In analytics as in programming, naming is one of the biggest issues. And UTM tags are one of the first things that one can mess up.

Most people ignore UTM, but you do so at your peril. Properly set up, UTM tags allow you to measure the effects of individual campaigns, channels, and even variations of tests for e.g. landing pages & emails.

Here's how to set up smart UTM taxonomies such that you can put UTM to work for you.

A caveat about prior data

In UTM as in much of the rest of GA, you can’t back-fill data that hasn’t been properly reported. So if you’re going into this lesson expecting to salvage your years of busted UTM data, unfortunately you will need to cut your losses and move on.

Once you get your UTM house in order, I recommend placing an annotation in GA to make sure you know when to start analyzing your data. Otherwise, you might end up analyzing all of the busted data that you were gathering beforehand.

And finally, you’re still going to gather busted data – at least for a while. UTM cuts both ways: you can create the best taxonomy in the world, but ultimately your data is only as good as the UTM queries that you build, promote, and QA.

The breakdown of UTM query parameters

For those in the back, UTM queries are broken into 3 required parameters: source, medium, and name. Two more, terms (for e.g. keywords) & content (for e.g. variations of a similar campaign), are optional.

When you’re starting out, you only need to focus on the three required parameters for your UTM queries.

Sources

UTM query sources correspond to the name of the source that you’re getting traffic from. For example, any affiliate link you have should have the medium set up as affiliate_link (see below), and the source set up as the name of the source (jane_doe, for example). In practice, you should have at least the following sources:

• google
• facebook
• instagram
• twitter
• linkedin
• All mailing list segments
• All affiliates
• All guest blog & podcast outlets
• All media referrals, if possible

Mediums

Mediums represent the format that your links are coming from. They should include the following at a minimum, where applicable:

• email
• instagram
• instagram_story
• google_ad
• facebook_ad
• facebook_page
• facebook_post
• twitter_bio
• twitter_ad
• twitter_post
• affiliate_link
• linkedin
• linkedin_post
• guest_blog
• guest_podcast
• guest_conference

These should be self-explanatory; add or subtract to taste, and make sure you’re representing every key source of traffic that you happen to be acquiring at any given time.

To sum up, the difference between source and medium is like the difference between the publisher and the platform. For example, for an article that links you on the New York Times, your source would be nytimes and the medium would ideally be website (for the site), app_ios (for a link from the Times’ iOS app), app_android (for the same from Android), etc.

Names

Here, the name corresponds to the specific campaign. Each ad campaign, referral source, etc should have its own discrete name. I typically use names that correspond to specific campaigns first, separated by underscores and all lowercase (so they can render easily in URLs). For example:

• summer2019reactivation
• summer2019reactivation_longform
• summer2019reactivation_email

Putting together a consistent taxonomy of names is hard, but do keep in mind that your names should map cleanly to your source and medium – unless you encounter an edge case-y, at-scale situation where you have the same campaign, with the same exact content, coming in through multiple outlets at once. (Think the same ad, run through multiple websites, on multiple podcasts, etc.)

Appending UTM as a standard operating procedure

Every link you hand to an affiliate, post to an ad, or create on your own guest collateral should have a unique UTM query that correctly identifies the traffic that you’re getting from each source.

Here’s Google’s UTM query builder. Bookmark it and use the heck out of it.

UTM Audits

Finally, remember that UTM audits should be performed on at least a quarterly basis, in order to ensure that you’re still getting clean data.

You can’t guarantee that people aren’t stripping the UTM parameters before posting your link, either, so you should always follow up with any partners or ad outlets to ensure that your links are being posted such that you’re able to more clearly measure their effectiveness.

Wrapping up

UTM is hard to get right, and your own query taxonomy is going to be wholly unique to your store and its promotional needs. Through this tutorial, you should have an understanding of how to create UTM query parameters, append them to your campaign links, QA them to ensure that your data is properly firing, and audit your UTM writ large to make sure you can act on the data you’re getting.

In UTM as in the rest of analytics, you’re only really as good as the quality of your data. And UTM is easy to screw up, with a signal:noise ratio built-in by default (customers stripping GET queries off their links before pasting, etc). With this tutorial, you can mitigate the adverse impact of fuzzy UTM data collection and get back to acting on your analytics’ insights.

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