We don’t like junk data; it makes our lives much more difficult as we strive to find actionable intelligence within the pages of metrics found in our Google Analytics reports. And when we’re intentionally sending data to our Analytics through the usage of UTM encoded URLs, we want the data that we’re sending to be as ordered and structured as possible so that we can gain insights from the results.
The problem is that in building our UTM strings we’re provided carte blanche ability to insert any variable value that comes to mind, in whatever format we choose… and thereby potentially making a complete mess of the data we’re trying so hard to use.
How should you put in “del.icio.us” as a source? Is it Facebook, facebook, or facebook.com? What about paid social (is it CPC or Social), or the company’s blog on Medium that points back to their own website? Is a press release a referral, social, advertising, or something else? Should we use spaces or hyphens or underscores to separate words?
All of our variable value decisions factor into how the session is categorized in Analytics, how it can be viewed from different angles, and whether it is being grouped properly in order to give us true reports. For quality reporting to happen we need to have an understanding regarding how Google Analytics is already seeing data coming in, and try our best to either match those existing values or create our own new groupings.
We need some Best Practices for using UTM codes, and we need to understand how to best utilize their data in our Google Analytics installation.
A quick UTM primer
UTM (Urchin Tracking Module) codes are a long-favored and standard method of incorporating data into a URL string that can then be seen within a base-level installation of Google Analytics and other analytics software. A UTM code begins with a base URL, then adds additional variable:value combinations of Source*, Medium*, Campaign name*, Term, and Content.
Example of a UTM-coded URL string:
By adding these variable:value combinations to a link, when that link is clicked it sends specific data to your Google Analytics installation that enables that session visit origination to be tracked in the specific way you’ve directed.
For more details please read our complete blog article on the subject of UTM encoded URLs.
Matching existing Sources
When presented with an empty form field, consistency is one of the hardest things to maintain. How did you last enter Facebook as a source? And should you be using Facebook, facebook, Facebook.com, let alone NYTimes, The New York Times, NYT, nytimes.com…
Now let’s say you were going to your sources report, trying to see where your traffic was coming from. Without keeping consistent sources, your line-item for the NYTimes wouldn’t be just one line, but maybe 4 or 5 different lines in different formats! You’d need to go and add them together to get a sense of how much traffic that one source sent you, but under different names. And if not compiled, what could be a top 10 source (registering in your dashboard widgets which only show up to 10 items) might not even show because its traffic has been fragmented in the reporting.
While some people have tried to formulate a master list, a good strategy is to always check within your Sources reports in Analytics before undertaking a UTM campaign. Look to see how traffic from that source is currently being recorded in your reports and make sure to use the same formulation in your own UTM encoding. If you see The New York Times in your referrer as “nytimes.com” then make sure to match that when entering your UTM source for the New York Times.
(Tip: our UTMftw service saves your variable values for re-use to keep you consistent!)
Matching existing Mediums
Mediums are groupings of sources, ways to see “types” of sources as aggregates. Google Analytics has four default mediums: referral, organic, cpc for paid search, and (none) for direct traffic. Beyond those four defaults, we often make use of: email, social, banner, and print.
You might also have mediums that many people don’t have, like chat, instant message, telephone… it’s up to you to determine how your sources should be grouped, but you want to keep within the structure above as much as makes sense.
Source / medium data are some of the primary ways that Google Analytics uses to order reports, with these variables being accessible in almost every corner of your metrics. Before you go outside the default mediums, or even into the additional ones mentioned above, make sure to strategically define how you want to make use of your mediums and whether additional options are optimal.
Understanding default Channel Groupings
The best way to describe Channel Groupings in Google Analytics is as a way of aggregating different sources, mediums, or combinations of sources and mediums to create a Channel.
For example, “Paid Search” is a combination of CPC, PPC, paidadvertising as mediums AND ad distribution network is not “Content”; combined, they yield the Paid Search channel. Another channel, Social, uses regular expressions to group the mediums of social, social-media, socialmedia, etc. OR Social Source Referral is true into a channel of Social.
With this in mind, it is then important to align your utm_source and utm_medium so that it conforms to these preset Channel Groupings. If you’d already aligning based on matching Mediums (previous section) you should be all set, but it’s good to understand this alternative means of seeing the data as it’s a primary report within Analytics.
Customizing Channel Groupings
Some good examples of modified Channel Groupings that aren’t part of the default are Promoted Social or Employee Advocacy.
You might be running a boosted post in Facebook, Twitter, or Instagram, but treating the traffic from those sources as just social would be misleading yourself. The traffic they’re sending to your site isn’t organic social, and wouldn’t you want to see Organic (normal) Social as opposed to Promoted Social? You’d want to be able to see how traffic from your boosted posts is performing compared to your “organic” social traffic or simply isolated. You might also want to see how your paid social is performing as opposed to advertising in web pages or search engines.
To create this Channel Grouping you’d in essence be combining two types of groups: Paid Advertising (medium) and social sources (Twitter, Facebook, etc), unless you took the approach of creating a new medium (paidsocial), but that might prevent you from doing greater cross-comparisons.
For employee advocacy, you might have a service assisting you, such as Bambu, that is engaging your employees to disseminate messages via social media. In this case we might be using the utm_source of “bambu” and the utm_medium of “social”, or we could use the utm_source of “bambu” and the utm_medium of “employee advocacy”. Either way, what we’d want to do is create a custom channel to isolate this traffic and see it as a “channel” that we can compare against other channels (that being Employee Advocacy).
Changes and additions are not retroactive, and any data reported on will be reflected starting on the day the channel goes live.
Get started with UTM campaigns
Hopefully now you’ll have the information necessary, not just to make use of UTM campaigns, but to use them with best practices. By keeping your campaigns well-structured and using a bit of planning you’ll be able to get cleaner data that results in better reports that can be used for actionable intelligence.
Use our UTM For the Win tool to assist you in your campaigns, and contact us for assistance with your Google Analytics and gaining actionable intelligence.