Are you trying to solve any of these challenges?

  • Manage structured data for campaigns, content, product catalogs or other marketing data
  • Enrich your digital platforms (e.g. analytics, CMS) for better personalization and insights
  • Improve tracking code/Adobe CID classifications globally
  • Build an improved and standardized process in your digital advertising/media operations
  • Unify disparate internal and external teams/agencies around creating clean and uniform data
  • Trying to get a taxonomy implementation buy-in, including standardizing naming conventions across content and campaigns
  • Going through a digital transformation and not sure where to begin

If any of these issues are important to you, Claravine can help. Schedule a demo today.

Learn how the best brands master campaign tracking

Marketing success begins with good data. This guide shares the steps any organization can take to implement campaign tracking best practices and optimize spend based on richer insights.

This guide will cover important topics including:

  • How to align campaign measurement with strategic marketing objectives
  • How to enforce a consistent classification taxonomy across teams and channels
  • How to optimize digital marketing based on reported performance metrics

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Learn how we can help you instantly standardize your tracking and improve your data quality in ways that drive better decisions.

Google Analytics Campaign Tracking [for beginners]

At Claravine, we talk a lot about Campaign Analytics. And we usually assume that our audience understands the industry jargon we’re throwing around. After all, most Claravine clients found our solution well into their analytics journey. The typical organization won’t realize they need a solution for keeping their campaign tracking consistent until they already have a pretty big problem.

That’s changing a bit. With growing awareness of problems resulting from poor data quality (such as the impact on company revenue), we’re starting to speak with clients who are beginners and want to avoid data quality pitfalls from the outset.

If this describes you or members of your team, here’s a short lesson on Google Analytics (GA).

UTM Parameters 

First things first: GA is set up around UTM parameters. What are they, and why are they useful? At its most basic, a UTM parameter is a simple piece of data that gets added to a URL string.

Suppose you own a business website, and you plan to run a bunch of discount promotions this Spring. Would it be useful to know if your eventual buyers came to you from paid advertising efforts, social media, or an in-house customer database? If the answer is yes, GA’s UTM parameters will make that clear.

Standard Dimensions

There are five standard dimensions used in GA:

  • Source: the site where a customer interacts with your content, or where the referral comes from (e.g. Twitter, Facebook) 
  • Medium: indicates channel type; CPC is commonly used to indicate paid search; or it could be display advertising, email, social, etc.
  • Campaign: the unique identifier for this marketing effort, e.g, spring_discounts
  • *Term: indicates a paid keyword, or another level of detail if the keyword doesn’t apply
  • *Content: captures ad size, type, any distinguishing creative detail that you’re using for that customer interaction

*Term and Content are optional because they are used for paid traffic

The URL you attach to your ad could look similar to this:

Although there are several limitations to Campaign URL Builder that you should keep in mind, Google’s tool is a good resource if you want to try a little experimenting. If you’d like to see a best-in-class example, Claravine offers a solution allowing teams to do bulk creation of UTM parameters with validation included. We can verify the presence of the right GA property, on the page, before your campaign goes live.

Although Term and Content are optional fields, and you may not need them now, it’s a good idea to get into the habit of treating every field like it’s important — at some point, it could be very important. Skipping fields could result in eventual holes in your data.

Remember, these are the built-in reports that come standard with GA. There is an option to track additional, non-standard dimensions. Those will be under custom reports, and they are a topic for a different post. Everything I’ve described here applies to the built-in campaign reporting, and the standard parameters. They are things that beginners should be aware of.


So now you’re ready! Be sure to use the same campaign parameters for any campaign that’s running across multiple channels, (Twitter, Instagram, email). If you standardize the campaign name and vary the channel/source/medium information, you can compare across channels and by ad type. Maybe you’ll discover that a promo code works well in email, but mentioning a trade-in rebate works better for your social media posts.

At a higher level, as you look at a roll-up of how every channel is performing, the channel groupings will show you what data belongs with which channel.

Why is this important or useful? It offers insight into the results of various marketing efforts, relative to each other, which creates efficiency and leads to savings. If an inexpensive text ad performs as well as an elaborate banner ad, you may not need to hire that design firm after all.


One thing we have to mention here — even though this is a post for beginners — is auto-tagging. If you’re running paid search on Adwords (and if you’re a GA client, it’s very likely that you are), all the things we’ve mentioned in this post will happen automatically for your campaigns there, via auto-tagging. Adwords has a unique identifier that gets tagged to your campaigns.

This shouldn’t interfere with your ability to compare your AdWords data to other datasets (from Facebook, Twitter), if you’re using your parameters consistently.

As You Mature

If you find yourself someday in a situation where you run so many different types of campaigns that you need a more robust type of tracking, please come back and ask us about the kinds of classification data you can derive through an analytics system like Adobe. Adobe Analytics offers many more custom variables than GA, and no two implementations are the same. It will be a good problem to have because it will mean that you’re experiencing massive growth — and if you’re a beginner, it’s a topic for another day. Until then, check out our Digital Experience Data Management eBook to learn more about how to standardize and manage campaign tracking data and processes across your organization.

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