According to BuiltWith, there are more than 30 million websites using Google Analytics to track traffic and user engagement – let’s assume that’s a conservative guess. And according to the Small Business Administration, there were 29.6 million small businesses in the United States in 2017.
What can we take away from these two numbers? There are a lot of small businesses that are using Google Analytics to better understand – and optimize – their website. And on the surface, that sounds great, right?
Unfortunately, it’s not.
Google Analytics can be a powerful data analysis tool (especially considering its free price point) – but only if it’s used correctly.
The sad truth is, there are plenty of pitfalls that can ruin Google Analytics data and lead small business owners to making misguided – or flat out wrong- decisions about their marketing efforts.
Let’s explore some of the major issues that the average Google Analytics user might not know.
UTM Parameters: Email Traffic Not Reporting Correctly
This is by far one of the most common issues small business owners encounter with their Analytics data.
More and more businesses are realizing the value of email marketing (despite recent GDPR events), but few business owners likely know the true impact these campaigns are having on their businesses.
Sure, popular email marketing platforms can give you lots of great data about open rates, click-through rates, and even whether people are reporting your emails as spam. But what most platforms can’t do is tell you what happens after the click. Did all those customers who clicked on the email make a purchase? Or did none of them?
This is, in theory, where Google Analytics should shine. After sending an email campaign, you can just pop into Google Analytics and check on how your Email traffic is doing (after all, it’s a built-in channel grouping for Google Analytics).
But wait… Your email platform says you got 1,000 clicks on your last newsletter, but there’s not a single email session in Analytics.
What’s going on here?
Unfortunately, while it’s true that Google Analytics has a channel set up for email traffic, you have to do some work to actually get email traffic to show up there. Namely, you need to use Urchin Tracking Modules (more commonly known as UTM parameters).
Google has a resource for learning more about UTM parameters, but here’s a quick example:
https://www.domain.com/example-directory/example-page/?utm_source=newsletter&utm_medium=email&utm_campaign=jan2017
- utm_source – This is the “source” of the traffic; some sort of descriptor for what the user was doing previously. For email, this was likely a newsletter or an abandon cart email.
- utm_medium – This is the “medium” the traffic used to get to your site. For email traffic, this should almost always be email.
- utm_campaign – This is the campaign that the traffic is tied to. This can really be anything, but should give you some indication of what marketing effort this campaign was tied to. In the example above, it was tied to our January 2017 email blast.
There are a handful of other UTM parameters you can use. but the three above are essential.
Self-Referrals: Traffic from Your Site or Subdomains
It’s important to realize that Google Analytics is NOT tied to your domain name. It’s just a piece of JavaScript code that either fires or doesn’t fire – regardless of the website it’s on.
This can lead to a number of issues, but one of the most common (and frustrating) is ‘receiving’ traffic from your own website:
In most cases, what’s likely happening here is one of two things:
- The site has a subdomain that isn’t properly configured to track Google Analytics across both sections of the site.
- The site has pages on it that don’t have the Google Analytics code on it.
In reality, both of these issues are actually pretty similar – they both have to do with how Google Analytics decides what channel to put traffic into.
At a super high level, Google Analytics uses data sent by your browser to determine where your session came from. For example, if a user comes to your site from Facebook, that user’s browser tells your Analytics code that it came from Facebook – and Analytics takes care of it from there.
However, this transaction of information happens every time a page loads. So when that same users loads the next page on your site, your browser says you came to that page from a different page on your site. Analytics just knows to disregard this information in favor of the original source.
Unfortunately, it’s not a perfect process. Let’s revisit the two scenarios:
Google Analytics on Subdomains
I should preface that this is increasingly becoming a non-issue, since out-of-the-box Analytics resolves most issues like this. That said, if you’re running an older version of the Google Analytics code, you should know that by default, it may consider subdomains to be completely separate sites.
This means, if you have a blog on blog.domain.com, you might be seeing traffic come from blog.subdomain.com – even though it’s using the same Analytics code!
Pages Missing Google Analytics Code
Similarly, if you’ve got pages on your site that are missing the Google Analytics tracking code, you could wind up in a situation where you’re sending referral information to your site that conflicts with the original source data sent by the user’s browser.
For example: Let’s say a user comes to your homepage via Google. They’re now an Organic Search session in the eyes of Analytics. Say they then go to your About Us page which, for whatever reason, is missing the Analytics tracking code.
Two things are going to happen now:
- Google Analytics will have no idea that the user was ever on the About Us page. If there’s no Google Analytics code on the page, Google Analytics has no way to track that pageview.
- When a user clicks on a link to another page, they’re sending new source data to Google Analytics, which may override the original data that allowed Analytics to classify the traffic as Organic Search. It will now likely be a Referral session.
The result: Not only are you missing potentially crucial information about that user’s session, that session is likely being split into two distinct sessions.
Cross Domain Tracking: Most Sales/Leads Attributed to Single Channel
Remember: Google Analytics is just a piece of JavaScript. It doesn’t know what is part of your site and what isn’t – it just processes data according to a set of rules.
This can lead to a similar issue to the one we just looked at: all (or most) of your sales are attributed to a single channel (which is almost always Referral or Direct). If you dig even deeper, you’ll likely realize that these sales/leads are actually coming from a single referral source.
Here are a handful of examples of common culprits you might see:
- PayPal
- NetSuite
- CardinalCommerce
- WuFoo
And the reason for this makes a lot of sense, given what we learned with the last issue: Google Analytics classifies sessions based on the last-known source data.
So if someone comes to your ecommerce store from a Bing Ad, adds an item to their cart, and then pays for their purchase via PayPal, what can often happen is that the sale actually gets credited to PayPal instead of the Bing Ad session.
So what’s happening? Well, when you use PayPal or some other “third-party” checkout or partner, your users are technically leaving your site – which opens your data up to a host of tracking issues, like we discussed above.
Perhaps most annoyingly, when that third-party platform finally sends traffic back to your site, it’s sending new source data along with it – which means the ultimate goal completion will be attributed to them.
This isn’t a deliberate or nefarious tactic to inflate value (usually, anyway). Instead, it’s just how the internet works.
Luckily, Google Analytics has a way to work around this – but it requires modifying your code a little bit in order to implement cross-domain tracking.
Wrapping Up
Have you encountered any of the issues above? Are you fully confident that your data is providing you with accurate information about your various marketing efforts?
If you’re not sure you trust your data, a thorough Analytics audit can help you uncover weak spots in your data and make sure you’re putting your marketing dollars to good use.
Don’t let bad data prevent you from good marketing!
