Dear fake users – who does Google think you are?


Google Analytics is rife with Fake or Ghost referrers, this post takes a look at how Google itself classifies these users by Age, Sex, Interests etc

Anyone with a website that uses Google Analytics must have noticed quite a bit of traffic coming from “Referrals”.

Some of the sites, whose names keep changing every month, also seem to generate quite a bit of traffic for your websites.

Sites such as or or or any of such similar websites.

The funny thing is that these sites don’t really refer any traffic to you (sorry for bursting your popularity bubble). They actually don’t even visit your site, they just tell Google that they did – simple.

The sad part is that after all these years, Google with all its smarts and money hasn’t been able to curb this menace – who doesn’t like (fake) inflated numbers?

Did we say Google had smarts? (oh yes we did) and part of those smarts they also have a “profile” of users that live on the Internet and visit sites all day. They know how old you are, what you like, your gender etc.

We decided to analyze what Google knew about these fake users, so lets take a look from a data perspective.

  • Gender

    Predominantly Male


  • Age

    Fairly young, assuming old people aren’t fake 😉


  • Affinity Categories (reach)

    Whatever this title means, the actual data is better self-explained

    Google Analytics Affinity Categories

  • In-market segment

    Not sure what that means

    In-market segments Google

  • Other Category

    Again – no idea


  • Top 10 Countries for our beloved fake users

    45.3% were from Russia (with love)

    Google Analytics Fake referrers

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