5 Causes of Misleading Google Analytics Data

By Geena Nazareth | Feb 21, 2017
More Articles by Geena


google-analytics-accountMany assume that once Google Analytics is set up and tracking, all of the data being reported is 100% accurate.  Unfortunately, that isn’t the case.  The reality is there’s a good chance that your data is as least somewhat inaccurate or misleading, but having accurate data is essential to evaluating performance, planning and budgeting.  Performing a Google Analytics audit and identifying data inaccuracies is a great place to start.  Here are five common causes of misleading Google Analytics data and how to recognize them.

1. Self-Referral Traffic

Referral traffic arrives on your website through another source (i.e. a link on another website).  Self-referral traffic arrives on your website from your own domain or subdomain.  A small number of self-referrals are normal, and typically occur when a user returns to your site after their original session has “timed-out” and Google considers it a new session.  If your website is listed as one of the top referral sources in the Google Analytics referral report, you likely have a problem.  You can identify approximately when the problem began by clicking on your domain/subdomain in the referral report and examining the graph for an obvious spike in referral traffic.  You may need to extend your date range to do so.  The real issue with self-referrals is that your traffic is being incorrectly attributed, and you don’t know where your visits are really coming from.  The issue can be rectified, but setting up Google Analytics correctly from the beginning is unquestionably the easier route.  Self-referrals can occur for several reasons, one of them being improper cross-domain tracking, which brings me to my next item.

2. Cross-Domain Tracking Mistakes

You may run into cross-domain tracking problems if your site has multiple subdomains (i.e. blog.example.com) or if you have an eCommerce site that sends users to a third-party shopping cart, like PayPal, to make purchases.  If cross-domain tracking isn’t implemented correctly across all domains/subdomains involved, your Google Analytics data will be inaccurate.  As a visitor moves from the primary domain to another domain/subdomain, Analytics will create a brand new session, which will result in incorrectly attributed referral traffic.  You can detect this issue if you see a large amount of traffic coming from your domain/subdomain or even from your third-party shopping cart site in the Google Analytics referral report.  Monitoring and assessing your traffic data is essential to discovering this problem and others.

3. Untagged Traffic

In order for your digital advertising traffic to be attributed to the correct source, you must tag your campaign URLs.  UTM parameters are tags that you can add to the end of a URL for tracking purposes. When you add UTM parameters to a URL, you are essentially creating a new URL that provides Google Analytics with information about that traffic, such as source, medium and campaign.  If you do not provide this information, Analytics will see the traffic as a referral source.  If you observe a spike in Facebook referral traffic (for example) in the Google Analytics referral report after launching your Facebook campaigns, you likely forgot to tag your campaign URLs or implemented the UTM parameters incorrectly.  Having a dedicated digital advertising team can help ensure accurate UTM parameters creation and implementation.

4. Website Redesign

Google Analytics data loss is a common problem for websites undergoing a redesign.  You will be anxious to see the impact the new, optimized design has on performance but…there is no data.  The resulting data loss from this error can be frustrating.  A sudden and sustained drop in traffic for the page(s) in Google Analytics will be the main indicator of this issue and performing an SEO audit prior to relaunching is the best way to avoid it.

5. Internal Traffic

Individuals affiliated with your company may visit your website frequently, but have no intention of making a purchase or completing a conversion action.  This can result in your Google Analytics traffic data being inaccurately inflated.  If you are a company that wouldn’t necessarily have increased “local” interest (like an office building for a software company rather than a brick and mortar retail store) you may notice an unexplained concentration of visits coming from your physical location.  Otherwise, this issue can be hard to identify but you can assume it is occurring to some degree.

Unless you carefully monitor and evaluate your website traffic on a regular basis, the problems mentioned above and others may go unnoticed.  You may frequently visit Analytics to gather performance data, but simply reporting on the data Google Analytics is giving you does not guarantee its accuracy.  A thorough assessment is often necessary to ensure you are getting the most value from your Google Analytics account.

Questions or comments?  Continue the conversation below.

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