Understanding targeting flags

Definition and purpose of targeting flags

Targeting flags let you control which users see a specific feature. You can think of them as customizable switches. They allow you to turn features on or off for different users based on set conditions. This helps you test features with specific segments before a full rollout.

Importance in feature rollouts

Using targeting flags in feature rollouts is crucial. They help you manage risk and ensure stability. For example, you can release a new feature to only 10% of users. If everything goes well, you can gradually increase availability. This way, you can catch and fix issues before they impact all users.

Benefits of precise targeting

Precise targeting offers several benefits:

• Improved user experience: Only relevant users see new features.

• Better feedback: Target specific groups for more useful insights.

• Risk management: Roll back features easily if something goes wrong.

By using targeting flags, you can make data-driven decisions and enhance user satisfaction.

Key components of targeting flags

What elements make up targeting rules?

Targeting rules decide who sees your feature. They consist of context kinds, attributes, operators, and values. Each rule checks if a user meets specified conditions.

Context kind defines the scope, like user or device. Attributes are details like email or location. Operators determine how attributes are matched, such as "equals" or "contains."

Values are specific criteria used in rules. For example, an email ending in ".edu." Together, these elements ensure precise feature targeting. For more information on attributes and operators, you can refer to Statsig Docs on Feature Flag Conditions.

Real-world use cases

Rolling out a new feature: Target a specific user segment. Introduce features gradually. Learn more about Reusable Targeting with User Segments.

Gradually increasing availability: Start with 10% of users. Increase in stages. Monitor performance. Check out Feature Flags for more details.

Rolling back features: If bugs appear, revert quickly. Return users to the previous version. Ensure stability. For best practices, visit Feature Flag Best Practices.