Google Analytics mistakes not to make


Mistake #1: Using outdated tracking code

When you create a new site design and don’t update your tracking code (especially if you’ve moved from Google Analytics to Google Tag Manager), you risk it becoming outdated. Always make sure to use the most recent version of your tracking code as a precaution against these types of errors. Traffic will usually show inflated numbers, but unless you look deeper, you won’t know where the duplicate traffic is coming from. Even then, it’s hard to pin down. To find it, we will have to use a Google Chrome plugin. Make sure you’re not using duplicate tracking codes by using the Google Tag Assistant Chrome extension. When multiple instances of the same tracking code are enabled, this will appear as a red label inside the extension.

Mistake #2: Ignoring signs of scratching

A potential cause of bloated data in your GA account is scraping. If your site was scraped but the Google Analytics tracking code was not removed, you may be receiving traffic from a duplicate site in your GA. Investigate and inspect these domains for scraped content if you find a lot of traffic in Google Analytics data from any of these sites. This should immediately grab your attention. If you see a lot of your own content on the new site, double-check to make sure your tracking code hasn’t been transferred as well.

Mistake #3: Not switching from http:// to https:// in your GA admin panel

If you are migrating your website, make sure your admin panel is also migrated from http:// to https://. If you want to make sure your traffic data is tracked accurately, you need to get it right. You may forget to include some of your reporting data in your Google Analytics tracking if you don’t.

Mistake #4: Ignoring spam/bot traffic

Spam and bot traffic are also issues you should be aware of. You can affect the accuracy of your Google Analytics monitoring if you overlook the possible effects of spam and bot traffic. With respect to spam and bot traffic, this can lead to overinflated traffic performance and therefore inaccuracies in your data reports. This happens because spam and bot traffic are not considered reliable traffic sources. If you think your search traffic is growing but you’re basing your decision on spam and bot traffic, you could be in for a world of disappointment. That’s why it’s crucial to ensure that all SEO strategy decisions focus on real users and traffic, not spam or bots.

Mistake #5: Not evaluating sampled traffic vs. Unsampled traffic

It could be an error in making your data monitoring decision if your Google Analytics account on sampled traffic.

What is sampled traffic?

Non-sampled and sampled modes are available in Google Analytics. Non-sampled data processing means that Google Analytics tracks all possible Google traffic and does not use sampled data processing.

Default reports are not sampled. The following general sampling thresholds apply to ad hoc queries of your data:

Analytics Standard: 500,000 property-level sessions for the date range you’re using

Analytics 360: 100 million view-level sessions for the date range you’re using

However, when you create a default report in Google Analytics, that data is not subject to the sampling listed above.

When creating reports, be sure not to rely on sampled data. And, if you rely on this information, you are aware of the implications of sampled data.

Mistake #6: Ignoring hostname in URLs

Google Analytics does not include the hostname in the URL by default. When dealing with multiple subdomains, this can be tricky because you never know where the traffic is coming from. Always make sure you know 100% where the traffic is coming from. At least you will know 100% at all times what is going on with the hostname in your URLs. Your local SEO company can help you do this and more transparently for you.