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How to spot bot (non-human) traffic on your website

We make more and more decisions by using data, and this trend will only continue to grow because data-driven decisions typically outperform other types of decision making.

However, to make good decisions, you need good data. We will focus on website analytics in this post, but the same applies to other forms of analytics.

Most people track their website analytics using Google Analytics, and while Google Analytics is great, it is by no means perfect. Therefore, you cannot just assume that all the information you see in Google Analytics is useful data. 

All websites get hit with bots (non-human visits/hits), so being able to spot them is essential, and more importantly being able to separate spam from real data.

How bots can muddy the water (and result in bad decision making)

Let’s use an example to illustrate this point better. For instance, if you have an e-commerce website and your typical website traffic is 1,000 per week. After restructuring your home page and some catalog pages, you noticed your traffic jumped to 1,500. That’s great, a 50% increase in a week, so your recent website changes must be working, and we should probably double-down and make more changes? 

Not exactly, if we detect that 600 of those hits are spam (bots), then our conclusion is very different because it would show that our traffic dropped from 1,000 to 900. Therefore, restructuring our home page and catalog pages hurt and not helped our website traffic.

Furthermore, bots can skew important metrics like conversion rate, because your conversion rate will drop significantly if your website gets flooded with bots (non-human traffic).

How do you spot bots?

Any spikes in traffic need to be analyzed carefully, and the first question you have to ask yourself, “Is this spike caused by bots or something else?”. If you are using Google Analytics the most obvious places to look are referrals, bounce rate, and session duration. 

Check Referrals 

  • What are referrals? Simply put, a referral is another website linking to your website
  • Do referral URLs look legitimate? Hint: any links with the word “SEO” in it are a red flag

Check Bounce Rate

  • What is bounce rate? It is a percentage of visitors that navigate away from your website after viewing only one page
  • How many of your website visits have 100% bounce rate? 100% bounce rate doesn’t automatically equate to a bot, but if you see a 100% bounce rate with 0:00:00 average session duration than it is probably a bot

Check Average Session Duration 

  • What is the average session duration? It is the average length of a user session. More specifically, how long a visitor has stayed on your website
  • Do you have a lot of website visits with 00:00:00 duration? Sometimes Google Analytics is not able to detect duration, so 00:00:00 duration by itself doesn’t always mean bot/spam. However, as we mentioned, if you see traffic with 00:00:00 duration and 100% bounce rate then it is probably a bot or spam

How do you filter/exclude bots from your Google Analytics report?

You can exclude referral URLs (that look like spam) by adding them to your “Referral Exclusion” list. Simply go to Admin >  Property (select from the dropdown) > Tracking info > Referral Exclusion list. 

Just keep in mind that this will only exclude referral spam you are aware of. Excluding other types of bots and spam will require some manual filtering. This is why many marketers and analytics experts export website analytics data into spreadsheets where it can be sorted and manipulated easily. 


We often see bots and spam cause distortion in website data; hence making it impossible to use for decision making (at least until the data is cleansed). No business or website is immune to spam and bots, so it’s not a question of when your website will get hit by bots and spam, but what percentage of your current traffic can be attributed to non-humans (bots and spam).

Website data is extremely useful and every marketer and business owner should keep a close eye of their analytics, but good decision making is only possible with good data, hence why identifying and eliminating bot data is so important. 

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