Urchin Tracking Module (UTM) tracking is a parameter that can be added to a URL for tracking the performance of specific campaigns and identifying attribution paths for how visitors arrived on your website. This guide walks you through the types of UTM parameters Datadog RUM collects and how you can use RUM to monitor their use.

Data collected

UTM campaigns are connected to View events in RUM. The campaign data is collected automatically by the Browser SDK and can be viewed as facets in the RUM Explorer. The UTM parameters Datadog collects can be defined as the following:

view.url_query.utm_sourcestringThe parameter in the URL tracking the source of traffic.
view.url_query.utm_mediumstringThe parameter in the URL tracking the channel where the traffic is coming from.
view.url_query.utm_campaignstringThe paramter in the URL identifying the specific marketing campaign tied to that view.
view.url_query.utm_contentstringThe parameter in the URL identifying the specific element a user clicked within a marketing campaign.
view.url_query.utm_termstringThe parameter in the URL tracking the keyword a user searched to trigger a given campaign.

Use cases

Identify how users arrive at your site

To measure how users arrive at your site, you can use the ‘@view.url_query.utm_medium’ facet. This facet shows different mediums such as social, organic, search, Google campaigns, or even specific events like a webinar. You can watch session replays from users who come to your website from different mediums and observe if any noticeable patterns occur between various groups.

Track whether certain campaigns are higher traffic than others

Screenshot of all views to a given campaign page

In the above query, we can count all views of a page, such as the landing page, where the campaign is running. This can help you understand if certain pages are getting more visits and you should increase advertising spend toward that specific page.

Analyze a UTM source by country

Screenshot of UTM source by country

In this example, you can track the different sources of campaigns like advertisements versus organic traffic. You can then add an additional layer, like geography, to understand if viewership patterns change by country.

Further Reading

Additional helpful documentation, links, and articles: