times they were clicked) on the ‘Child adoption’ page on 1st January 2024:

SELECT
  link_url,
  COUNT(*) AS events,
FROM
  `ga4-analytics-352613.flattened_dataset.flattened_daily_ga_data_*`
WHERE
  _TABLE_SUFFIX BETWEEN '20240101'
  AND '20240101'
  #Filter to just navigation events
  AND event_name = 'navigation'
  #Filter to just external link clicks
  AND outbound = 'true'
  #Filter to just the page of interest
  AND cleaned_page_location = '/child-adoption'
GROUP BY
  link_url
ORDER BY
  events DESC

File downloads

File downloads will have the event name ‘file_download’.

File downloads of a given file

You can count downloads of a file, regardless of which page the file was downloaded on, by using the file_download event and Link URL.

Method in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Link URL’ dimension by the ‘Event count’ metric. Alternatively, you could add in the ‘Page path and screen class’ dimension to show you which pages your file is downloaded from, or the ‘Link text’ dimension to show you which text is clicked to download your file
  2. Filter the data by the ‘Event name’ dimension to equals/contains ‘file_download’. This selects the file_download event which fires when the user clicks on a link to download a file
  3. Filter the data by the ‘Link URL’ dimension to equal the URL of the specific file you want to find downloads of
  4. Sort the table however you like

File downloads on a given page

You can find all file downloads from a given page by using the file_download event and filtering to the desired page path.

Method in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Link text’ or ‘Link URL’ dimension by the ‘Event count’ metric
  2. Filter the data by the ‘Event name’ dimension to equals/contains ‘file_download’. This selects the file_download event which fires when the user clicks on a link to download a file
  3. Filter the data by the ‘Page path and screen class’ dimension to equal the path of the specific page you want downloads from. The ‘page path’ is the part of the URL after the hostname (not including any query strings) of a page, so by using it here we are selecting the page the user clicked the download link on
  4. Sort the table however you like

Method in BigQuery

The following SQL gets a count of file downloads for the different files (using the Link URL) on the ‘Apply for a postal vote (paper forms)’ page on 1st January 2024:

SELECT
  link_url,
  COUNT(*) AS file_downloads,
FROM
  `ga4-analytics-352613.flattened_dataset.flattened_daily_ga_data_*`
WHERE
  #Filter to the right date
  _TABLE_SUFFIX BETWEEN '20240101'
  AND '20240101'
  #Filter to just file_download events
  AND event_name = 'file_download'
  #Filter to just the page of interest
  AND cleaned_page_location = '/government/publications/apply-for-a-postal-vote'
GROUP BY
  link_url
ORDER BY
  file_downloads DESC

Search terms

The ‘Search term’ (or search_term, if using the BigQuery data) dimension is sent with:

  • the ‘search’ event - when the user searches
  • the ‘view_item_list’ event (ecommerce tracking) - the view of the search results page
  • the ‘select_item’ event (ecommerce tracking) - when the user selects a search result
  • the ‘page_view’ event - only populated on page views of search results pages

These different events sent with the search term should enable you to analyse which terms users are searching for, and what users do after searching for various terms. The fact the search term is sent with many events does however mean you need to filter to the event you are interested in to make sure you are not accidentally double or triple counting the search terms used.

A basic exploration containing search terms used on GOV.UK can be found here.

Search terms used to get to a specific destination page

Method in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Search term’ dimension by the ‘Event count’ metric.
  2. Filter the data by the ‘Event name’ dimension to equals/contains ‘select_item’. This selects the select_item event when a user clicks on a search result.
  3. Filter the data by the ‘Link URL’ dimension to equal the path of the specific destination page you want search terms to. The ‘Link URL’ is the link the user clicked on from the search results, so by using it here we are selecting the search destination page.
  4. Change the date range and sort the table however you like!

This should give you a table showing the search terms used to get to your given page.

If you are unfamiliar with filtering GA4 data, it may be helpful to include the dimensions in your table to check that your filters have worked correctly (you should only be able to see ‘select_item’ in the ‘Event name’ column and the specific page you want search terms from in the ‘Link URL’ column).

For an example in Looker Studio, see the ‘Searches leading to these pages’ table in this sample Looker Studio report.

Search terms from a specific page

There are a couple of different ways that this can be done with the GA4 data.

Method one - using the search event in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Search term’ dimension by the ‘Event count’ metric
  2. Filter the data by the ‘Event name’ dimension to equals/contains ‘search’. This selects the search event which fires when a user searches
  3. Filter the data by the ‘Page path and screen class’ dimension to equal the path of the specific page you want search terms from. The ‘page path’ is the part of the URL after the hostname (not including any query strings) of a page, so by using it here we are selecting the page the user searched on
  4. Change the date range and sort the table however you like

This should give you a table showing the search terms used from your given page and the number of times each was searched for (the count).

For an example in Looker Studio, see the ‘Top searches from these pages’ table in this sample Looker Studio report.

Method two - using the view_item_list (search results) event in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Search term’ dimension by the ‘Event count’ metric
  2. Filter the data by the ‘Event name’ dimension to equals/contains ‘view_item_list’. This selects the view_item_list event which fires on views of search results lists
  3. Filter the data by the ‘Page referrer’ dimension to equal the specific page you want search terms from. The ‘page referrer’ is the page which led the user to their present page, so by using it here we are selecting the page before the search results
  4. Change the date range and sort the table

This should give you a table showing the search terms used from your given page and the number of times each was searched for (the count).

If you are unfamiliar with filtering GA4 data, it may be helpful to include the ‘Event name’ and ‘Page referrer’ dimensions in your table to check that your filters have worked correctly. You should only be able to see ‘view_item_list’ in the ‘Event name’ column and the specific page you want search terms from in the ‘Page referrer’ column.

Method in BigQuery

The following SQL gets a count of search terms used in searches on the ‘Sign in to your Universal Credit account’ page on 1st January 2024:

SELECT
  search_term,
  COUNT(*) AS searches,
FROM
  `ga4-analytics-352613.flattened_dataset.flattened_daily_ga_data_*`
WHERE
  #Filter to the right date
  _TABLE_SUFFIX BETWEEN '20240101'
  AND '20240101'
  #Filter to just search events
  AND event_name = 'search'
  #Filter to just the page of interest
  AND cleaned_page_location = '/sign-in-universal-credit'
GROUP BY
  search_term
ORDER BY
  searches DESC

Engagement

There are a variety of metrics available to help you look into user engagement with content on GOV.UK.

Bounce rate

The definition of a bounce has changed from Universal Analytics to GA4. The bounce rate is now the percentage of sessions that are not engaged sessions (the bounce rate is the inverse of the engagement rate). Engaged sessions are all sessions that either last longer than 10 seconds, have more than one screen or page view, or contain a conversion event (ordinary events do not count and as of March 2024 we do not yet have any conversion events set up).

It is important to note that the bounce rate can only be used when reporting on landing pages (using the ‘Landing page + query string’ dimension). Do not use the bounce rate metric with more general page dimensions (such as ‘Page path and screen class’, ‘Page path + query string’, ‘Page location’ and so on). Although GA does not prevent you from adding bounce rate to such reports, the figures reported will not be accurate!

Method in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Landing page + query string’ dimension by the ‘Bounce rate’ metric
  2. If you are interested in the bounce rates for specific pages, filter the data by the ‘Landing page + query string’ dimension to equal/contain the path of the specific pages you want. The ‘Landing page + query string dimension’ only uses the path and query string - the part of the URL after the hostname
  3. Change the date range and sort the table however you like

A basic exploration showing the bounce rate on GOV.UK landing pages can be found here.

User and tech attributes

There are a variety of dimensions available to help you understand the attributes of users using GOV.UK.

Device category

The device category tells you whether a user was using a desktop, mobile, tablet, or other device to browse GOV.UK.

Method in an exploration

Steps:

  1. In an exploration, create a table showing the ‘Device category’ dimension by the ‘Sessions’ metric
  2. If you are interested in the device categories used on specific pages, you could filter the data by the ‘Page path and screen class’ dimension to equal/contain the path of the specific pages you want. This would then tell you the devices used in each session that included a view of the selected page
  3. Change the date range and sort the table however you like

Sorting and ordering data

You can sort the data in your exploration by clicking on the value column headings you wish to sort the data by.

This page was last reviewed on 1 May 2024. It needs to be reviewed again on 1 November 2024 .
This page was set to be reviewed before 1 November 2024. This might mean the content is out of date.