Feature Experimentation
Optimizely Feature Experimentation is feature management and A/B testing for product teams. Run experiments anywhere in your technology stack with server-side SDKs.
Key Capabilities
Feature Flags - Launch features safely with a kill switch
A/B Testing - Run experiments in any application
Server-Side - Experiment anywhere in your stack
Zero Latency - In-memory bucketing, no blocking network requests
Documentation Sections
Explore the sections below to learn how to integrate Feature Experimentation with your tools and services.
Articles in this section
Putting Optimizely Feature Experimentation into production: SDK setup, consistent bucketing across services, rollout patterns, webhook verification and flag cleanup.
2-Step Bucketing Pre-bucket Users Without Tracking Impressions
Two-Step Bucketing with DISABLE_DECISION_EVENT: Pre-bucket Users Without Tracking Impressions
How to verify your Optimizely webhook signature (Step-by-step)
Verify your Optimizely webhook signature step by step to authenticate datafile update notifications and reject forged requests before you process them.
Optimizely Mobile SDK Setup: iOS and Android
Set up Optimizely Feature Experimentation SDKs on iOS (Swift) and Android (Kotlin): install, manage the datafile, evaluate flags, and track events.
Feature Flag Best Practices for Production Systems
Feature flags turning into a mess? Learn to classify, name, roll out, and retire flags safely at scale with Optimizely Feature Experimentation.
Server-Side A/B Testing with Optimizely: A Practical Guide
Run server-side A/B tests with Optimizely Feature Experimentation. Setup, SDK decision and tracking code, audiences, and pitfalls to avoid in production.
Optimizely Global Holdouts: Measure the Real ROI of Your Experimentation Program
A global holdout measures the true cumulative ROI of your experimentation program. How Optimizely native Global Holdouts work, and how to run and read one.
Canary Deployment: Progressive Delivery with Feature Flags
A canary deployment releases changes to 1% of users first, then ramps to 100% with instant rollback. How progressive delivery works with feature flags in Optimizely.
Blue-Green Deployment with Feature Flags: Cut Over Safely and Roll Back Fast
Learn how blue-green deployment works, when to use it, and how Optimizely feature flags add user-level control, measurement, and instant rollback.
Find Unused Feature Flags (and Dangling References) in Your Codebase
optipilot-find-code-refs reconciles the flag keys in your code against the live Optimizely Feature Experimentation inventory, reporting orphan flags (live but unused) and zombie references (called in code but archived). CLI and GitHub Action.
Connect Feature Experimentation with analytics and data platforms
Forward Google Analytics 4 Events to Feature Experimentation
Forward Google Analytics 4 events into Optimizely Feature Experimentation so your existing GA4 conversions become experiment metrics without rebuilding them.
Google Analytics 4 Integration for Feature Experimentation
Track Feature Experimentation server-side experiments in Google Analytics 4 with notification listeners and GTM
Integrate Adobe Analytics with Optimizely Feature Experimentation
Integrate Adobe Analytics with Optimizely Feature Experimentation using SDK notification listeners, with client-side and server-side code examples.
Integrate Contentsquare with Optimizely Feature Experimentation
Integrate Contentsquare with Optimizely Feature Experimentation using SDK listeners and Dynamic Variables to segment heatmaps and session replays by variation.
Integrate Segment with Optimizely Feature Experimentation
Integrate Segment with Optimizely Feature Experimentation using SDK notification listeners in JavaScript, Node.js, and Python to route decisions downstream.
Integrate RudderStack with Optimizely Feature Experimentation
Integrate RudderStack with Optimizely Feature Experimentation. Covers the native Optimizely Fullstack destination for conversions, the identify-to-activate footgun, a DECISION notification listener (JavaScript, Node.js, Python) for streaming decisions to your warehouse, legacy mobile device mode, identity mapping, and troubleshooting.
Integrate Amplitude with Optimizely Feature Experimentation
Integrate Amplitude with Optimizely Feature Experimentation via SDK decision listeners in JavaScript, Node.js, and Python, plus Amplitude Audience Sync.
Integrate FullStory with Optimizely Feature Experimentation
Integrate FullStory with Optimizely Feature Experimentation using SDK decision listeners, the V2 Browser API, and the Server API for Node.js and Python.
Integrate Google Tag Manager with Optimizely Feature Experimentation
Integrate Google Tag Manager with Optimizely Feature Experimentation using SDK decision listeners in JavaScript, Node.js, and Python to route variations to GA4.
Integrate Heap with Optimizely Feature Experimentation
Integrate Heap with Optimizely Feature Experimentation using SDK decision listeners and the Heap HTTP Track API, with JavaScript, Node.js, and Python code.
Integrate Mixpanel with Optimizely Feature Experimentation
Integrate Mixpanel with Optimizely Feature Experimentation using SDK decision listeners in JavaScript, Node.js, and Python, plus user profiles and Cohort Sync.
Integrate mParticle with Optimizely Feature Experimentation
Integrate mParticle with Optimizely Feature Experimentation using DECISION listeners across Android, iOS, JavaScript, React, and React Native.
Integrate Pendo with Optimizely Feature Experimentation
Integrate Pendo with Optimizely Feature Experimentation using SDK decision listeners in JavaScript, Node.js, and Python to segment Pendo analytics by variation.
Integrate PostHog with Optimizely Feature Experimentation
Integrate PostHog with Optimizely Feature Experimentation using SDK decision listeners in JavaScript, Node.js, and Python to segment funnels by variation.
Integrate Tealium with Optimizely Feature Experimentation
Integrate Tealium with Optimizely Feature Experimentation via SDK decision listeners in JavaScript, Node.js, and Python so variations travel with events.
Forward Amplitude Events to Optimizely Feature Experimentation
Forward Amplitude events into Optimizely Feature Experimentation as conversions, either from your own application code or with an Amplitude webhook streaming sync.
Integrate Datadog or New Relic with Optimizely Feature Experimentation
Tag Datadog or New Relic APM traces with Optimizely Feature Experimentation flag decisions to monitor latency, errors, and throughput by variation.
Analyze Optimizely Feature Experimentation Data in Snowflake or BigQuery
Analyze Optimizely Feature Experimentation data in Snowflake or BigQuery via native data sharing, S3 Parquet export, or Warehouse-Native Analytics.
Integrate Localytics with Optimizely Feature Experimentation
Send Optimizely Feature Experimentation flag decisions to Localytics on iOS and Android to segment mobile analytics and funnels by experiment variation.
Integrate Sentry with Optimizely Feature Experimentation
Forward Optimizely Feature Experimentation decisions into Sentry as tags, context and breadcrumbs, with browser, Node.js and Python listeners.
Integrate Amazon Redshift with Optimizely Feature Experimentation
Land Optimizely Feature Experimentation decisions in Amazon Redshift with Firehose or COPY, and query revenue per variation from first exposure.
Integrate Firebase with Optimizely Feature Experimentation
Forward Optimizely Feature Experimentation decisions into Firebase as user properties and events, on the web and through the Measurement Protocol.
Integrate LogRocket with Optimizely Feature Experimentation
Filter LogRocket session replays by Optimizely variation using decision listener traits and events, with browser, Node.js and Python examples.
Integrate Braze with Optimizely Feature Experimentation
Send Optimizely Feature Experimentation decisions to Braze as custom attributes and events, using the Web SDK or the users/track REST API.
Integrate Zapier with Optimizely Feature Experimentation
Send Optimizely Feature Experimentation decisions to a Zapier webhook without burning your task quota, with Node.js and Python listeners.
Integrate Hotjar with Optimizely Feature Experimentation
Segment Hotjar heatmaps, recordings and surveys by Optimizely variation using the Identify and Events APIs, with browser and server examples.
Integrate June with Optimizely Feature Experimentation
Forward Optimizely Feature Experimentation decisions into June as user traits, company group traits and events for account-level B2B analysis.
Integrate Matomo with Optimizely Feature Experimentation
Segment self-hosted Matomo reports by Optimizely variation using visit-scoped custom dimensions and the HTTP Tracking API, with code examples.
Integrate Snowplow with Optimizely Feature Experimentation
Attach Optimizely Feature Experimentation decisions to every Snowplow event as a validated entity, with schemas and browser, Node and Python code.
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