Data spam has always been existent in the web analytics accounts and reports. Moreover, over the past years, data spam has turned out to be a real problem. Data spam, in this context, denotes scammers and spammers that pollutes Google Analytics reports with junk links and contents. The main goal of referral spam is to drive traffic to own websites for ad impressions or push malware into the victim’s site. Like email spam, referrals are time wasting and annoying. However, unlike email spam, these nuisances are not visible. It implies that referral spam is embedded in GA reports. The distorting data impacts go unnoticed as a result of referral spam.
Frank Abagnale, the Customer Success Manager of Semalt, elaborates here one practical issues in this regard.
Distorting impacts of data spam
One of the most noticeable effects is inflated numbers of traffic – page views, sessions and, visitors. However, the effect is much more significant than just traffic numbers. For instance, spam visits cause high bounce rate traffic, non-converting and little engagement. They skew “success metrics” downwards. The denominator contains junk every time any performance percentage or ratio is considered.
When “referral traffic” is considered, the problem is significant because the main effect is experienced through leads (visitors’ traffic) that are received from building affiliates, partnerships and, positioning links within social media discussions. It implies that referrals can be valuable traffic. However, spam accounts for over 50 percent of the effect anytime inflated impact on referral visitors only is viewed. This renders the evaluation of referral performance by an internet marketer.
Important filters to remove referral spam
Two types of filters can be used to remove referral spam. First, the Hostname Filter which allows own domain name to drive data to the GA. Secondly, a Referral Source Filter that eliminates spam referrers. These two View filters can be applied to GA data for complete removal of referral spam. Admin rights is a must in GA to achieve this filtration.
The Hostname Filter
It is regarded as a straightforward filter that tells GA to fetch data that originates from the owner’s website only. Third party reports are excluded. While using this filter, internet marketers should be aware of “googleusercontent.” It is the hostname used by Google when visitors use this search engine’s tool known as Google Translate on a site’s content or a webpage. Thus, the use of “googleusercontent” within hostname filter captures and allow its content to be displayed in the GA reports.
The Referrer Source Filter
It eliminates most of the polluting referrers. Additionally, referrer source filter works perfectly for a wide range of sites. However, it is not a definitive list because different organizations have distinct spammers that invade their websites. Therefore, site owners are encouraged to apply this filter and evaluate its impact. One important consideration before using this filter is to gather all spammers and separate them into report set (View). In this manner, the exact referral sources can be monitored, hence establishing any false positive.
The historical data
Filters have configurations for eliminating spam. Users might want to remove historically collected spam within Google Analytics. This cannot be permanently achieved by the use of filters. Instead, a unique segment is applied while viewing reports to help remove historical referral spam.