In my last two articles in this series, I stressed the importance of a strong analytics foundation as well as building the necessary blockades to restrict spam and referral bots from affecting your data integrity. While that is usually enough to get you to the point of trusting your analytics, there is some data that crosses your path in Google Analytics reports that likely have you scratching your head. In fact, there seems to be something new every year that pops up. The latest offenders are query parameters and campaign tracking.
How to exclude unneeded query string parameters in Google Analytics
Query strings are added to the base of a URL in order to serve content more quickly, track specific information, or to pass data to or from a form. Most websites aren’t immune to this practice since it can arise when using common functions like search features, filtered lists, passing ecommerce product variants, Google’s pre-defined UTM tags, email campaign tags, optimization tracking, marketing automation tracking, and content management functions.
While this is often a very useful practice, Google Analytics considers these URLs as unique, separate pages due to the unrecognized tracking parameters that are tacked on to your normal URL strings. If your website uses query string parameters, you may be creating hundreds or thousands of unique page views which don’t actually exist.
For example, you may have a number of scenarios for just one page:
In this case, if you wanted to track the bounce rate of that specific page, you’d have to calculate it manually across all instances above.
A simple way to fix this is to ask Google Analytics to stop tracking the query string URLs as unique pages.
Easily check if query strings are skewing your data pulling up a report in Google Analytics under Behavior > Site Content > All Pages and search for all pages with a question mark (?).
Once you have an idea of what Google is tracking, you’ll want to decide if you want Google to track those as unique pages or as one page.
In order to remove the query strings from your reports, you can do so under Admin > View Settings (preferably under your filtered view) and include the parameters you would like to exclude, separated by a comma:
How to update rogue UTM naming conventions in Google Analytics
Another anomaly that you may come across are rogue UTM parameters in your reports caused by typos, capitalization, or misuse. If you’re running any type of campaign, we always recommend setting up UTM parameters to pull in source, medium, and campaign name data to track the effectiveness of your campaigns. The best way to manage these is by setting up a naming convention and track them via Google Tag Manager.
However, in some cases, you may see data in your reports that might not be familiar or is incorrect. There are a couple ways this might happen:
- Google Analytics reads lowercase and uppercase as two different characters. One of your co-workers might tag an email campaign with utm_medium=Email, while you tag it with utm_medium=email. In this case, Google Analytics would register two different media for the email campaigns.
- If you find unfamiliar campaigns in your reports, it’s likely someone else is tagging your website, unintentionally. This can happen when your partners include you in an email campaign where their email provider automatically tags all URLs.
- If you don’t have an internal naming convention, your co-workers might be using the wrong parameters. There is potential to place the source in the medium field or misspell the labels.
You’ll know pretty quickly when your Campaign reports have bad data. There is a fast way to keep this from happening in the future by using the Search and Replace filter under your View. You would need to select Custom > Search and Replace as your Filter Type. Select the Campaign (Medium, Source or Campaign Name) from the Filter Field. Then include the term you want to search for and the term you want to replace it with. This will create a filter only on the View that you have selected so that whenever Google detects the chosen string, it will replace it with the string you have given it.
Good data makes for good decisions
As we’ve mentioned before, your business decisions are only as good as the data you’re basing them on. Now that you know how to set up a solid analytics foundation, filter out unwanted referral data, and how to keep an eye out for extraneous data, you can put your stress aside knowing that you’ve separated the wheat from the chaff. Keep your eyes peeled to this blog as we continue to look for and shed light on data integrity invaders.