Google Analytics Basics: Traffic Sources and Mediums 

 

Knowing the basics of Google Analytics sources and mediums can help set you up for success as you go onto bigger and better things in the world of data and analytics, such as UTM coding. This is why my first post in my UTM Coding series is all about Google Analytics basics – traffic sources and mediums. 

What Are Web Analytics Programs?  

Google Analytics is a freemium web analytics software used by over 29 million websites (source: https://trends.builtwith.com/analytics/Google-Analytics). Its popularity comes from the fact that a) it’s free and b) it comes from the ever powerful Google. That combination is pretty hard to beat. 

People love web analytics programs because they help measure basic web traffic, including how people found your website, what pages they visited when they were here, when they visited (time, date, day of week), how long they stayed on your website, and more. We refer to the “how people found your website” dimensions as traffic sources and mediums. 

Google Analytics Sources, Mediums, and Channels 

For every visit to your website, Google Analytics (usually automatically) attributes a source and medium. A source is defined as the specific origin of your traffic. Examples of sources are facebook, linkedin, pinterest, google, yahoo, bing, yelp, yellowpages, bbb, and more. A medium is the category of the source. Examples of mediums are email, social, organic, ppc, cpc, and referral. 

Once Google receives a source and a medium, it places the traffic in an even larger category, called a channel. Examples of channels are: email, social, organic, direct and referral. As I said before, Google will always give a source and a medium to your traffic, however if that source and medium doesn’t fall into one of their predefined channels, Google classifies it as (other). 

Google's Predefined Rules for Each Category

Google’s Predefined Rules for Each Category

As you may have guessed it, (other) isn’t very helpful when you’re looking for a 30,000-foot view of your data, which is why you want to avoid (other) whenever possible. Luckily, you can avoid (other) by following a few simple rules 

How to Properly Categorize Your Source and Medium to Avoid Getting (Other) 

One of the most common reasons traffic gets attributed to (other) is because the source or medium is capitalized. I try and always avoid capitalization because it’s the easiest way to keep everything consistent. It also makes it easier to pass off UTM coding to someone else in your absence. Examples of improper capitalization are: 

    • Facebook 
    • FACEBOOK
    • Organic 

Google will also categorize your traffic as (other) if the medium is not part of their system-defined channel groupings. Examples of mediums not included in Google’s channel groupings are: 

    • offline 
    • boosted
    • paid 

If you decide you want to use these mediums but avoid the (other), have a Google Analytics expert modify your channels before you deviate from Google’s rules. For a full list of what’s acceptable in the eyes of Google, visit here: https://support.google.com/analytics/answer/3297892?hl=en&ref_topic=6010089.

Google Analytics Direct Traffic 

When Google is unable to attribute both the source and medium of your website traffic, the visit gets classified into the “direct” channel with a source of “direct” and a medium of “none.” While you may think this doesn’t affect you, if your company sends our any emails, it might. Many email programs don’t communicate properly with Google, traffic from email subscription lists often come through as direct traffic. 

With Google Analytics, you can test if your email is coming through as a direct visit with real-time reporting from Google Analytics. If your test proves positive and your traffic isn’t getting properly attributed, it may be time to learn about UTM coding, which allows you to override the traffic sources and mediums Google automatically assumes. 

Summary 

Knowing the basic rules of Google’s sources, mediums, and channels can help you lay the groundwork for bigger and better data analytics initiatives, like UTM coding. Whereas small mistakes can cloud your Google Analytics insights and lead to erroneous analysis. If you already know the basics of UTM coding, read ahead about best practices for UTM coding – part one and part two.

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