Understanding individual targeting in feature management

Individual targeting lets you assign specific users to different feature variations. This method is perfect for testing or providing tailored experiences. You can personalize user experiences by selecting individual users for specific features. This approach ensures only selected users see new changes, helping you gather focused feedback.

Best practices for individual targeting

• Keep targeting rules concise. Overly complex rules can slow down your system and confuse users.

• Review and update contexts regularly. Ensure your targeting remains relevant and accurate.

• Utilize segments for broader audiences. Segments maintain performance and simplify management.

• Limit individual targets. For optimal performance, keep individual targets under 10,000.

• Schedule removal dates. Set dates to remove temporary targets, like in trial features.

• Use custom context keys. Target based on specific user attributes for more precise control.

• Monitor performance impacts. Regularly check if individual targeting affects system speed.

Scheduling and managing individual targeting

Scheduling removal dates

Set future removal dates for targeted contexts. This is useful for trial features and beta tests. It helps keep your targeting rules organized. For more details on setting up and managing such features, refer to the documentation.

Removing contexts from targeting

Navigate to the targeting page. Edit and remove contexts as needed. This keeps your targeting list clean and efficient. You can learn more about removing contexts to maintain an organized targeting list. For a comprehensive understanding, check out the Statsig glossary on behavioral targeting.