Google Analytics is the most used platform for measuring website performance. Across the globe, almost 15 million websites use the tool. You’re probably using it to track what people are doing on your site. As Bristol digital analytics specialists, we work with brands to optimise their analytics.
In doing so, we encounter a number of Google Analytics problems. A few of them crop up with surprising regularity. These common Google Analytics problems often impact how data is tracked. In this guide, I’m going to run down 10 of the most common Google Analytics problems we come across. I’ll cover each of these issues and offer solutions to them.
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Custom campaigns let you track how referred traffic comes to your site. For instance, you can track site visitors that come from a specific social media campaign. Having this data at your fingertips lets you assess the efficiency and ROI of individual campaigns.
There’s a chance your Google Analytics isn’t tracking custom campaigns. That may be because you didn’t know how to set up the tracking. Fortunately, getting tracking up and running for a campaign is pretty simple:
If you follow those simple steps, you can track your custom campaigns. If you still have problems accessing the data from your dashboard, revisit the Campaign URL Builder and make sure the URL you’re using matches exactly.
For many companies, digital marketing is one part of a wider marketing strategy. There’s a good chance you are also running offline campaigns, like TV, radio or magazine adverts. Most companies do. Many also assume that traffic generated from these campaigns cannot be tracked. That’s a mistake that leaves a damaging hole in their analytics.
Even though the campaigns are offline, it’s easy to track their results. All you have to do is give each campaign a unique element. By that, we mean one of the following:
Doing this means that you can track traffic related to the unique element you’ve featured. You’ll know that all of that traffic has been generated by your offline campaign. These are the same principles marketers would use to track campaigns before the launch of the internet.
Many sites have sales or conversion funnels that span more than one domain or sub-domain. For example, a funnel may take visitors from a blog post to a sales page and then a third-party shopping cart. Depending on the set up of each step, that could be three separate domains.
Tracking visitor movement through these funnels is known as cross-domain tracking. Cross-domain tracking errors can cause a range of problems with your analytics. Most notably, it can cause new sessions to be logged when they aren’t new sessions at all. They’re existing visitors moving down your funnel.
You have two main options to fix these errors. You can roll out correct cross-domain tracking using either Google Analytics or Google Tag Manager. Analytics support offers instructions on adding the necessary parameters yourself. Or you can choose to install Google’s Linker Plugin, to handle it for you.
With Google Tag Manager, you also have two options. You can either use Link Click/ Form Submit Tags or Auto Link Domains. Tag Manager support runs you through each option.
You want the bounce rate of your site to be as low as possible. When it’s abnormally low or drops suddenly, it suggests you have a problem with your Analytics. Bounce rate will generally stay pretty constant and can be anything from around 40% – 80% for most sites.
There are three main issues that can result in a sudden drop in bounce rate:
This is really an error of perception. Site owners will often worry if their Google Ads data and Analytics sessions don’t match. They can see it as a sign that something is wrong with one of them. That’s not necessarily the case.
Google Ads records the number of times a visitor clicks your ads. It’s a very simple metric. Each and every click is recorded. Analytics sessions are much more complex. They record users coming to your site, what they do and when they leave. They comprise several layers of data.
A number of factors can lead to Analytics sessions not being recorded. These include things like server latency or redirects. In short, you need not worry if your Google Ads and Analytics don’t match up.
Another common issue with Google Analytics reports is when cost per click (CPC) metrics are not collected. This is a problem associated with linked Google Ads and Analytics accounts.
When you do link those two accounts, Ads is supposed to add tracking parameters to your campaigns. Sometimes this doesn’t happen automatically. If your CPC metrics are not being collected, you can change your Ads settings to correct this:
There’s never a situation when you want to see a 404 error. At the best of times, they’re an annoyance. At the worst, they’re a source of massive frustration. The latter is certainly true when the errors are returned in your Analytics data.
This can happen for a number of reasons. Those include things as simple as having pasted a link incorrectly when setting up your Google Ads campaign. The errors could, however, occur because auto-tagging isn’t possible for your site.
The quickest way to check if this is the case is through Chrome Developer Tools. You can access Developer Tools as shown above. You can find a comprehensive guide on how to check if auto-tagging is possible.
When you set up a Property in Google Analytics, it’s auto-assigned a View. That View is called ‘All Website Data’ and should not be edited. If you want to break down your data further – and you will – you need to create new Views.
You can create new views via the admin tag on Analytics, as shown above. When you create a new View, you can apply Filters. These Filters define which hits will be included in or excluded from the View’s data. You might, for instance, set a Filter so that a View only records hits from a certain country. This can help you optimise your site or content for different audiences.
Applying too many such filters to a View can spoil your data. The ins and outs aren’t important, but overuse of filters can ultimately make a View redundant. The way you get around this is mercifully simple. All you need to do is to add more Views rather than more Filters.
You can add multiple Views and then apply a select few Filters to each. That gives you the same ability to compare and contrast data without compromising its accuracy.
Your raw data on Google Analytics is the data returned in the ‘All Website Data’ View we mentioned earlier. That’s the default View which you access when you set up a new property. You should never edit or filter this view.
The raw data View is basically your yardstick. It’s the overview of your site data. You can only understand the relationships and trends in smaller, filtered data sets by comparing them with this raw data. It’s essential you retain the raw data.
Mess around with the ‘All Website Data’ View there’s no going back. If you filter your raw data and don’t have the View for the same site in another Property, you can’t retrieve it. Analytics cannot be applied retrospectively to already filtered data.
Duplicated data in reports can impact your analysis, and ultimately your strategy. There’s one common way that duplicate data can occur. That’s when a visitor uses uppercase letters to type your URL into their browser. Something that happens pretty often.
Doing so doesn’t stop them from getting to the right page, but can impact your data. Google Analytics will record the URI (end of the URL) as it appears on the visitor’s browser. That means you’ll have lines on your Analytics reports for both the correct URL and the one with uppercase letters.
Once that duplicate data has got into your reports, you can’t remove it. It is easy, though, to stop it from occurring in the first place.
If you’ve discovered any of the above problems, there’s no need to worry. You’re not alone. These are among the most common Google Analytics problems around. A quick study of our 10 common Google Analytics problems should show you just what’s wrong with your analytics. Our simple step-by-step solutions, too, ought to swiftly get you on the road to recovery.
If you have any questions about analytics let me know in the comments below. I will be happy to answer your questions.