Common Google Analytics Mistakes & How to Avoid Them
- SEO |
A new article on Search Engine Journal says that simple analytics mistakes can interfere with your SEO reporting. Here, you can learn how to avoid the most common Google Analytics mistakes.
The author says that even experienced SEO professionals make mistakes. The good news is that you can learn to spot and solve them.
The author says that even experienced SEO professionals make mistakes. The good news is that you can learn to spot and solve them.
- Having More Than One Google Analytics Tracking Code: Having more than one instance of Google Analytics tracking code can cause you to over-report your data.
- Not Tracking the Right Event Clicks: If you're not tracking the correct event clicks, you aren't getting accurate performance data.
- Not Filtering Out Your Own Company Traffic: Look deeper into Google Analytics and investigate your company's IP address. If you find traffic coming from your own IP address, you need to block it from Google Analytics.
- Not Tracking External Sources of Traffic With UTM Tags: If you don't ensure the correct UTM tags are installed on your ads, how can you ensure the accuracy of your traffic reporting?
- Not Being Mindful of Your Parameter URLs: Parameter URLs are all well and good until they're hit by a ton of traffic and become a nuisance. This inundation of traffic can result in reports hundreds of pages long. If you know that certain parameter URLs should not be tracked, filter them out of your Google Analytics reports.
- Ignoring Individual Sources of Traffic: When you ignore individual sources of traffic, you are tuning out a valuable chunk of decision-making data.
- Using Outdated Tracking Code: When you create a new site design and don't update your tracking code to new ones (especially if you have transferred to using Google Tag Manager over Google Analytics) you run the risk of it being outdated.
- Ignoring Signs of Scraping: Scraping is one possible reason for inflated data in your GA account. If your site has been scraped and the Google Analytics tracking code left intact, you may be seeing the duplicate site's traffic in your GA.
- Not Switching http:// to https:// in Your GA Admin Panel: If you perform a website migration, you will need to ensure that your admin panel is also switched from http:// to https://.
- Ignoring Spam/Bot Traffic: Spam and bot traffic is also something you don't want to ignore. If you ignore the potential impacts of spam and bot traffic, you could be negatively influencing the accuracy of your Google Analytics tracking.
- Not Assessing Sampled Traffic vs. Unsampled Traffic: If your Google Analytics account is relying on sampled traffic, this could be an error in your data tracking decision-making.
- Ignoring the Hostname in URLs: By default, Google Analytics does not include the hostname in the URL. This can be a challenge when working with multiple subdomains because you cannot be entirely sure where traffic is coming from. Always make sure that you know 100% where the traffic is coming from.
- Not Analyzing the Right Profiles: When you first set up Google Analytics, you have one profile you can use. Over time, however, you can use more than one profile depending on the purpose of said profiles.
- Ignoring URL Rewriting & Excessive Parameters: Ignoring URL rewriting can result in unintended consequences. For example, say that your data includes many parameters all coming from different URLs on your site. They could be reporting inaccurate traffic data because there are multiple URLs per page based on the excessive query parameters. When this occurs and you ignore it, you run the risk of reporting on inaccurate data.
- Not Tracking All Subdomains in Your Property Profiles: This is a highly "it depends" scenario because it depends on what you're tracking when it comes to your Google Analytics data. If you're tracking many different subdomains, you may be in for a world of surprises in Google Analytics if you don't track them within Google Analytics.
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