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Common Google Analytics Tracking Mistakes (and How to Avoid Them)

Google Analytics is a monster of a marketing tool, enabling users to streamline their marketing efforts to achieve company success. However, with great power comes great responsibility, here are some common mistakes you can avoid to make the most of it.

Google Analytics is a marketer’s best friend. It helps you understand how your customers are behaving, pinpoint gaps in your online marketing strategy, and guide future investments.

That is, of course, provided you get your tracking right.

If your data collection is flawed, you’re at risk of making bad business decisions or sinking money into actions that don’t deliver.

Having duplicate tags, for example, could lead to double-ups and skew your reporting. On the other hand, if you haven’t set up your interaction events properly, you may be tracking actions that ultimately don’t bring you closer to your end goal.

You NEED to get your Google Analytics running smoothly if you want to have data that you can reliably trust and act on.

But how do you correct Google Analytics mistakes if you don’t even know what you’re looking for? 

That’s what we’re here to fix. 

In this post, we break down 18 of the most common mistakes we see on a daily basis and how to correct them (or avoid them altogether).

 

#Mistake 1. Tracking your own sessions

Your team probably spends a lot of time on your website. If you count these into your reporting, it can inevitably skew your Google Analytics data by making it look like you have more web visitors than you actually have, or that you have higher average session durations than you actually do.

How to fix this common mistake: Create an IP address filter to exclude internal traffic from Google Analytics. You can do this by first obtaining your IP address by searching “what is my ip address” on Google. Once you’ve got this, create a filter that excludes this IP address like so:

GA ip address

To exclude multiple IP addresses, follow this handy guide by Google.

 

#Mistake 2. Not including a bot filter

While we’re on the topic of filters, forgetting to exclude traffic from bots is another one of those common Google Analytics mistakes that marketers make. 

Unfortunately, every website gets bot traffic. In fact, a survey by Databox found that more than half of all marketers say their website generates bot traffic daily or weekly.  

website bot traffic graph

Including these in your reporting causes a host of issues, including an overinflation of total website traffic, lower engagement levels, and a lower conversion rate. What’s worse, you might end up basing decisions on this “increase” in traffic — leaving you in for a host of disappointment.

How to fix it: This one’s a relatively quick fix. Go into the Admin section of Google Analytics and click on “View Settings”. 

 

GA 1

 

Once you’ve in, click “exclude all hits from known bots and spiders”. 

GA 2

 

#Mistake 3. Having more than one Google Analytics code

This one seems unlikely, but it’s actually one of the more common Google Analytics mistakes. There are a number of reasons why a website might have a duplicate Google Analytics tracking code:

  • You have more than one CMS in place

  • You have a hard-coded and Google Tag Manager implementation

  • You’ve left old tracking codes on your pages

  • You’re using internal UTM parameters

These kinds of mistakes lead to artificial inflation of your Analytics data because Google will be tracking every interaction twice. And, like spam or bot traffic, basing your decision or reporting on this information could spell trouble in the long run because these double-ups won’t reflect in your bottom line.

How to fix it: Duplicate Google Analytics codes won’t be obvious at a first glance, but one of the best ways to detect this is by looking at your bounce rates. Having a near-zero bounce rate (i.e. 1-3%) could be a sign that you have some double-ups on your website.

GA 3

If you want to drill down to see if individual pages have a duplicate tracking code, you can do this by going to Behaviour > Site Content > Landing pages and sorting by bounce rate.

After you’ve found the culprit, use the GA Debug chrome extension to check out what’s happening on those pages. 

 

#Mistake 4. Missing Google Analytics code

Having a missing Google Analytics tracking code on your website means that you won’t be gathering ANY data on performance. This is one of those mistakes that could happen if you switched your website theme and forgot to update add the Analytics code, or because you’re using multiple CMS.  

How to fix it: Google Analytics does have a built-in missing Google Analytics tracking code notification, but it’s slow and can be easy to miss. Be sure to check your notifications regularly by clicking on the top right-hand corner like so:

tracking code

 

Another solution is to use Screaming Frog to scrape your website for Google Ads' Google Tag Manager and Google Analytics codes like so:

screaming frog

 

#Mistake 5. Missing or incorrect set-up of interaction events

Interaction events mark crucial milestones along the customer journey. You might track use event tracking for when a user submits a form, plays a video, hovers over a promotional banner, or clicks on one of your product pages. When you have this raw data on hand, it’s easy to identify precisely where your customer funnel is letting you down and rectify it to win more conversions from your site traffic.

However, there are some cases where you may be setting up interaction events for tracking events that are automatically accounted for on each page (such as scroll depth tracking). This little oversight could lead to unrealistically low bounce rates across your entire website.

How to fix it: If you’ve doubled up on interaction events and tracking events, you can easily fix this in Google Tag Manager. Go into your tag configuration, scroll down to “Non-interaction hit”, and change this from “false” to “true”:

GA 4

If you’re just using Google Analytics, this can be done by adding in an additional line of code:

non-interaction events

 

#Mistake 6. Tracking traffic from other domains

Your Universal Analytics code is visible to everybody. Someone could open up the source code on your website, copy your tracking code, then start recording traffic under your domain.

While the reasons behind WHY someone would go into your source code and do this remain a mystery, it’s still important to take preventative measures to ensure you’re only tracking data from your own property.

How to fix it:  Once again, we go back to the filter. Go into View Settings and Click on Edit Filter. Set up a filter to only include traffic from your domain, and you’re good to go.

edit filter

 

#Mistake 7. Including spam referral traffic

Spam traffic isn’t the same as bot traffic, but it’s equally undesirable. If you’re running a popular website, you might find that other websites point spammy links back to your domain. While most of these amount to very little, some could drive traffic in the hundreds or even thousands. 

Thankfully, these are easy to search for. Go into your Google Analytics Referrals report by navigating to Acquisitions > All Traffic > Referrals. From here, you’ll see a list of all of the websites driving traffic back to your domain, like in this example:

spam website

If you’re seeing a website with a weird URL, chances are it’s probably spam referral traffic. Another way to do it is to filter by referrers with a near-100% bounce rate or more than 10 users per session.

How to fix it: Make a note of all the spam referrers that you’ve found. Set up a filter by campaign source, then list these domains as filters:

add filter to view

Lastly, don’t click on the link as it might leave your computer susceptible to viruses or malware. 

 

#Mistake 8. Tracking self-referral traffic

Your own domain shouldn’t be showing up in your referral reports. If it is, it means you’ve made the mistake of tracking self-referral traffic.

Self-referrals primarily occur because of two reasons:

  • One session could have been split into two while moving around your site. For example, a cookie could have been stored on blog.domain.com but you then ended up moving to another URL like shop.domain.com. 

  • A session was started on a page without a Google Analytics tracking code, but the user then moved on to a page with a tracking code. The only data that Google Analytics has on that source of referral traffic is your website, so it records it as a self-referral.

How to fix it: Debug your website following these instructions from Google. This list includes detailed explanations of why self-referrals occur and how to fix them:

self-referrals

 

#Mistake 9. Using UTM parameters incorrectly

UTM parameters are helpful when collecting data for a specific campaign or referral. However, these are also commonly misused by marketers — particularly when linking from one internal page back to another.

Internally linking with UTM parameters can skew your attribution efforts and mess with your session data. On top of this, it’s a wasted effort because all of this data is already available to you in Google Analytics.

How to fix it: Remove any UTM parameters on your own website and opt for one of these options instead:

  1. Use the page path analysis feature in Google Analytics to see the previous steps a user took before landing on your ending page. This can be done by setting your campaign page as your ending point and reviewing the different pages that drove traffic to that destination.

  2. Create an internal link parameter (“ITM parameter”) and use GA’s custom dimensions feature to track these traffic sources. Smashing Magazine has an incredibly helpful and detailed breakdown of the process.

 

#Mistake 10. Forgetting to exclude query parameters

Sticking with parameters — creating further parameterised URLs for your landing page is a surefire way to mess with your tracking and make it difficult to dig deeper into your data. These URLs will break up one landing page into multiple rows when reporting, like in this example:

apparel ga

How to fix it: Use your report filters to search for any parameterised URLs (ones with a “?”):

At a glance, you’ll be able to spot whether one landing page is being splintered off into multiple pages.

If you notice this error happening, simply exclude parameters that you don’t want to see in your View Settings:

view settings ga

Be mindful not to exclude any parameters that you ARE using, like search query parameters, UTM parameters, or ones that you’ve created to track specific campaigns.

 

#Mistake 11. Not using site search reports

This isn’t mandatory, but it is extremely helpful — particularly for eCommerce sites. If you have a search function on your website, these search reports are a valuable way to gain insights into which products are the most popular, what content users are interested in, and where there are opportunities to create new content.

These reports look like this:

GA graph

You can set up site search reports by going into your Google Analytics account, navigating to the view where you want to set up site search, and turning tracking to “ON”. Once you’ve done this, you’ll need to enter the words that designate internal query parameters — Google has more detailed information on the process in this article.

 

#Mistake 12. Forgetting to merge your source and your medium

Most marketers think that the source and medium are the same things — and if you’re making this error, it’s not hard to see why. If you haven’t merged your traffic source and medium, you’ll end up with Google Analytics reports that look like this for Facebook or AdWords:

facebook referral

 

How to fix it: Use filters to merge all your referral traffic from a single domain like in this example:

filter verification

Unfortunately, these filters aren't retroactive so you’ll still have historical data containing all of these different sources. Last but not least, don’t forget to test your filter before implementing it, and add a note in your back end so everyone on your team knows exactly why there’s been a change in source and medium traffic.

 

#Mistake 13. Not using annotations

Not using annotations won’t mess up your tracking data, but it sure is handy when you’re looking back and reflecting on what happened on any given date. Annotations are the perfect way to track any spikes or dips in traffic, or evaluate the success of an offline campaign or a new sale.

In Google, they look like this:

GA annotations

Source: Search Engine Watch

 

How to fix it: Start using annotations ASAP.  You can do this by navigating to any graph report, then clicking on +Create new annotation:

 

GA annotations 2

Image source: Practical eCommerce

Keep in mind that you can create both shared and private annotations, depending on the nature of what you’re noting down. Private annotations are only visible when you log in to Google Analytics, whereas shared annotations can be seen by anyone who has access to the reporting view.

 

#Mistake 14. Cross-domain tracking

If you’re not using cross-domain tracking, you’re missing out on a huge chunk of data about user behaviour. Cross-domain tracking allows you to see sessions on two related websites that you own, such as your eCommerce site and shopping cart site or a campaign mini-site. 

Without cross-domain tracking, your website data looks like this:

cross domain 1

Image source: Google

With cross-domain tracking, you consolidate all of this data into a simple report like so:

cross domain 2

Image source: Google

If you have subdomains like blog.mysite.com or help.mysite.com, you can also set up subdomain tracking:

cross domain 3

Image source: Google

How to fix it: The way you set up cross-domain tracking in Google Analytics differs depending on the scenario. There’s one way to do it if you’re tracking multiple domains, another for tracking this AND sub-domains, another for tracking a domain and a sub-directory...you get the idea. Luckily, Google has a support page that outlines detailed steps for every type of cross-domain tracking, which should include all the information you need to get started.

 

#Mistake 15. Tracking PII from your site traffic

Your site should NOT, under any circumstances, be tracking personally identifiable information (PII). These include phone numbers, email addresses, or even the names of users visiting your site. 

You may not be doing this knowingly. The trouble is, you could be generating this PII by accident simply by creating URL parameters that contain personal data. This is particularly common when you’re working with forms:

PII site traffic

 

Google takes this stuff VERY seriously. If you’re caught gathering PII, Google will send you an email notifying you of the breach. Ignore this, and you might find yourself in a whole heap of legal issues.

How to fix it: Don’t risk it, period. However, if you are concerned you’re passing on sensitive information, follow these steps to check for PII in Google Analytics.

Navigate to Behavior > Site Content > All Pages, and type in the filter “@”. This will bring up any page views that include email addresses like so:

PII site traffic 2

You can also use the GA Debugger Chrome Extension and look for names, phone numbers, addresses, or emails.

 

#Mistake 16. Not setting up custom goal/conversion tracking

The end game of your website is to generate leads or sales. If you’re not tracking this, you’re missing one of the MOST important pieces of data in Google Analytics. You won’t know how many of your site visitors ultimately made a purchase with you, or how many filled out a form. You won’t know which sources convert the best. And you absolutely won’t be able to draw any kind of conclusion on how you should invest your time and money in the future.

How to fix it: Create goals and conversions for key points in your customer journey, such as when they navigate to your “About us” page or sign up for your newsletter. When you’re getting everything set up, be sure to check that all of your codes and triggers are set up right. Having conversion triggers firing at the wrong time or multiple times can cause a ton of headaches and skew your data.

 

#Mistake 17. Only using one view

This applies even if you’re only using Google Analytics for one site domain. You should always, always, ALWAYS have at least three different custom views for your site traffic: your master view, a backup of your master view, and a testing view where you can play around with filters or more sophisticated settings.

How to fix it: Log into your GA account and go to Admin > View Settings. Hit +Create View to create a new view. Follow the prompts to set u your view, then give it a name like Master View, Backup View, Testing View. You’ll then see all the views in your Google Analytics reports like so:

all web site data

Image source: Monster Insights

 

#Mistake 18. Not testing your Google Analytics set-up

You should ALWAYS test your tracking set up before using it to guide your decision-making. Most Google Analytics mistakes occur when you don’t correctly set up your tracking and analysis, which can mess with ALL of your data.

“Your first step should be setting up Google Analytics, so it will report back to you what we call as “useful version of the truth.” For example, if you aren’t properly tagging your traffic with UTM’s, that’s the priority. Only then will the “Source/Medium” reports start to provide really useful details. If you have UTM’s all setup, then move on to goals. That way, that same “Source/Medium” report will not only tell you where your visitors are coming from, it’ll start telling you just how effective those traffic sources are.”

- Chris Mercer, measurementmarketing.io

Before relying on your Google Analytics as your “truth”, it’s worth checking that all of your conversions are firing correctly, tags are installed correctly, and you’re not racking up tons of spam/bot traffic.

How to fix it: Use incognito browsing or browse your site from a different property. Visit different pages, do test purchases, fill out forms, and click on your most frequently visited pages. After you’ve done this, go into Google Analytics and see if this data has been correctly reported on. You can also use the real-time Google Analytics reports view to check that everything’s working as it should while you’re browsing.

GA report

Image source: Monster Insights

After you’ve checked that everything’s working as it should, don’t just set and forget. Pencil in time to conduct regular check-ins on your reports, and do a full audit of your reporting every now and then. This will help you get ahead of any issues before they have too much of an impact on your Google Analytics data.

 

Maximise conversions, leads and sales with Google Analytics

Setting up your Google Analytics account correctly can be tough, but it is absolutely worth doing. By fixing these common Google Analytics tracking mistakes, you'll be well on your way to collecting accurate data that can guide future marketing investment and supercharge your ROI.

Once you're collecting the right kind of data, it's time to use that information to work. We'll use Google Analytics data to pinpoint opportunities to increase your conversions, track the success of your digital marketing campaigns, and set you on the path to online domination.

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