User-Specific Feature Flag Targeting

Target specific users by ID to enable features for beta testers, internal teams, or individual accounts. Fine-grained control for feature previews.

Targeting

Detailed Explanation

User-Specific Targeting

User targeting enables a feature for specific individuals by their user ID. This gives you precise control over who sees a feature, making it ideal for beta programs, internal testing, and VIP access.

Configuration Example

{
  "advanced-analytics": {
    "name": "Advanced Analytics Dashboard",
    "description": "New analytics with real-time charts and custom reports",
    "type": "boolean",
    "enabled": true,
    "defaultValue": false,
    "targeting": [
      {
        "type": "user-ids",
        "userIds": "user-001, user-042, user-108, admin-jane, admin-bob"
      }
    ]
  }
}

LaunchDarkly Targets

In LaunchDarkly, individual targeting uses the targets array:

{
  "targets": [
    {
      "variation": 0,
      "values": ["user-001", "user-042", "user-108", "admin-jane", "admin-bob"]
    }
  ]
}

Unleash UserWithId Strategy

Unleash uses the userWithId strategy:

{
  "strategies": [
    {
      "name": "userWithId",
      "parameters": {
        "userIds": "user-001,user-042,user-108,admin-jane,admin-bob"
      }
    }
  ]
}

Combining with Other Rules

User targeting is often combined with other rules. The evaluation order typically is:

  1. Individual targets (highest priority) -- specific user IDs
  2. Segment rules -- group-based targeting
  3. Percentage rollout -- catch-all for remaining users
  4. Default value -- fallback when no rules match

When to Use User Targeting

Scenario Example
Internal testing Enable for your team before launch
Beta program Give early access to opted-in users
VIP customers Premium features for enterprise accounts
Debugging Enable verbose logging for a specific user
Demo accounts Always show the latest features

Scaling Considerations

Individual user targeting works well for small lists (up to a few hundred users). For larger groups, use user segments instead to avoid maintaining long user ID lists in your flag configuration.

Use Case

A product team builds a new analytics dashboard and wants to gather feedback before launch. They enable the feature for 5 internal users and 10 beta testers by their user IDs. Once feedback is incorporated, they switch to a percentage rollout for broader release.

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