Step-by-Step Guide to Filtering Referral Spam in Google Analytics

To effectively filter referral spam in Google Analytics, follow these steps:

 
1. Identify the referral spam domains:    
        
   • In Google Analytics, navigate to the "Acquisition" report.
        
   • Click on "All Traffic" and then "Referrals."
        
   • Look for suspicious domains with high bounce rates, low session durations, or 100% new sessions.
        
   • Common referral spam domains include "semalt.com," "buttons-for-website.com," and "darodar.com."
      
    
   
2. Create a new view for filtered data:    
        
   • In the Admin section of Google Analytics, click on "View Settings" under the view you want to filter.
        
   • Click "Copy View" and name it "Filtered Data" or something similar.
        
   • This new view will contain your filtered data, while the original view remains unaltered.
      
    
 
3. Set up a referral exclusion list (for Universal Analytics):    
        
   • In the Admin section, click on "Tracking Info" and then "Referral Exclusion List."
        
   • Add the domain names of the referral spam sources you identified earlier.
        
   • This step ensures that Google Analytics doesn't attribute sessions to these spam referrals.
      
    
 
4. Create filters to exclude referral spam (for Universal Analytics):    
        
   • In the Admin section, click on "Filters" under the "Filtered Data" view.
        
   • Click "Add Filter" and name it "Exclude Referral Spam."
        
   • Select "Custom" as the filter type and choose "Campaign Source" as the filter field.
        
   • In the filter pattern, enter the referral spam domains separated by a pipe symbol (|), e.g., "semalt.com|buttons-for-website.com|darodar.com".
        
   • Save the filter and repeat the process for other spam domains if necessary.
      
    
 
5. Configure unwanted referrals in Google Analytics 4:    
        
   • In the Admin section of GA4, click on "Data Streams" and select your web data stream.
        
   • Under "More Tagging Settings," click on "Configure your domains."
        
   • In the "Unwanted referrals" section, add the spam referral domains you want to exclude.
        
   • Save your changes to apply the filters to your GA4 data.
      
    

For more information on identifying and filtering referral spam in GA4, refer to the .

By following these steps, you can effectively filter referral spam in both Universal Analytics and Google Analytics 4, ensuring your data accurately reflects genuine user interactions with your website.

Identifying and Handling Referral Spam in Google Analytics 4

Google Analytics 4 (GA4) handles referral spam differently than Universal Analytics. In GA4, you can identify and manage unwanted referrals directly within the platform:

 
1. Identify unwanted referrals in GA4:    
        
   • In GA4, navigate to the "Traffic acquisition" report.
        
   • Click on the "Session source/medium" dimension to view referral sources.
        
   • Look for suspicious referral sources with high bounce rates, low engagement, or unusual naming conventions.
      
    
 
2. Configure unwanted referrals in GA4:    
        
   • In the Admin section, click on "Data Streams" and select your web data stream.
        
   • Under "More Tagging Settings," click on "Configure your domains."
        
   • In the "Unwanted referrals" section, add the spam referral domains you identified earlier.
        
   • Save your changes to apply the filters to your GA4 data.
      
    
 
3. Use the ignore_referrer parameter for individual events:    
        
   • If you want to exclude specific referrals for individual events, you can use the ignore_referrer parameter.
        
   • Set the parameter to true when sending events to GA4 to ignore the referrer for those specific events.
        
   • This approach allows you to selectively filter referral spam for certain events while maintaining referral data for others.
      
    

It's important to note that GA4 automatically detects and filters out some common referral spam domains. However, regularly monitoring your referral sources and manually configuring unwanted referrals ensures comprehensive filtering of referral spam in your GA4 data.

For a step-by-step guide on configuring unwanted referrals in GA4, check out this .

Monitoring and Maintaining Referral Spam Filters

Once you have implemented referral spam filters in Google Analytics, it's crucial to monitor and maintain them regularly. Here are some best practices to keep your data clean and accurate:

 
• Regularly review your referral sources:    
       
  • Set a reminder to check your referral sources every month or quarter.
       
  • Look for any new or unusual referral domains that may indicate new spam sources.
       
  • Add any newly identified spam domains to your filters or unwanted referrals list.
     
   
 
• Update your filters as needed:    
       
  • As spammers evolve their tactics, you may need to update your filters to capture new spam patterns.
       
  • If you notice a significant increase in referral traffic from a previously unknown source, investigate and add it to your filters if necessary.
     
   
 
• Collaborate with your team:    
       
  • Ensure that all team members working with Google Analytics are aware of the referral spam filters in place.
       
  • Encourage team members to report any suspicious referral sources they encounter.
       
  • Maintain documentation on your referral spam filtering process and the domains you have excluded.
     
   
 
• Stay informed about referral spam trends:    
       
  • Follow Google Analytics forums, blogs, and social media channels to stay up-to-date on the latest referral spam trends and techniques.
       
  • Engage with the Google Analytics community to learn from others' experiences and share your own insights.
     
   

By regularly monitoring and maintaining your referral spam filters, you can ensure that your Google Analytics data remains accurate and reliable, providing valuable insights for your website's performance and user behavior.

Remember, while filtering referral spam is essential, it's just one aspect of maintaining data integrity in Google Analytics. Other important considerations include:

 
• Properly configuring your tracking code and property settings
 
• Filtering out internal traffic and bot traffic
 
• Regularly auditing your Google Analytics setup to ensure data accuracy
 
• Educating your team on best practices for data collection and analysis

By taking a proactive approach to data integrity, you can maximize the value of your Google Analytics insights and make informed decisions to improve your website's performance.

Referral spam can significantly skew your Google Analytics data, leading to inaccurate insights and misguided decision-making. By implementing effective referral spam filters in both Universal Analytics and Google Analytics 4, you can maintain the integrity of your data and focus on genuine user interactions. Stay vigilant, monitor your referral sources regularly, and adapt your filters as needed to ensure your Google Analytics data remains a reliable and valuable resource for your website's success.