Handling Fake Traffic & Bogus Referrals

An analysis is only as good it’s referral data. A brief look at almost any company’s raw data would show their figures are intertwined with a number of odd-looking referrals and links. So how does one remove these stains that are ruining our “pure data”? In this blog, we will highlight several spam solutions that could help you feel more confident in the information you are gleaning from analytics.

To begin, almost all spam comes from one of two sources; spam crawlers and ghost bots. Spam crawlers actually go to your site and navigate around, making them appear to be a normal user. On the other hand, ghost bots never actually makes it to your site, instead they go directly to your Google Analytics (GA) site and this registers as a view on GA, despite never actually visiting your page.

Before implementing any spam solutions, there are two notes we should explore.

Note 1: The very first thing you should do when implementing spam control is to create a new “view” in GA. DO NOT implement spam control on the original view in GA. Spam control can be finicky to perfect, and if done wrong, historical data could be wiped out leaving you with nothing to refer back. Every GA property is given room for many views and creating a new view only takes a couple mouse clicks. Name your new view “Spam Control” and your old view as “Raw Data”. Now you have access to both all your historical raw data and you have a new view to adjust the spam moving forward.

Note 2: Spam is an evolving beast that will find a way around your spam implementations. The fixes I suggest here will be effective but in time the spam will find ways around it. Since spam can be seen as a living breathing embodiment of poor data, we too must stay active in implementing the newest spam control to avoid corrupting our data.

Spam Bot Removal

What follows are some simple steps for removing spam and implementing spam filters for both ghost bots and spam crawlers.

Ghost Referrals: Spam Filter Implementation

While under the administration tab in GA, navigate over to the “Spam Control” view you created and hit “Filters”

  • Select “Add Filter”
  • Name your filter (For example maybe “Hostname Filter”)
  • Under the filter type select “Custom”
  • Select the toggle for “Include”
  • Under “Filter” field select “Hostname”
  • In the “Filter Pattern” field add your Domain Address
  • Hit “Save”

With this filter implemented, any Ghost Bots trying to hit your analytics will be ignored.

Spam Crawlers: Spam Filter Implementation

Step 1: Identify those domains that are filling your sites with inaccurate information. If the referring domain seems reasonably fake, for example “Free-social-buttons.org” or “get-Free_traffick-Now.net” then they these domains should be added to the list. In Google Analytics under the “Acquisitions” tab, select “All Traffic”

  • In the area that lets you select a secondary dimension, select “Hostname”

From here, you can see where your referrals are coming from. Any domain that is unrecognizable or blatantly wrong should be added to a list for Step 2 of this implementation.

Step 2: Filter your list of domains from Step 1 so they don’t register on Analytics

  • Go to the Admin Section of your analytics
  • Under “Account” navigate to the “Filters” section
  • Click on the “Add Filter” button
  • Going down the filters select the “Exclude” toggle and select “Referral” as the filter field
  • Enter the domains you have collected from Step 1 and put one in the filter pattern
  • Hit “Save” and repeat for the rest of your list of domains.

With these two filters in place, the vast majority of the spam affecting your analytics will be gone, no longer leaving you to draw false conclusions and allowing you to focus on pure data and improve the functionality of your site.


Removing spam calls for a treat