How To Tell If The Facebook.Code.Is From A Legit Source Google Analytics Mistakes To Not Do

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Google Analytics Mistakes To Not Do

Mistake #1: Using Outdated Tracking Code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your tracking code (especially if you’ve switched from Google Analytics to Google Tag Manager), you risk it being outdated. Always make sure you’re using the most up-to-date version of your tracking code as a precaution against these types of errors. The traffic will usually display inflated figures, but unless you look deeper, you won’t know where the duplicated traffic is coming from. Even then, it’s difficult to pinpoint. To find it, we’ll need to use a Google Chrome plugin. Make sure you’re not using any duplicate tracking codes by using the Google Tag Assistant Chrome extension. When you have several instances of the same tracking code enabled, this will appear as a red tag inside the extension.

Mistake #2: Ignoring Signs of Scraping

One potential cause of inflated data in your GA account is scraping. If your site was scraped but the Google Analytics tracking code was not removed, you might be getting 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 one of these sites. This should immediately stand out to you. If you see a lot of your own content on the new site, double-check to make sure your tracking code wasn’t transferred over as well.

Mistake #3: Not Switching http:// to https:// in Your GA Admin Panel

If you’re migrating your website, make sure your admin panel is migrated from http:// to https:// as well. If you want to ensure that your traffic data is accurately tracked, you must get this right. You risk forgetting to include any of your reporting data in your Google Analytics monitoring if you don’t.

Mistake #4: Ignoring Spam/Bot Traffic

Spam and bot traffic are also issues you should 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 traffic performance over-inflation and, as a result, inaccuracies in your data reporting. This occurs because spam and bot traffic are not regarded as reliable sources of traffic. If you believe your search traffic is growing but you base your decision on spam and bot traffic, you might be in for a world of disappointment. This is why it’s crucial to make sure that any SEO strategy decisions are focused on actual users and traffic, not spam or bots.

Mistake #5: Not Assessing Sampled Traffic vs. Unsampled Traffic

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

What is sampled traffic?

Unsampled and sampled 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.

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

Analytics Standard: 500k sessions at the property level for the date range you are using

Analytics 360: 100M sessions at the view level for the date range you are using

When you create a default report in Google Analytics, however, this data is not subject to the sampling listed above.

When you’re reporting, make sure you’re not relying on sampled data. And, if you’re relying on this information, you’re aware of the implications of the sampled data.

Mistake #6: Ignoring the Hostname in URLs

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

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