What is Optimizely Feature Experimentation?
Optimizely Feature Experimentation is a full-stack experimentation and feature management platform built for product, engineering, and data teams. Run A/B and multivariate tests across web, mobile, and server-side environments from a single SDK. Feature flags, audience targeting, and real-time results all come built in.
The Stats Engine supports multiple statistical methods, including sequential testing, Bayesian, and frequentist (fixed horizon), so teams can choose the approach that fits their traffic, goals, and decision-making style. Results stay valid throughout, with false discovery rate controls and outlier smoothing built in. Multi-armed bandits automatically shift traffic to winning variations. AI agents review experiments before launch, generate variations, and surface insights from results.
From controlled rollouts and instant rollbacks to full-stack experimentation across every digital surface, Optimizely compresses the cycle from hypothesis to validated decision.
Categories & Use Cases
Videos
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Screenshot of Feature Flag Setup. Here users can run flexible A/B and multi-armed bandit tests, as well as: - Set up a single feature flag to test multiple variations and experiment types - Enable targeted deliveries and rollouts for more precise experimentation - Roll back changes quickly when needed to ensure experiment accuracy and reduce risks - Increase testing flexibility with control over experiment types and delivery methods
Product Demos
Technical Details
| Deployment Types | SaaS |
|---|---|
| Mobile Application | No |
| Supported Countries | All |
FAQs
What is Optimizely Feature Experimentation?
Optimizely Feature Experimentation unites feature flagging, A/B testing, and built-in collaboration—so marketers can release, experiment, and optimize with confidence in one platform.
What are Optimizely Feature Experimentation's top competitors?
VWO, AB Tasty, and LaunchDarkly are common alternatives for Optimizely Feature Experimentation.