Referral Spam in GA4
The other day, we were going through Google Analytics with a client, specifically looking at recent website traffic and if there were any significant trends. As we were scrolling through the different sources, the client suddenly got very excited when they noticed a website that had driven hundreds of users to the website. However, our reaction was less ecstatic, give the adjacent information that was apparent to us – the website in question was a nonsensical subdomain that was unheard of, the hundreds of “users” had an average engagement time of zero seconds, and the website had driven no traffic in the previous period we were comparing against.
This story is all too common to us advertisers, as analyzing website traffic is a significant component of our jobs. But, if the websites aren’t driving any real traffic, then what are they doing? Are these users the so-called bots that we often hear about? Are these somehow malicious or attempts to steal our data? What exactly are those random websites showing up in Google Analytics?
More often than not, this unusual source of website traffic is a result of referral spam. In its simplest form, referral spam is a result of automated scripts of code being executed, known as bots, with the specific purpose of triggering Google Analytics page views (reported as users) on other websites.
The general concept behind referral spam is that with the website in question showing up as a significant traffic source, you as the user of Google Analytics will manually investigate said websites in question. This manual navigation to the websites is fundamental to the “success” of referral spam. Common malicious uses for referral spam include:
· Affiliate links – the source website will navigate to a random e-commerce store through a referral link, allowing for the referrer to be compensated.
· False storefronts – the source website will appear like a storefront, possibly tricking you into making a purchase or to be retargeted with ads.
· SEO boosts – Generally, the more traffic a website generates, the higher its SEO ranking. Visiting the source website could improve the SEO ranking of an illegitimate website by increasing traffic through direct visits.
It is important to understand that not all bots or mysterious referrals are necessarily illegitimate (e.g. search engines crawlers), but such referrals are usually much lower in volume than referral spam is.
Aside from having a better understanding of website traffic, monitoring referral spam can also clue you into potential causes for degrading website performance due to increased page views or in rare cases, potential security breaches. While referral spam is unavoidable, as long as you do not directly visit the source websites (i.e. copying and pasting the links into your browser), referral spam is fairly harmless.
Most importantly, identifying referral spam allows you to filter through “false” website traffic (i.e. users who did not actually spend any time on the website), otherwise inaccurate conclusions through false increases in volume or decreases in engagement time and other metrics could be drawn. Ultimately, vigilantly monitoring Google Analytics for referral spam is crucial to holistically understanding website activity.