How to Keep Your Analytics Clean: Removing Unwanted Bot Traffic

How to Keep Your Analytics Clean: Removing Unwanted Bot Traffic

As an experienced marketer with a keen eye for accurate data, you understand the importance of clean analytics. In the digital age, the presence of bots crawling your website can muddy the waters, making it challenging to make informed decisions. In this article, we’ll explore various methods to filter out bot traffic from your analytics.

Why Remove Bot Traffic?

 A report released by Imperva in 2023 found that bots comprised nearly half (47.7%) of Internet traffic, while bad bots accounted for more than a quarter of traffic. While not all bots are malicious, they can still skew your data and compromise the accuracy of your analytics. While many bots do their best to act like humans, there is no intent behind their actions – their actions are random, leading to distorted insights. By effectively filtering out these bots, you create a space where your analytics genuinely represent authentic human actions, preferences, and decisions. This shift enables you to extract insights that empower you to make well-informed decisions, fine-tune your strategies, and ultimately drive growth.

While GA4 offers built-in bot filtering, it is not comprehensive. GA4 may block known spam-related bot traffic, but “other” bots can still appear in your session, engagement, and conversion data. Let’s explore the other options for removing bots from your analytics data.

Method 1: Robots.txt

Robots.txt, a simple text file residing on your web server, plays a crucial role in directing web crawlers and search engine spiders, influencing how they interact with your web pages. This file has the power to prevent search engines from indexing your website, but improperly configured robots.txt files can lead to your site being entirely omitted from search engine listings.


  • A fundamental and widely recognized method for controlling web crawlers
  • Easy implementation through simple text file editing
  • Provides a clear directive to web crawlers, guiding their behavior on your site
  • Some bots consuming bandwidth can slow down your website’s performance


  • Compliance is voluntary, meaning bot operators often choose to ignore this directive if they feel its in their best interest
  • Limited control over precisely which bots are blocked, since you either have to block all bots or know the bots by name that you want to let in. 
  • Improperly configured robots.txt files can lead to exclusion from search engine listings
  • Blocking quality assurance bots may limit reach on content or ads because the platforms can’t validate the content is safe and within platform guidelines 

Method 2: IP Address Filtering

IP Address Filtering offers a method to selectively control web traffic by identifying and blocking specific IP addresses, making it a valuable tool in combatting bot activity.


  • Provides precise control over which IP addresses to block, allowing targeted protection
  • Effectively blocks known bots, bolstering security against malicious traffic


  • Requires continuous monitoring and updates to adapt to evolving bot tactics
    • About 30% of bad bot requests originate from residential IPs, making them hard to distinguish from real users
  • Misconfiguration can inadvertently block legitimate users, necessitating careful setup and maintenance
  • Blocking quality assurance bots may limit reach on content or ads because the platforms can’t validate the content is safe and within platform guidelines

Method 3: Customizing Google Analytics Views

If you spend time searching the web for a solution to this problem, you will undoubtedly run across solutions involving filters in Google Analytics. These solutions rely on Universal Analytics and are not applicable to GA4, the current version of Google Analytics. As Universal Analytics cannot collect data after July 2023, there is currently no effective way to use filters or view settings in Google Analytics to remove bot traffic outside of referrer spam (see below).  

Method 4: Referral Exclusions Lists in GA4

Referral Exclusions Lists in GA4 offer an effective way to combat referral spam, helping maintain data quality by filtering out unwanted referral-based bot traffic.


  • Effectively eliminates referral spam, maintaining the accuracy of your data
  • Allows for the creation of conditions to identify and exclude specific domains as referral sources


  • Limited to dealing with referral-based bot traffic
  • Will not block the majority of bots which will either use a legitimate referrer or no referrer at all

Method 5: AI-Bot Detection Tools

AI-bot detection tools automate the process of identifying and mitigating bot traffic, distinguishing between human and automated activity by analyzing connection type and device data.


  • Automates the bot detection process, saving time and effort
  • Can identify subtle patterns indicative of bot behavior
  • Enhances security by mitigating the risks associated with malicious bot activity


  • Can be costly, especially for advanced AI solutions
  • May produce false positives or negatives, leading to the blocking of legitimate traffic or allowing some bot activity to go undetected
    • Researchers have found that while many bot-detection models claim high accuracy rates, these rates are often a result of their performance on the specific dataset they were trained on
  • Often limited to “bad” bots so users don’t prevent good bots, like quality assurance bots, from visiting their website

Method 6: Click Fraud Software

Click fraud software is designed to detect and prevent fraudulent clicks in pay-per-click (PPC) advertising campaigns. It helps advertisers safeguard their budgets, improve ad performance, and maintain the integrity of their advertising efforts.


  • Click fraud software effectively identifies and prevents fraudulent activity in PPC advertising campaigns
  • It offers detailed tracking of the sources of invalid traffic, helping advertisers make informed decisions
  • Utilizing click fraud software can lead to significant cost savings for advertisers spending 5-figures or more per month in online advertising


  • Limited to select paid channels only; does not apply to organic or referral traffic, or ad platforms that don’t provide IP filtering and dispute processes
  • Implementing click fraud software does not guarantee an immediate improvement in campaign performance
  • It may have limited blocking capabilities when dealing with sophisticated click fraud tactics
  • Using this software often requires a substantial initial investment
  • Most don’t filter the traffic, only prevent future traffic from the fraudster’s IP
  • Focused exclusively on fraud bots and does not filter other types of bots from your analytics

Method 7: Bot Filtering Tools

Bot filtering tools are specialized solutions designed to identify and block bot traffic from loading into your analytics instance. These tools analyze various data points, including IP addresses, user agents, and more, to ensure that only genuine human traffic is counted.


  • Bot filtering tools automate bot detection, saving valuable time and effort in the process
  • These tools are cost-effective compared to other paid solutions, making them budget-friendly
  • Installation is straightforward and user-friendly


  • While they filter bots out of analytics, they do not provide extensive tracking of invalid traffic sources
  • The use of Google Tag Manager is required for these tools to function effectively
  • Bot filtering tools lack detailed tracking capabilities for identifying the sources of invalid traffic
  • Because they filter traffic from Tag Manager and analytics platforms, but allow the traffic to hit the website, they do nothing to limit server load

A Note About Bot Traffic

It’s important to recognize that no single tool or method can guarantee the complete removal of all bot traffic from your analytics. Bots come in various shapes and sizes, and some are adept at evading detection (and getting better every day). However, this shouldn’t deter you from taking action. Implementing bot-filtering measures, even if they are not foolproof, is a proactive step in the right direction. Doing something to mitigate bot interference is far more beneficial than doing nothing at all. By making an effort to filter out a significant portion of bot traffic, you can significantly improve the accuracy and reliability of your analytics, giving you a more solid foundation for data-driven decision-making.

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