UTM Tracking or UTM codes are one of the ways for marketers to track the performance from pretty much any digital marketing campaign that uses links.

UTM stands for Urchin Tracking Module is a simple code that can be attached to any URL to generate Google Analytics data for digital campaigns. Specific to Google Analytics, UTM helps track the progress of the campaign on all online platforms.

The data from UTM codes can be tracked in Google Analytics through 3 main aspects; source, medium, and campaign. This allows Google Analytics to tell you where link clicks have come from, what campaign directed the clicks to your website and the medium in which those links were used.

A common utilisation of a UTM code is to create a unique URL for each campaign which can then be used across a range of digital platforms to provide insights into what and where your marketing is working the best.

The created URL or set of URLs can then be assigned to any marketing campaign which forwards users to your website. This enables Google Analytics to track the data from the various marketing campaigns, which enables comparative analysis of traffic and conversions for each campaign sources.

Setting up UTM tracking codes

In order to set up UTM tracking codes you first need to have your Google Analytics properly configured and receiving traffic data.

You must also have a general understanding of how the UTM tracking codes are created and used. This article is more of an introduction into what UTM tracking codes are so will not go in depth on the details.

We have compiled some information below to help you understand how they work, and provide some insight into how and where you might use them in your marketing however you may need some expert advice to implement these correctly if you have no experience in this area.

How UTM Tracking codes work

As mentioned earlier, UTM tracking codes are attached to a link to track the progress and success of your marketing campaigns. A UTM tracking code would look something like this…

https://teneighty.co.nz/?utm_source=facebook&utm_medium=paid_post&utm_campaign=winter_specials

So what does this mean exactly? Well in the link you will see that the source is Facebook, the medium is a Paid Post and the campaign is for Winter Specials. You could create another one for Instagram as the source and/or you could use one where the source might be a newsletter and the medium and button.

In each case, the campaign name would stay the same if each link was used for the same promotion and you will now be able to track the clicks from those links and analyse the success from each platform to get the best ROI with your marketing.

So lets jump in and get a better understanding of what it all means…

Campaign Name (utm_campaign): Required Field.
This is your unique identifier for the campaign you are running. You may use different mediums, sources, or content for an individual campaign, but your campaign name will be the same for all of these, allowing you to see which channels performed best within each campaign.

Campaign Source (utm_source): Required Field.
This identifies where the user clicked the URL, the source of the link, be it from your email newsletter, a button on the website, or another source like Facebook or Instagram.

Campaign Medium (utm_medium): Required Field.
This is the “thing” that contains the link and matches the medium you see in Google Analytics, The medium could be anything from paid ad, organic post, header banner, text link or button. Its pays to expand on it sometimes to make sure it makes sense when looking at the data so button might need to be more descriptive like buy tickets button or top banner, footer banner etc.

Campaign Content (utm_content): Optional Field.
This is most useful for A/B testing. For instance, you may be testing two versions of an email against one another, and in one you place the link in a button and in the other you use a text link.

One final tip when using UTM tracking codes is that you should really plan your strategy in advance and try to determine the channels and maintain consistency across the various metrics such as the source and medium so that you are not using a bunch of different names or references for the same thing. This will help to interpret the data a lot better and make more informed decisions when analysing the results.