Targeting rules

Overview

This topic explains how to use targeting rules to target segments of users based on their built-in and custom user attributes.

Creating targeting rules

Targeting rules can have one or more conditions.

Each condition has three parts:

• A built-in or custom user attribute, which defines the scope of the condition's impact, such as only targeting an email address. To learn more, read User attributes.
• An operator, which sets differentiating characteristics of the attribute, such as limiting the condition to emails that end with certain extensions. If a condition specifies multiple values for the operator to track, the operator iterates over the array. To learn more, read Operators.
• A value, which identifies the attribute by a value you specify, such as gmail.com.

Here is an image of a user targeting rule:

To create a rule that serves true to all users whose email address ends with gmail.com:

1. Click Add rules icon.

2. Enter a name for the rule.
3. Choose email from the Select an attribute menu.
4. Choose ends with from the Select an operator menu.
5. Enter gmail.com in the values field.
6. Choose true from the serve menu.
7. Click save.

If a targeting rule references any custom attributes with null values, then the flag skips that rule.

You can add multiple conditions to a rule. Here is how rules handle multiple conditions and values:

• Users must meet all the conditions in a rule to match the rule. If any of the conditions are not met, the user will not match the rule.
• If a condition has multiple values, FeatBit considers the condition met if there is a match on any of the values.

Percentage rollouts

If you want only a portion of users matching a rule to receive a particular variation, you can serve a percentage rollout.

Here is an image of the percentage rollout section:

In this example, 25% of users will receive the true variation.

To learn more, read Percentage rollouts.

Experimentation

After you save a targeting rule, you can click the Set A/B test rule button to run an experiment on the rule. To learn more, read Creating experiments.

Here is an image of the et A/B test rule button on a flag's targeting rule:

User attributes

FeatBit includes built-in attributes for users. Here are some examples of common user attributes:

• keyId
• name

For a full list of built-in user attributes, read Built-in user attributes.

FeatBit also allows you to create your own custom user attributes. For instance, you might want to target users based on plan, group, role, location, or organization. Using custom user attributes, you could show some features to users on your regular plan, and additional features to users on your premium plan. Or you could roll out a new feature to 30% of organizations, rather than 30% of users.

To learn more, read User attributes.

Operators

FeatBit supports the following operators:

Setting the default rule

FeatBit defines a final default rule, for any users that don't match any of the targeting rules on the page. As with other rules, you can choose to serve a specific variation, or apply a percentage rollout to any remaining users.

Here is an image of the percentage rollout section:

Now, 30% of all users who have not been targeted by any other rules will receive true.

If you do not want to target users based on user key or any custom attributes, you can use the default rule to control the flag's rollout for all users.

Setting the default off variation

When the toggle is turned off, FeatBit will serve the default off variation for your feature flag. For boolean flags, the default off variation is set to false. For multivariate flags, you select one of your custom variations. You can customize the default off variation for both boolean and multivariate flags in the Targeting tab.

Evaluation order

The Targeting tab evaluates rules in the order below:

If feature is turned ON

1. Targeting individual users
   
   1. First variation
   2. Second variation
   3. Third variation
   4. ...
2. Targeting user customized rules
   
   1. First rule displayed in UI
   2. Second rule displayed in UI
   3. Third rule displayed in UI
   4. ...
3. Target remaining users through the configuration in Default Rule

If feature is turned OFF

Serve variation pre-defined in OFF section\