Oct 21, 2014

Google Analytics Spam?

How To Refine Your Analytics Metrics And Improve Data Integrity using Filters

You already have to worry about spam in your email, social media accounts, and telemarketers; now you have to worry about spam in your Google Analytics data too! If your Analytics reports contain spam or bad data, it can be harmful to make important decisions as a result of that data.

If you’ve looked through your “referrals” (other websites that send traffic to your website) in Google Analytics, you may have noticed a website called semalt.com. It’s a spam SEO website based in the Ukraine. Traffic on your website from their spam bot can throw off your web metrics, inflating your bounce rates and visits, lowering your time on site and pages per visit. This is just one example of bad data, your account could contain more.

Here is how to filter spam and bad data from your Analytics Reports

This example will prevent Google Analytics from recording data from referral sources that you specify. This tutorial shows how to exclude semalt.com from your Google Analytics, however other filters can be applied in a similar way.


Step 1 - When logged into Google Analytics, choose admin from the top menu.

google analytics spam step 1

Step 2 - Create a view to apply your filters to. It is a good idea to have at least two views. Have one called unfiltered that will never have any filters applied to it (this is your backup view). Your other view can be called filtered, this is what you are going to apply your filters to, and use for reporting and decision making.

google analytics spam step 2

Step 3 - Create Your Filter. When you have your Filtered view setup, you can add filters to it by choosing the Filters option.

google analytics spam step 3

Step 4 - Fill out the filter fields as follows, then click save.

google analytics spam step 4

This process will not erase semalt.com from your data history, it will only prevent Google Analytics from recording this data in the future.

You should add an annotation to your Analytics reports to record why your Analytics Metrics may have changed on that date. For example, I’d add an annotation that says “excluded semalt.com from reports by adding a referral filter.”

google analytics notation example

Tip

Add more filters as appropriate. Try filtering your office’s traffic. Traffic from you and your employees does not represent behavior from customers and prospects, and is skewing your data.  Visit http://www.whatismyip.com/ to find your IP address and add an IP filter in Google Analytics.

The reason we created a backup unfiltered view is because filters permanently alter the recorded data. Having an unfiltered view as a backup allows us to fall back to something in the event we discover one of our filters was set up incorrectly.

It’s important to stay proactive with your analytics data. It can shed a lot of insight as to why changes in traffic volume and visitor behavior on your site are happening. It’s important to ensure your Analytics data has integrity before taking action as a result of it.

If you need help with this or want to learn more about how your Google Analytics data can guide your digital marketing programs, feel free to give us a call.