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UTM Naming Convention: Unbinding Multi-Regional Marketing Analytics the Improvado's way

UTMs are a common practice for marketers managing cross-channel campaigns. However, UTM tagging becomes a top priority for teams that promote their products across different markets and regions.

Without a well-thought UTM naming convention, teams can't track the efficiency of their ad spend. In other words, they don't know which exact campaign, channel, banner, or product generated a conversion. Add in the costs to launch untrackable campaigns across multiple regions, and we'll end up with tens of millions of dollars that can't be attributed to any conversion.

Surprisingly, it's quite a frequent case for enterprise-level companies to ignore naming conventions and even UTM tagging as a whole. From our experience, in 30% of cases, large companies spend marketing budgets with no chance to track their effectiveness.

By using UTM tags based upon a well-designed naming convention, you ensure that your cross-channel marketing analytics works as it should, and you can assess the impact of each marketing dollar on your revenue growth. 

While helping our clients develop, audit, and adjust their UTM naming conventions, we've drawn several lessons:

  • There's no such thing as a perfect naming convention.
  • Everybody says that following a naming convention is important, but only a few really understand the real value behind it.
  • It takes a lot of effort to ensure that all third-party vendors, freelancers, and even in-house employees follow the convention.

This article revisits a well-known but controversial topic of UTM naming conventions and shares Improvado's best practices for UTM tagging.

Choosing a naming convention model

Cryptic model

Positional model

Key-value model

UTM macros to automate campaign tracking

Advanced UTM practices
Learn how to amplify your marketing analytics and better understand your leads with our guide to advanced UTM practices

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Choosing a naming convention model

Companies stick to these three models when creating UTM tags:

  • Cryptic model
  • Positional model
  • Key-value model

Each of them has its strengths and weaknesses. Let's review them and find out why we settled on the key-value model.

Cryptic model

With the cryptic mode, your campaign name turns into an encrypted ID which may look like this: "utm_campaign=123581faj19fmv9910653fq". To decipher the code, you need to compare it with the lookup file to convert the code into a readable classification.

Pros:

  • Protects your UTM tags from being read by outsiders
  • The ID remains the same even after you change the campaign name

Cons:

  • The structure is barely readable to your team members
  • Impossible to create a UTM tag or check its correctness without a lookup spreadsheet
  • A deciphering spreadsheet packed with codes is hard to navigate and often freezes your computer

Verdict: To achieve maximum efficiency with the cryptic model, companies need additional tools and well-designed tech infrastructure to run the process smoothly. Otherwise, UTM tags are prone to human errors.

Positional model

It's one of the most common UTM tagging methods where you line up all attributes and separate them with a delimiter.  

For example:

en_20072022_li_social_paid_summersale

The example tracks language in the first position, the campaign launch date in the second, then the channel (LinkedIn), the campaign medium, the campaign type, and, finally, the campaign topic.

Pros:

  • A much more readable model since it doesn’t require additional files to decipher the code.
  • Easier to check the correctness of attributes.

Cons:

  • The model is dependent on the order. If one of the attributes is missing, you can’t track overall campaign performance.
  • Each position should be filled, even if it doesn’t apply to the campaign. Some parameters may look like “_na_na_”.
  • It requires memorizing which position stands for what.
  • Each new attribute makes the tag harder to read and create.

Verdict: The model is feasible for entry-level analytics but should be revised with the increasing complexity of campaigns.

Key-value model

This is the model we find the most flexible, convenient, and the one we use on a day-to-day basis at Improvado. 

The naming convention includes:

  • An attribute code. For example, "cid" stands for campaign ID, "pr" stands for the product name.
  • An attribute value. For example, "tw" for Twitter, "li" for LinkedIn.
  • A delimiter between codes and values. They are usually separated with a hyphen "-". For example, "pr-backpack".
  • A delimiter between each code-value pair. Different teams use "!", ":", "|", and other delimiters. For example, "la-en|pr-backpack".

Pros: 

  • The model neither depends on complex spreadsheets nor on the position of attributes in the tag.
  • Readable by design, both for humans and machines.
  • The ordering doesn’t matter.
  • No need to fill in all attributes all the time.
  • It’s more suitable for dashboarding.

Cons:

  • The model is harder to type because it’s easy to miss a delimiter.
  • You still need to learn the meaning behind your attributes.

Verdict: Considering all the benefits of this model, we find it the most effective for marketing analytics. It’s readable, scalable, easy to automate with UTM macros (which will be covered later), and, ultimately, good for any activities that require comprehensible keys and grouping.

Since this model is more machine-processing-friendly, it's easier to use it for dashboarding. For example, you can create automatic drop-downs in Data Studio and filter the entire dashboard based on the required attributes.

UTM macros to automate campaign tracking

There are two main reasons behind errors in UTM tags:

  • Marketers aren’t thoroughly aware of their own naming conventions
  • Marketers have to fill in parameters manually and make mistakes in the process

Macros solve both of these problems. They are essential for companies that are knee-deep in UTM tags.

UTM macros provide the following benefits:

  • No need to manually crunch various campaign parameters
  • A minimal chance of human error when creating a new UTM tag
  • Less time wasted on creating UTM tags for new ad campaigns

Here's a macro example that we use to track Google Ads campaigns:

{lpurl}?utm_source=google&utm_medium=cpc&utm_campaign=n-discovery-usa&utm_content=cid_{campaignid}|gid_{adgroupid}|adid_{creative}|phid_{targetid}&utm_term={keyword}&placement={ifsearch:search}{ifcontent:display}content={creative}

Let's decompose it into separate parts:

  • {lpurl} stands for the URL of the landing page visited by a user.
  • utm_source, utm_medium, and utm_campaign are custom-set parameters that you can define before launching your campaign.
  • cid_{campaignid} attribute automatically retrieves the campaign ID.
  • gid_{adgroupid} attribute automatically retrieves the ad group ID.
  • adid_{creative} attribute automatically retrieves content used in the ad.
  • phid_{targetid} returns the ID of the keyword.
  • utm_term={keyword} returns the exact keyword that matches the search query.
  • placement={ifsearch:search} lets you know that your ad was clicked from a site in the Google Search Network
  • {ifcontent:display} lets you know that your ad was clicked from a site in the Google Display Network
  • content={creative} returns a unique ID for your ad.

Macros will gather all this information for you. All you have to do is enter them into the required field in your ad platform.

A proper UTM naming convention defines your place on the market

A well-thought naming convention makes a difference between making informed campaign decisions and draining ad budget into nowhere. UTM tags are crucial for data-driven attribution, bidding strategy alignment, and all kinds of marketing analytics needs.

Improvado can help you create a naming convention tailored to your industry and marketing use cases. With a proper naming convention and UTM audit dashboard, you can focus on campaign analytics and precisely track the efficiency of your marketing dollars. 

Get in touch with Improvado to discuss your marketing analytics needs.

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