Google Analytics mistakes you shouldn’t make
Error n. # 1: use an outdated tracking code
When you create a new site design and don’t update your tracking code (especially if you’ve switched from Google Analytics to Google Tag Manager), you run the risk of it getting out of date. Always be sure to use the most current version of your tracking code as a precaution against these types of errors. Traffic will generally show inflated numbers, but unless you look deeper, you won’t know where the duplicate traffic is coming from. Even then, it is difficult to pin down. To find it, we will need to use a Google Chrome plugin. Make sure not to use any duplicate tracking codes using the Google Tag Assistant extension for Chrome. When you have multiple instances of the same tracking code enabled, this will appear as a red label within the extension.
Error n. # 2: ignore the signs of scraping
One possible cause of bloated data on your GA account is scraping. If your site was scratched but the Google Analytics tracking code was not removed, you may be getting duplicate site traffic on your GA. Research and inspect these domains for pulled content if you find a lot of traffic to Google Analytics data from one of these sites. This should immediately make you stand out. If you see a lot of your own content on the new site, double check to make sure your tracking code didn’t carry over as well.
Error n. 3: Don’t change 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 have to do it right. You risk forgetting to include any of your reporting data in your Google Analytics monitoring if you don’t.
Error n. # 4: ignore spam / bot traffic
Spam and bot traffic are also issues to be aware of. You may be affecting the accuracy of your Google Analytics monitoring if you neglect the possible effects of spam and bot traffic. When it comes to spam and bot traffic, this can result in overinflation of traffic performance and as a result inaccuracies in your data reporting. This occurs because spam and bot traffic are not considered reliable sources of traffic. If you think your search traffic is growing but you are basing your decision on spam and bot traffic, you may find yourself in a world of disappointment. That’s why it’s crucial to ensure that any SEO strategy decision is focused on actual users and traffic, not spam or bots.
Error n. 5: don’t evaluate sampled vs. Unsampled traffic
This could be an error in your data monitoring decision making if your Google Analytics account is based on sampled traffic.
What is sampled traffic?
The sampled and unsampled modes are available in Google Analytics. Unsampled data processing means that Google Analytics is tracking all possible Google traffic and is not using sampled data processing.
The default reports are not subject to sampling. The following general sampling thresholds apply to ad hoc inquiries of your data:
Analytics standard: 500,000 sessions at the property level for the date range you are using
Analytics 360: 100 million view-level sessions for the date range you are using
However, when you create a default report in Google Analytics, this data is not subject to the sampling mentioned above.
When reporting, make sure you are not relying on sampled data. And, if you trust this information, you are aware of the implications of the sampled data.
Error n. # 6: ignore hostname in URLs
Google Analytics does not include the hostname in the URL by default. When it comes to multiple subdomains, this can be difficult because you never know where your 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 make it easier for you.