How to filter out internal users on signup page, when the users are not identified yet/anonymus?
To filter out internal users on the signup page when users are still anonymous (not yet identified), you face a challenge: Mixpanel’s cohort exports and integrations (such as with Appcues, Chameleon, Kameleoon) only work with identified users—anonymous users (those without a user profile or who haven’t been identified with .identify()) are not exported or matched in these systems. This is a limitation across Mixpanel’s integrations and cohort sync features, as stated in the documentation for Appcues, Chameleon, and Kameleoon integrations.For anonymous users, Mixpanel assigns a random $device_id and does not have access to user properties (like an internal/external flag) until the user is identified. Therefore, you cannot directly filter out internal users at the signup page level using Mixpanel cohorts or user properties, since those properties are only available after identification.Best Practice: - If you can infer internal users based on device, IP, or other session-level data before identification, you could add a custom event property (e.g., is_internal: true) to the anonymous events at the time of tracking. This would allow you to filter these events in Mixpanel reports by this property, even before the user is identified. - However, the knowledge sources do not provide a built-in Mixpanel feature for automatically filtering out internal users among anonymous users at the signup page level.Summary: You cannot use Mixpanel’s cohort or user property filtering to exclude internal users on the signup page before they are identified. You would need to add a custom event property at the time of event tracking if you have another way to detect internal users while they are still anonymous. Otherwise, filtering by user properties is only possible after identification, as Mixpanel’s identity management and cohort features require identified users to function as filters or segments Appcues Integration Chameleon Integration Kameleoon Integration.If you need to filter out internal users in reports or Data Views after identification, you can do so using user properties, but not for anonymous users at the signup page.
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To identify internal users before they are authenticated (i.e., while still anonymous), you can use properties available at the time of the event—most commonly, the IP address. Here’s how you can approach this:
1. Using IP Address to Flag Internal Users
If your internal users access your site from known IP ranges (e.g., your company’s office IPs), you can check the client’s IP address server-side and add a custom property such as is_internal: true to the event when it matches your internal IP list. For example: LBKS{ "event": "Signup Page Viewed", "properties": { "is_internal": true, "ip": "136.24.0.114" } }LBKSThis allows you to filter out these events in Mixpanel reports by the is_internal property, even before the user is identified.How to set the IP address in Mixpanel:
- For server-side tracking, set the ip property in your event payload to the client’s IP address (not the server’s IP). Mixpanel will use this for geolocation and you can use it for your own filtering logic as well Define IP Address.
- You can add any custom property (like is_internal) based on your own logic before sending the event.
2. Limitations with VPNs
If internal users use a VPN, their IP address may not match your internal IP ranges, making this method unreliable in those cases. VPNs can mask the true IP address, so you may not be able to consistently identify internal users this way.
3. Summary
- Custom property: Add something like is_internal: true to events if you can detect internal users by IP or other means.
- IP-based detection: Works if you control the network, but is unreliable if users are on VPNs or remote networks.
- No perfect solution for VPNs: If users are on VPNs, you may not be able to reliably identify them as internal until they authenticate.For more details on setting IP addresses and custom properties in Mixpanel, see the documentation on manual geolocation tracking and IP address handling.
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