Optimizely Feature Experimentation
A/B testing tools
Personalization software
Mobile app optimization software
Feature management software
Conversion rate optimization tools
Application development software
Mobile development software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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What is Optimizely Feature Experimentation
Optimizely Feature Experimentation is a feature flagging and experimentation platform used to roll out, test, and measure product changes across web and mobile applications. It supports engineering and product teams running controlled experiments, progressive rollouts, and targeted feature delivery. The product emphasizes developer workflows (SDKs, APIs, and integrations) alongside experimentation analytics to connect feature releases with user behavior and business outcomes.
Integrated flags and experimentation
The product combines feature flag management with A/B testing workflows in a single system. Teams can run progressive deliveries and controlled experiments without maintaining separate tooling for release control and measurement. This reduces handoffs between engineering and growth teams and helps standardize how experiments are implemented and evaluated.
Developer-focused implementation options
Optimizely provides SDK-based implementation patterns suited to application development teams. It supports common rollout patterns such as percentage rollouts, targeted audiences, and kill switches. These capabilities align with modern release practices where teams need controlled deployments across multiple environments.
Targeting and segmentation controls
The platform supports delivering different experiences to defined user segments, enabling personalization-style use cases tied to feature delivery. Teams can target by attributes and contexts relevant to product usage and experimentation design. This helps organizations test changes on specific cohorts before broader exposure and manage risk during releases.
Engineering effort required
Feature experimentation typically requires instrumentation, event design, and SDK integration work. Organizations without strong engineering support may find setup and ongoing maintenance heavier than visual-only testing approaches. Experiment quality depends on consistent tracking and careful implementation across clients and services.
Complexity at scale
As the number of flags, experiments, and segments grows, governance becomes more difficult. Teams often need naming conventions, lifecycle management, and access controls to avoid stale flags and conflicting experiments. Without disciplined processes, results interpretation and operational reliability can degrade.
Not a full marketing suite
While it supports targeting and experimentation, it is not designed as an end-to-end customer engagement platform with broad campaign orchestration. Organizations seeking email/SMS automation, CRM-style workflows, or full CDP capabilities may need additional systems. This can increase integration requirements for unified personalization programs.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Rollouts (Free Feature Flagging) | $0 — Free (no credit card required) | Unlimited feature flags, controlled/staged rollouts, SDKs for web/mobile/server, remote configuration, run one experiment at a time (free tier). Source: Optimizely Free Feature Flagging page. |
| Feature Experimentation (Paid) | Custom pricing — Request pricing / Contact sales | Paid plans are custom-quoted (MAU-based licensing); billed based on Monthly Active Users (MAUs) and typically sold on 12-month subscriptions. Includes advanced experimentation, audience targeting, SDKs across languages, cached data files. Official site requires contacting sales for exact pricing. Source: Optimizely Plans & Pricing and Support pages. |
Seller details
Optimizely, Inc.
New York, NY, USA
2010
Private
https://www.optimizely.com/
https://x.com/optimizely
https://www.linkedin.com/company/optimizely/
