If you’re using PostHog to track user behavior and product analytics, it’s essential to filter out internal team members and test accounts to keep your data accurate. In this guide, you’ll learn how to set up PostHog internal user filtering to ensure clean and reliable analytics.
Why You Should Filter Internal Users in PostHog
By default, PostHog captures all events—including those from developers, marketers, QA testers, and anyone on your team. This can skew data and lead to misleading insights. Setting up filters for internal and test users in PostHog helps:
- Keep your conversion rates accurate
- Ensure event data reflects real user behavior
- Avoid false signals in A/B testing
Steps to Exclude Internal Users in PostHog
1. Go to Settings
From the PostHog sidebar, navigate to Settings. Scroll down to find the section called “Filter out internal and test users.”
2. Add Filtering Rules
You can filter users by various properties, such as:
- IP address (e.g., office IPs or VPNs)
- Email domain (e.g., @yourcompany.com)
- Custom user properties
- URL parameters (for test sessions)
Example: To exclude specific IPs
- Property: IP address
- Operator: does not contain
- Value:
192.168.1.1, 10.0.0.1(use commas to separate multiple values)
Read this article to learn everything you need to know about Filters.
3. Use Multiple Filters if Needed
PostHog supports multiple rules at once, helping you build a comprehensive internal user exclusion filter. Combine filters like IP address + email domain for better accuracy.
4. Apply Globally or Per Insight
You can choose to:
- Toggle “Enable this filter on all new insights” for global filtering
- Or manually apply filters on individual reports or dashboards
Maintain Clean Data in PostHog
Adding these filters ensures you’re analyzing clean, trustworthy data. This is especially important when you rely on PostHog for product decisions, marketing performance, or feature testing.
Conclusion
Setting up PostHog internal user filtering is one of the best ways to maintain clean analytics and improve decision-making. Whether you’re launching experiments or measuring product engagement, filtering out your internal team ensures your data reflects real users.
PostHog also has a detailed guide on this topic — you can check it out here.
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