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UPDATE: As of 4th February 2020, the ‘Network Domain’ and ‘Service Provider’ dimensions in Google Analytics have been marked as ‘no longer supported’ and are returning (not set) values – so filtering bot traffic just got a little bit tougher and some of the recommendations below may no longer be applicable. 


Bot Spam traffic in Google Analytics has EXPLODED in the last few years. We’re seeing it all the time in our clients’ accounts. More and more we’re seeing this bot traffic attributed to Amazon.

In fact, I was inspired to write this blog after a query from one of our clients:

“Why is there over a 30% difference in total users from our filtered GA view to our unfiltered view. I can’t believe it’s all spam”– said Client X.

It turns out the answer was spam and most of it was attributed to Amazon.

So, sit back, relax and prepare yourself to learn all about Amazon bot spam, how we find it and what we do about it.

Should I Worry About Bot Traffic in Google Analytics?

The short answer is: Yes. The longer answer is: Definitely. Yes. 100%. Why are you even asking? Are you serious?

We need to filter out bad bots from Google Analytics so that we can be confident that the data we report on (the traffic totals, behavioural insights and conversion rates etc) are really from human beings, not bots. Our clients are data-driven organisations, so the data that is driving their decisions MUST BE accurate.

How did we Find this Spam?

Some things we look for when trying to identify bot traffic in client accounts are:

  • Low site engagement
  • High bounce rates
  • No goal completion

 When you see all the above things, you might just have found yourself some spam!

 How to Check Your Google Analytics Account

In Analytics, navigate to Audience Technology > Network.

Add a table filter on Service Provider with a substantial amount of sessions (say 200+) and bounce rates higher than 90%.


Ahhh, here we see the usual suspect…Amazon. In this example, we have multiple variations of “traffic” from Amazon including “amazon technologies inc”, “ inc” and “amazon data services uk”.

Let’s look at the evidence. The “traffic” from these have some things in common: have very high bounce rates, low pages/session and average session duration of just 1 second or below. Looks suspicious, right? It’s because it is.


Want more proof? Add “City” as the secondary dimension, and you will find that this “traffic” often comes from either Ashburn or Boardman – exactly where Amazon’s data centres are located.


Don’t do a lot of business in Ashburn or Boardman? No? Neither does this client but as you can see, this client is getting a substantial amount of low-quality traffic from “Amazon”. But now – it’s not really from Amazon, is it?

How Did we Deal with this Amazon Bot Traffic?

1.    Enable Bot Filtering

Go to Admin > View Setting and tick the box to filter out “known” bots and spiders. This filter excludes all known bots/spiders listed by the Interactive Advertising Bureau. It provides some degree of protection but won’t fully protect your site against all bots and spam traffic. Still, it’s a good way to start protecting your site from known bots and spiders.


TOP TIP! Don’t enable this on your main reporting View. Create a Test View first, so that you can see what data is being excluded. It’s best practice to run tests on all filters including filters from Google.

2. Set up an ISP Domain Filter

Remember our screenshot above where we found that there was a substantial amount of suspicious traffic from “amazon technologies inc”, “ inc” and “amazon data services uk”?  Add Network Domain as the secondary dimension and you’ll see that the Network Domain for this traffic is “”.


Using this data, we recommend creating an ISP Domain filter to filter out this traffic. This is what it looks like:



Don’t forget to verify your filter to make sure it will work!

And there you have it, how to find and how to exclude bot traffic from Amazon!

What are your thoughts on spam traffic in Google Analytics? What precautionary measures do you take? Happy to hear your comments!