Creating UTM Codes: A simple way to track campaign ROI

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Did you know 87% of marketers say data is their company’s most under-utilized asset? That’s not something to be taken lightly, considering businesses that use data-driven strategies drive five to eight times more ROI than businesses that don’t.

Website analytics play an essential role in measuring the effectiveness of your marketing efforts and understanding your customers better. If you have a website today, it is only to your benefit to take advantage of Google Analytics. Start tracking campaign ROI to eliminate guesswork and better allocate marketing spend. UTM codes are a simple yet effective way to pinpoint where traffic is coming from, ensuring results are attributed to the right content and campaign. 

What are UTM codes?

UTM (Urchin Tracking Module) codes were named after Urchin Software which was acquired by Google in 2005 and later rolled out as Google Analytics. Essentially, a UTM code is a query string you can add to the end of a URL to gather more detailed information about users who access the page. That information will then show up in Google Analytics, as well as any other analytics tools you use.

Here’s an example.

https://mzltd.com?utm_source=giveaway&utm_medium=QR&utm_campaign=conference_name

The first step to creating a UTM code is adding a question mark after the URL which signals to the analytics software that a string of UTM parameters will follow.

Next, include different parameters to get more granular data about where traffic is coming from. These parameters can be added in any order after the question mark, separated by ampersands.

  • Campaign (utm_campaign)—Identifies the campaign name tied to the link. If you don’t have any marketing campaigns, you could think of this parameter as grouping like sources (e.g. “printed_collateral”). In our example URL, it is a specific conference which could include a variety of associated materials, like landing pages for registration, follow-up emails, or promotional social media posts.
  • Source (utm_source)—Where traffic is coming from. This could be a social channel like Facebook or LinkedIn or a search engine such as Google or Yahoo. The URL above indicates that it is a giveaway associated with the conference.
  • Medium (utm_medium)—How the traffic is getting there (or through what channel). This goes a step further than the source, narrowing it down to a specific medium such as a QR code, banner ad, email or other.
  • Content (utm_content)—Describes the type of content traffic comes from. This is helpful for tracking how the same ad performs in a different size and page location, such as a sidebar versus a header.
  • Term (utm_term)—What term was used to access the page, such as a keyword you paid for in a PPC ad. It’s also useful for specifying CTA text if there are multiple CTAs within an email that link to the same URL.

In the URL example above, we used three parameters—the source is the giveaway, the medium a QR code, and the campaign would be the name of the conference.

Access your data in Google Analytics by navigating to Acquisition > Campaigns > All Campaigns. This will open a report that displays the acquisition data for all campaign names. You can sort through the data using the Primary Dimension filters at the top of the table to choose from Campaign, Source, Medium, Source/Medium, and Other.

Considerations and best practices.

Since there are multiple parameter options, UTM codes can get very disorganized quickly. Inconsistencies or too much repetition will clutter your data and confuse your team. Stick to these best practices to standardize campaign reporting and keep track of data better.

Create a naming convention.

Consistency is crucial when it comes time to analyze and sort through parameter data. Establish a naming convention from the start to organize reporting and enable easy data filtering. Since UTM parameters are case-sensitive, enforce lowercase so data isn’t splintered. Standardize any abbreviations, and when possible, use Google Analytics’ default channel grouping so that it will be easier to compare data.

In addition, make sure your team uses underscores and/or dashes to separate words—not spaces. Underscores should be used when you want to keep two words together so they’re read as one. It’s also good practice to create a spreadsheet record of who built the link and when so that if anyone has questions down the road, they know who to ask. This also makes it easy to identify existing naming conventions.

Avoid redundancy.

You don’t need to use all 5 parameters. If one is too similar to the other it’s probably not needed and will segment your data unnecessarily. On the flip side, don’t shy away from the content parameter since it’s optional. There are times when using this parameter will help you avoid making multiple campaigns when the data should ideally fall under one. For example, if you’re running the same ad but in different locations on a page, use the utm_content to specify the placement.

It’s also important to be specific. For example, if you’re running an annual campaign, always include the year to ensure data from previous campaigns won’t be mixed in with current ones.

Be careful with custom parameters.

Custom UTM parameters can be added to get more granular, accurate results if a certain attribute doesn’t easily fit into one of the five standard ones. However, having multiple custom parameters that are only used a couple of times will clutter your data and be too limited of a dataset to provide valuable insights. Only create a custom code if it’s a parameter you need regular reporting on, such as geolocation tracking or separate reporting for two sub-brands.

Here are a few examples of what a custom parameter would look like:

  • &brand=xyzbrand
  • &geo=chicago
  • &affiliate=john-smith

Start putting your data to use.

Strategize smarter by including UTM codes in your analytics approach. It’s a simple way to gain valuable insights into the effects of your campaigns and ROI. By sticking to naming convention best practices, your team will be able to analyze the data efficiently and make smarter marketing decisions faster.


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