Semalt Expertise: Removing Referral Spam From Google Analytic Reports

23.05.2018

Semalt Expertise: Removing Referral Spam From Google Analytic Reports

Sometimes Google Analytics may depict a strange in ux of referral traf c to a site without any special promotions or outstanding content. It gets dif cult to explain how this happened and why it did. To get the correct information, one should be getting rid of the referral spam permanently.

Lisa Mitchell, the Customer Success Manager of Semalt, explains how to x the problem of in ux and unwanted spam.

Referral Spam Referral spam occurs when a website receives referral traf c from spam bots or programs. The information appears in Google Analytics account reports which mess with the data contained there and breeds issues with reporting.

They are easy to spot and may have sources from all over the world. Other times, it gets more covert, but referral traf c with 100% bounce rates is most probably a referral spam.

If one is still not sure, with a good malware program at hand, they can visit the site personally to view if the traf c has any impact. The technique used with referral spams is that recurring website requests rake referral URLs to the https://rankexperience.com/articles/article1050.html

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target website. A Ghost spam is that which receives does not need a spammer to visit the site they wish to target.

Fixing Referral Spam Some people claim that one can exclude referral spam. The information is not entirely right, and it is vital that one refrain from using the list of referral exclusions found in Google Analytics.

The reason is that it is used to exclude traf c from a third-party shopping cart. It prevents customers from counting as traf c if they return to opt out of the site. Google Analytics attempts to connect the returning visitors to a prior source, or medium, thus excluding it as part of referral traf c. So, by excluding these referrals, the bad referral traf c will redirect to a different medium/source, and thus still skew in the analytics.

Removing Spam the Way The exclusion list is not the best way to x the issue of referral spam. The method lters, but not exclude spam traf c. Therefore, the traf c from each view has to be ltered off using the referral exclusion option. The following methods help to achieve this: 1. Create a new lter form called "Referrer Spam" at the view level 2. Set the option type to "custom" 3. In the eld option, set "campaign source" 4. The pattern eld lter should contain the referral spam domain as follows 5. Save The method deletes the speci c traf c from these views. It is crucial that users keep a copy of this in a text le for future use. Some of the best practices include having a web developer check the regular expression, making sure that they check the option for ltering known bots and spiders. The lters take 24 hours from implementation to take effect.

Create a Custom Segment Custom segments help keep spam data off the Google Analytic reports. They are a bit unpredictable which is why users should abide by the following: 1. Open the reporting view in GA and Add Segment, select New Segment (No Spam), then Advanced conditions 2. Indicate "sessions" and "exclude" in the options used to lter 3. Select "matches regex" and "source" https://rankexperience.com/articles/article1050.html

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4. Paste the regular expression saved previously After this, then save and then apply. It removes all ghost spam from the reports leaving clean data.

Referral traf c needs to be regularly monitored to make sure that all ghost data does not appear in the GA reports.

The likely scenario here is that when one removes a single spam website, hundreds, if not thousands more, crop up.

It means that the basic cleansing used will not hold for long. However, whether one takes on a technical, or nontechnical approach, it is possible to get rid of referral spam from the Google Analytics data.

Referral spam presents skewed analytics which results in false reports. Reports need accurate representations of data and traf c rates. Skewed data cannot be relied on to show what works and does not for the website.

https://rankexperience.com/articles/article1050.html

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