Don’t Bust Those Ghosts (Spam). Filter Them.

In a bit of reverse psychology, we created a blog last week that hinted at the insight provided in today’s post. That brings to mind this past Friday’s discussion. We talked about the importance of blocking referral spam from affecting your Google Analytics data. Remember the two types of referral spam that both quickly affect data?

Yahtzee! Ghost spam and crawler spam.

For crawler spam, we recommended that you contact your website administrator, or the person who manages your .htaccess file, to update the code that will block this type of spam.

Ghost spam, however, does not actually access your site. It uses measurement protocol to send data directly to Google Analytics—here is a great reference list that shows many known ghost and crawler referrals. Because of this, it’s important to set up filters in your Google Analytics to ensure that this information is not compromising your data.

I Ain’t Afraid of No Ghosts (Spam).

The first step is logging into your Google Analytics and use the Admin tab to locate the appropriate Account. We highly recommend keeping one view within your Account unfiltered and full of data. Once you begin filtering or implementing any changes within Google Analytics, there is no way to change or edit past information.

So keeping one View unchanged will give you all of your website’s information at a further date, should that need arise.

In the example below, we built a secondary view titled “Reunion – Filtered.” Once this is set up, it’s time to add those filters to those ghosts. Click on the Filters button, and you are now ready to go.

Now, click on the +New Filter button to create your ghost spam referral filter. We can call this Referral Spam under the Information section.

The next step is to click on the Custom toggle. Select Field under the Filter Field, then type in Campaign Source. Now you’re ready to add the ghost referrals that you do not want. You can add from the list we linked above, or you can check your GA to find the ones that have the greatest impact on your data.

Some great examples are free-floating-buttons.com, social-buttons.com, 4webmasters.org, traffic2money.com, and floating-share-buttons.com, but there are many more out there.

We recommend ensuring that you filter out ghost spam here, but again, block access to the crawler spam because that spam does actually visit your website.

Take a moment. Relax. After all, even Egon Spangler would have a time with Ghost-filtering.

Let’s get back to work…

When writing your referral websites, just put in the domain name—be sure not to include the www—then separate your different domains with a vertical bar (Shift + Slash). Add in all of the domains you would like and verify the filter at the bottom. This ensures that your filters work properly.

Once verified, Save the filter. All of this traffic will no longer affect your data, so you can once again make accurate and actionable decisions based on what’s actually happening on your website.

Note: Some digital strategies loath their referral spam so much, they only include the sources they know are submitting legitimate traffic. This is not a practice that we use, but it is one that has a solid rationale for many businesses and is something you may want to consider.

Here is an example of what we put in our GA filter pattern. It is something that we will add to as we identify more new ghost spam traffic trying to pollute our data.

floating-share-buttons\.com|social-buttons\.com|simple-share-buttons\.com|free-share-buttons\.com|free-social-buttons\.com|4webmasters\.org|trafficmonetize\.org|traffic2money\.com|get-free-social-traffic\.com|event-tracking\.com

If you have any questions about measuring your data and analytics as well as using that data to increase your traffic and conversions, be sure to contact us with any questions.

2 comments
  1. The Power of Google Analytics Goal Setting
    October 30, 2015 at 8:01 pm

    […] behind each and every click is a real person who is on your website for a reason (be sure you are filtering out spam traffic, so you know you’re looking at real people within your analytics). Who are they? What are they […]

    Reply
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