How To Collect Clean Data In Your Digital Marketing Efforts

Table of Contents

Introduction

We often encounter clients with very messy data when it comes to CRM systems as well as platforms like Google Analytics. Messy data is hard to pull, sort, organize, and analyze. Thankfully, there are several solutions to this widespread but often overlooked problem.

This article will ultimately help you keep your data clean and highly functional.

Google Ads

Google Ads is case sensitive, which can cause problems with campaign names and ad groups. Let’s look at an example of how we can write out an ad group name.

  • Red Running Shoes
  • Red running shoes
  • red running shoes

All of these ad groups have exactly the same name, aside from the way they’re capitalized. If we upload builds with these variants, Google Ads will create 3 different ad groups. As you’re growing an account and uploading more keywords into the same ad group, you can mistakenly create duplicate ad groups, and your keywords will be wrongfully segmented.

Best Practice: Use only lowercase

**Note: proper case formatting is also no good because mistakes can often be made with acronyms such as USA, LA, NYC and so on.

UTM Parameters

UTMs are pieces of text that are added to the URL and can then be picked up by platforms for tracking purposes. UTM parameters originate from Google Analytics’ predecessor Urchin and are now used most commonly with GA. However, they can also get picked up by tons of other platforms such as CRMs.

Capitalization

Google Analytics is also case sensitive. So, to keep your data clean, apply the same best practice from Google Ads. Don’t use uppercase letters in your UTMs in order to avoid possible duplicate entries.

Spaces

Avoid using spaces, since URLs naturally don’t have spaces in them. In order for a UTM parameter to get around that, “%20” is inserted in the URL where the space is supposed to be. But this will cause issues further down the line. Not every platform out there will pick this up properly, and if you’re analyzing URL level data, it can get confusing. Just use “_” instead if you want to have multiple words in a UTM parameter.

Special Characters

Special characters are not always registered properly. One example we see particularly often is “+” which appears in the BMM match type (eg. +red +running +shoes). This comes back as an empty space. What you get is keyword tracking which looks like this “ red running shoes”. This is a Salesforce and Pardot problem. Just don’t use them.

We highly encourage the use of the default parameter options used by Google Analytics.

Sources

  • Google
  • Facebook
  • Bing
  • Etc.

Mediums

  • Organic
  • Cpc
  • Email
  • Referral
  • Etc.

The problem with creating your own versions of these is that your data will start getting split up and going all over the place in Google Analytics. Google Analytics naturally attributes traffic to sources and mediums, without your use of UTM parameters. However, this doesn’t always work perfectly, so it is advised to add UTM parameters to all of your URLs. Only make up your own naming convention if you’re sure that this traffic does not fit into anything that Google Analytics has already thought of. An example of this would be something like a link you posted on a Reddit thread (something obscure). Then you could have utm_source=reddit & utm_medium=thread as some quick examples.

Conclusion & Best Practices Summary

At this point, we’ve gone through every best practice for keeping your data clean. To avoid data issues, these methods should be followed when naming anything related to digital content, which can include campaigns, ad groups, UTMs, tracking templates, etc.

Here they are again in list format:

  1. Only use lowercase
  2. Don’t use spaces
  3. Don’t use special characters
  4. Use GA default UTM naming conventions everywhere possible

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