Experimentation Platform Comparison
A comparison of common A/B testing platforms such as StatSig, Eppo, Microsoft ExP, and Netflix XP
Comparison
This page provides a detailed comparison of features, pricing, and capabilities across StatSig, Eppo, Microsoft ExP, and Netflix XP experimentation platforms.
Scroll down to explore detailed feature comparisons, pricing models, user experiences, and administrative capabilities.
Disclaimer: This comparison is AI-generated based on publicly available information and may not reflect the most current features or pricing of these platforms. The information about Microsoft's ExP is derived from research papers and books, while information about other platforms comes from public documentation. Please verify details with the platform providers before making any decisions. See our research methodology for more details or view reported inaccuracies.
Types of Experimentation Platforms
Organizations can choose between commercial solutions and building custom internal platforms
Commercial Platforms
Off-the-shelf solutions like StatSig and Eppo
Advantages:
- Faster implementation and time-to-value
- Lower development and maintenance costs
- Regular updates and new features
- Dedicated support and documentation
Considerations:
- Subscription costs that scale with usage
- Potential limitations in customization
- May not integrate perfectly with all systems
Internal Platforms
Custom-built solutions like Microsoft ExP and Netflix XP
Advantages:
- Complete customization for specific needs
- Deep integration with internal systems
- No per-user or per-experiment costs
- Full control over data and security
Considerations:
- Significant engineering resources required
- Ongoing maintenance and development costs
- Longer time to implement and iterate
The choice between commercial and internal platforms depends on your organization's scale, resources, and specific needs. Many organizations start with commercial solutions and may build custom components as they mature.
Overview
Comparing four leading experimentation platforms: StatSig, Eppo, Microsoft's ExP, and Netflix's XP. Each has different approaches and strengths for managing A/B tests and feature experiments.
StatSig
A full-stack experimentation and feature flagging platform that emphasizes statistical rigor and real-time analytics.
Key Characteristics:
- Robust statistical engine
- Real-time analytics
Eppo
A modern experimentation platform focused on connecting experiment results to business metrics.
Key Characteristics:
- Deep data warehouse integration
- Advanced metric framework
Microsoft ExP
Microsoft's enterprise-scale experimentation platform used across their products and services.
Key Characteristics:
- Massive scale capabilities
- Advanced trustworthy experimentation
Netflix XP
Netflix's experimentation platform designed for media and content optimization.
Key Characteristics:
- Content-focused metrics
- Long-term impact analysis
Feature Comparison
A detailed comparison of key features between experimentation platforms
| Feature | StatSig | Eppo | Microsoft ExP | Netflix XP |
|---|---|---|---|---|
| Assignment Latency | Very low (milliseconds) | Depends on implementation | Very low (milliseconds) with local evaluation | Optimized for content delivery (low ms) |
| Sample Ratio Mismatch Detection | Automated SRM detection with alerts | Built-in SRM detection | Advanced SRM detection with diagnostic tools | SRM detection with content-specific checks |
| Data Source Support | Built-in + warehouse integration | Strong data warehouse focus | Cosmos DB, Kusto, proprietary telemetry system | Custom data pipeline, Kafka, Spark, Keystone |
| Semantic Metric Definitions | Basic semantic layer with metric groups | Advanced SQL-based definitions with dbt integration | Comprehensive OEC framework with metric hierarchy | Content-focused semantic metrics with long-term impact |
| Feature Flags | Comprehensive built-in system | Basic feature flags, often integrated with other tools | Advanced flight system with sophisticated targeting | Content-specific flags with personalization capabilities |
| Real-time Analytics | Strong real-time capabilities | Depends on data warehouse refresh rate | Near real-time with Kusto and custom pipelines | Mix of real-time and batch processing |
| Statistical Methods | CUPED, sequential testing, Bayesian methods | CUPED, sequential testing, advanced variance reduction | Advanced trustworthy methods, CUPED, interleaving | Long-term impact analysis, quasi-experiments, causal inference |
| SDK Support | JS, React, Node, Python, Go, Ruby, Java, Swift, Kotlin | JavaScript, Python, Ruby, Java, Go | Internal SDKs for C#, TypeScript, C++, Java, Python | Internal SDKs for Java, JavaScript, Python |
| Compute Fabrics Supported | Cloud-based, AWS, GCP, Azure | Cloud-based, integrates with data warehouses | Azure, Cosmos DB, custom distributed systems | AWS, Spark, custom Netflix infrastructure |
| Config Management | UI-based configuration with API access | UI and SQL-based configuration | Advanced config-as-code with version control | Jupyter notebooks and UI-based configuration |
| Extensibility | API-based extensibility, limited customization | SQL-based extensibility, data warehouse integration | Highly extensible with plugin architecture | Modular architecture with custom extensions |
| Metric Framework | Pulse metrics, custom metrics, metric groups | Advanced SQL-based metrics with dbt integration | OEC framework with hierarchical metrics | Engagement, retention, and content metrics |
| Segmentation | Comprehensive user segmentation | SQL-based segmentation with dimension analysis | Advanced user and market segmentation | Content, user, and behavioral segmentation |
| Scale | Millions of users, thousands of experiments | Millions of users, hundreds of experiments | Billions of users, thousands of experiments | Hundreds of millions of users, thousands of experiments |
| Availability | Commercially available | Commercially available | Internal Microsoft only | Internal Netflix only |
Assignment Latency & Implementation
How quickly and efficiently each platform assigns users to experiments
StatSig
- Very low latency (milliseconds) for assignment decisions
- Client and server-side SDKs with local evaluation
- Automatic user assignment with customizable targeting
- Sticky assignments with configurable persistence
Eppo
- Latency depends on implementation approach
- Client and server-side SDKs available
- Flexible assignment with randomization framework
- Support for custom assignment strategies
Microsoft ExP
- Very low latency with local evaluation capabilities
- Flight system with sophisticated targeting rules
- Deterministic assignment for consistent user experience
- Supports billions of assignments per day
Netflix XP
- Optimized for content delivery with low latency
- Personalization-aware assignment algorithms
- Device-specific assignment capabilities
- Household and account-level assignment
Key Differences:
StatSig and Microsoft ExP offer the lowest latency with local evaluation, while Eppo's latency depends on implementation. Netflix XP is specifically optimized for content delivery with unique capabilities for household-level assignments. Microsoft ExP stands out for its scale, handling billions of assignments daily across Microsoft's product suite. Netflix XP is unique in its focus on content-specific assignments and device targeting across TV apps, mobile, and web.
Pricing Comparison
How different experimentation platforms compare in terms of cost and pricing models
Pricing Models
How different experimentation platforms structure their pricing
| Pricing Factor | StatSig | Eppo | Microsoft ExP | Netflix XP |
|---|---|---|---|---|
| Pricing Model | Monthly active users (MAU) based | Monthly active users (MAU) based | Internal cost allocation | Internal cost allocation |
| Free Tier | Yes (up to 1M MAU) | Limited free trial | Not commercially available | Not commercially available |
| Entry-Level Pricing | ~$2,000/month (varies by MAU) | ~$2,500/month (varies by MAU) | Unsure/No data | Unsure/No data |
| Enterprise Pricing | Custom pricing based on scale | Custom pricing based on scale | Internal budget allocation | Internal budget allocation |
| Infrastructure Costs | Included in pricing | Partially included, data warehouse costs separate | Significant Azure infrastructure investment | Significant AWS infrastructure investment |
| Development Investment | Commercial product development | Commercial product development | Large dedicated engineering team | Dedicated engineering and data science teams |
StatSig Cost Structure
Key factors that influence StatSig pricing
Free Tier
- Up to 1M MAU
- Core experimentation features
- Limited data retention
Growth Tier
- Starting at ~$2,000/month
- Scales with MAU
- Advanced experimentation features
Eppo Cost Structure
Key factors that influence Eppo pricing
Free Trial
- Limited time access
- Core features available
- No permanent free tier
Standard Tier
- Starting at ~$2,500/month
- Scales with MAU
- Core experimentation features
Microsoft ExP Cost Structure
Internal cost factors for Microsoft's platform
Internal Platform
- Significant infrastructure investment
- Large dedicated engineering team
- Internal budget allocation model
Scale Costs
- Massive Azure compute resources
- Cosmos DB and Kusto storage costs
- Exact costs not publicly available
Netflix XP Cost Structure
Internal cost factors for Netflix's platform
Internal Platform
- Significant AWS infrastructure investment
- Dedicated engineering and data science teams
- Internal budget allocation model
Scale Costs
- Kafka and Spark infrastructure
- Custom data pipeline maintenance
- Exact costs not publicly available
User Experience
How each platform serves different user roles and needs
Developer Experience
How developers interact with each platform
StatSig
- Comprehensive SDK ecosystem with multiple language support
- Simple integration with minimal code changes
- Integrated feature flags and experimentation
- Local evaluation for low-latency decisions
Eppo
- SDKs for major languages
- Flexible integration options
- Often requires integration with existing feature flag systems
- Strong data warehouse integration
Microsoft ExP
- Internal SDKs optimized for Microsoft tech stack
- Deep integration with development workflows
- Advanced flight system with sophisticated targeting
- Config-as-code with version control integration
Netflix XP
- Internal SDKs optimized for Netflix tech stack
- Device-specific implementation support
- Content-focused experimentation capabilities
- Integration with content delivery systems
Developer Preference Factors:
Microsoft ExP and Netflix XP are highly tailored to their respective companies' tech stacks and workflows, offering deep integration but limited to internal use. StatSig provides the most straightforward commercial implementation with integrated feature flags, while Eppo offers more flexibility for companies with existing data infrastructure. The internal platforms excel in customization and scale but require significant engineering resources to build and maintain, while commercial platforms offer faster time-to-value with less development overhead.
Admin Experience
Administration, governance, and management capabilities
Administration & Governance
How each platform handles administration, security, and governance
| Feature | StatSig | Eppo | Microsoft ExP | Netflix XP |
|---|---|---|---|---|
| User Management | Role-based access control | Role-based access control | Advanced RBAC with Microsoft identity | Custom role system with content permissions |
| Config Management | UI-based configuration with API access | UI and SQL-based configuration | Config-as-code with version control | Jupyter notebooks and UI configuration |
| Audit Logs | Comprehensive audit logging | Comprehensive audit logging | Advanced audit system with compliance | Detailed audit trails for content changes |
| Extensibility | API-based extensibility, limited customization | SQL-based extensibility with data warehouse | Highly extensible plugin architecture | Modular architecture with custom extensions |
| Environment Management | Dev/Staging/Prod environments | Dev/Staging/Prod environments | Advanced environment management with rings | Test/Prod with regional deployment options |
| Scale Management | Managed scaling for commercial customers | Depends on data warehouse scaling | Massive scale infrastructure with auto-scaling | Custom scaling for global content delivery |
| Compliance | SOC 2, GDPR, CCPA compliant | SOC 2, GDPR, CCPA compliant | Enterprise-grade compliance framework | Content-specific compliance controls |
StatSig Admin Experience
Key administrative features and capabilities
Project & Environment Management
StatSig provides comprehensive project and environment management capabilities, allowing administrators to organize experiments and feature flags across different environments (development, staging, production).
User Access Control
Administrators can define granular permissions for different user roles, controlling who can create, modify, or analyze experiments and feature flags.
Extensibility Limitations
Limited to API-based integrations with minimal ability to customize core platform functionality beyond what's provided out-of-the-box.
Eppo Admin Experience
Key administrative features and capabilities
Data Governance
Eppo places strong emphasis on data governance, with advanced controls for managing metric definitions, data sources, and experiment configurations.
SQL-Based Extensibility
Administrators can extend functionality through SQL-based customizations and data warehouse integrations, offering more flexibility than UI-only platforms.
Integration Management
Robust tools for managing integrations with data warehouses, feature flag systems, and other tools in the experimentation stack.
Microsoft ExP Admin Experience
Key administrative features and capabilities
Config-as-Code
Advanced configuration management with version control integration, allowing for code review processes and deployment pipelines for experiment configurations.
Plugin Architecture
Highly extensible platform with plugin architecture that allows teams to build custom modules and extensions for specific needs across Microsoft's diverse product portfolio.
Enterprise Scale
Built to handle massive scale with sophisticated infrastructure that supports billions of users and thousands of simultaneous experiments across Microsoft's products.
Netflix XP Admin Experience
Key administrative features and capabilities
Content-Focused Controls
Specialized administrative controls for content-based experimentation, including regional content regulations and content-specific permissions.
Modular Architecture
Modular design that allows for custom extensions and integrations with Netflix's content delivery and recommendation systems.
Jupyter Integration
Unique administrative approach that combines UI-based configuration with Jupyter notebook workflows for more sophisticated experiment design and analysis.
Admin Experience Comparison
Key differences in administrative capabilities
All four platforms offer comprehensive administrative capabilities, but with significant differences in approach and extensibility:
- StatSig provides the most straightforward commercial solution with an integrated approach to managing feature flags and experiments, but offers limited extensibility beyond API integrations.
- Eppo offers more flexibility through SQL-based customization and data warehouse integration, making it more adaptable for organizations with sophisticated data infrastructure.
- Microsoft ExP represents the most extensible platform with its plugin architecture and config-as-code approach, built for massive scale and diverse use cases across Microsoft's product portfolio.
- Netflix XP offers unique content-focused capabilities with a modular architecture that integrates deeply with Netflix's content delivery and recommendation systems.
- Build vs. buy considerations: The internal platforms (Microsoft ExP and Netflix XP) represent significant engineering investments that would be prohibitively expensive for most companies to replicate, while commercial platforms offer more accessible solutions with faster time-to-value.
For administrators, the choice between these platforms depends on organizational needs, existing infrastructure, and available resources. Commercial platforms offer faster implementation with less customization, while internal platforms provide deeper integration and extensibility but require significant engineering investment. Microsoft's approach emphasizes enterprise-scale governance and extensibility, while Netflix focuses on content-specific capabilities and data science workflows.
Key Platform Differences
Summary of distinctive characteristics and approaches of each platform
StatSig
- All-in-one platform for feature flags and experimentation
- Real-time analytics and immediate feedback capabilities
Eppo
- Sophisticated data warehouse integration capabilities
- Advanced visualization and reporting features
Microsoft ExP
- Enterprise-scale experimentation infrastructure
- Rigorous methodology with trustworthy experimentation
Netflix XP
- Content optimization specialized capabilities
- Long-term impact analysis methodologies
All four platforms offer robust experimentation capabilities, but they excel in different areas. Each platform has been designed with specific use cases and organizational needs in mind, from commercial solutions to internal enterprise platforms.