Build flags
Manage flags
Optimizely Feature Experimentation Flags are the foundation of Optimizely Feature Experimentation. They give your team full control over how and when features reach your users, without requiring a code deployment.
Flag statuses in Feature Experimentation
Flag statuses show where each flag is in its lifecycle draft, testing, live, paused, stale, or archived. Feature Experimentation calculates all statuses automatically (using the ruleset state, rule state, environment type, and time-based activity signals), except archived, which you set manually.
Flag variations and flag variables overview
Optimizely Feature Experimentation Flag variations let you avoid hard-coding variables in your application. Instead of updating the variables by deploying, you can group them in a flag variation and edit them remotely in the Optimizely app.
Idea builder for Optimizely Experimentation
Idea builder is a dedicated tool in Optimizely Experimentation that helps you generate experiment ideas using Opal, Optimizely's AI assistant. Provide structured context about your page, goal, and research, and Opal returns specific, actionable test ideas you can save, refine, and act on.
Create flag variables
Optimizely Feature Experimentation Flag variables let you add and configure more than one variable in a single experiment variation . For example, you can create a feature flag with several variables like color, size, and text.
Create flag variations
Optimizely Feature Experimentation A flag variation is a reusable group of flag variable values (also called remote feature configuration or remote variables) that let you avoid hard-coding values in your code. Instead of waiting for a deployment, you can group them in a flag variation and then update them remotely in the Optimizely Experimentation application.
Target audiences in Feature Experimentation
Optimizely Feature Experimentation Audiences give you control over which users can access your flag rules, for example, A/B tests , targeted deliveries , or multi-armed bandit optimizations . A single audience is defined based on custom user attributes you create.
Define user attributes to build audiences in Feature Experimentation
Optimizely Feature Experimentation Use attributes to build the audiences that see your experiments, and use the Attributes tab to manage your user attributes. To create a new attribute key Go to Audiences > Attributes .
Create advanced audience combinations in Feature Experimentation
Optimizely Feature Experimentation Using the Optimizely Feature Experimentation UI https //app. optimizely.
Build Feature Experimentation audiences in ODP
Use the real-time audience builder to create, edit, and manage audiences for Optimizely Feature Experimentation directly within Optimizely Data Platform (ODP). Create specific customer groups using ODP audiences, attributes, and event data, then target these groups within your flag rules.
Manage scheduled changes in Feature Experimentation
Optimizely Feature Experimentation You can schedule changes to an existing flag or rule , such as Turn a flag on or off . Play or pause a rule.