A/B Testing Platforms Comparison
Choosing the right experimentation platform for your team. Compare features, pricing, and methodology across the top 8 platforms.
Last updated: December 2025
What to Evaluate
A/B testing platforms differ in statistical methods, integrations, and target audience. Consider these factors when comparing options.
Statistical Methodology
Bayesian vs frequentist, variance reduction (CUPED), and sequential testing support.
SDK Coverage
Language support, SDK quality, and ease of implementation.
Analytics Integration
Native analytics, warehouse connectivity, and third-party integrations.
Enterprise Features
SSO, audit logs, compliance certifications, and role-based access.
Pricing Model
Free tiers, per-seat pricing, usage-based, or enterprise contracts.
Team Fit
Engineering-first vs marketing-first, data maturity requirements.
Feature Comparison
| Feature | Amplitude Experiment Enterprise | Statsig Startup-Friendly | LaunchDarkly Enterprise | Optimizely Enterprise | Split Mid-Market | GrowthBook Open Source | VWO Mid-Market | Eppo Startup-Friendly |
|---|---|---|---|---|---|---|---|---|
| Statistical Engine | Sequential testing | CUPED + sequential | Bayesian | Stats Accelerator | Sequential + Bayesian | Bayesian + frequentist | Bayesian | CUPED + frequentist |
| Feature Flags | Limited | |||||||
| Server-side SDKs | ||||||||
| Client-side SDKs | ||||||||
| Mutual Exclusion | ||||||||
| Holdout Groups | ||||||||
| Analytics Integration | Native (Amplitude) | Warehouse-native | Third-party required | Native + third-party | Third-party required | Warehouse-native | Native (VWO Insights) | Warehouse-native |
| Self-Serve Setup | Limited | |||||||
| SSO/SAML | Enterprise only | Cloud only | ||||||
| Data Warehouse Sync | Limited | Native | ||||||
| Pricing | Included with Amplitude plans. Free tier available. | Free up to 1M events/day. Pro from $150/month. | From $10/seat/month. Enterprise pricing varies. | Custom enterprise pricing. Contact sales. | Free tier available. Team from $33/seat/month. | Self-host free. Cloud from $99/month. | From $199/month for testing. Bundles vary. | Custom pricing based on usage. |
| ExperimentBets | Native Integration | Native Integration | Native Integration | Native Integration | Native Integration | Native Integration | Native Integration | Native Integration |
Platform Details
Product analytics platform with integrated experimentation. Strong behavioral cohort targeting and product analytics integration.
Strengths
- Deep integration with Amplitude Analytics
- Behavioral cohort targeting using existing user data
- Sequential testing reduces time to decision
- Unified product and experiment analytics
Considerations
- Best value if already using Amplitude Analytics
- Experiment features tied to analytics pricing tiers
- Learning curve for teams new to Amplitude
Best for: Teams already using Amplitude Analytics who want unified experimentation
Modern experimentation platform built by ex-Facebook engineers. Known for speed, warehouse-native approach, and generous free tier.
Strengths
- Generous free tier (up to 1M events/day)
- CUPED variance reduction speeds up experiments
- Warehouse-native for data-heavy teams
- Built by team with Meta experimentation pedigree
Considerations
- Newer platform, smaller ecosystem than established players
- Enterprise features require paid plans
- Documentation still maturing
Best for: Startups and growth teams wanting modern tooling with strong free tier
Feature flag platform that expanded into experimentation. Enterprise-grade reliability with strong DevOps focus.
Strengths
- Industry-leading feature flag infrastructure
- Excellent SDK support across languages
- Strong enterprise security and compliance
- Reliable flag delivery at scale
Considerations
- Experimentation is newer addition to core product
- Analytics integration requires separate setup
- Higher price point for full experimentation features
Best for: Engineering teams wanting best-in-class feature flags with experimentation
The original A/B testing platform, now a full digital experience platform. Strong web experimentation and content management.
Strengths
- Longest track record in A/B testing industry
- Visual editor for web experiments without code
- Full digital experience platform (CMS, commerce)
- Strong professional services and training
Considerations
- Enterprise sales process can be lengthy
- Full platform is complex if you only need testing
- Pricing typically requires custom quote
Best for: Large enterprises wanting a complete digital experience platform
Feature delivery platform combining feature flags and experimentation. Strong focus on developer experience and attribution.
Strengths
- Developer-friendly API and documentation
- Attribution engine ties features to metrics
- Strong targeting and segmentation
- Good balance of price and features
Considerations
- Analytics setup requires integration work
- Smaller community than larger competitors
- May need additional tools for full analytics
Best for: Mid-size engineering teams wanting developer-friendly experimentation
Open-source experimentation platform. Self-host for free or use their cloud offering. Popular with data-savvy teams.
Strengths
- Open-source with self-hosting option
- Warehouse-native (uses your existing data)
- No vendor lock-in for core functionality
- Active community and development
Considerations
- Self-hosting requires infrastructure investment
- Cloud offering has fewer enterprise features
- Smaller team than VC-backed competitors
Best for: Data teams wanting warehouse-native experimentation with flexibility
Conversion optimization platform with A/B testing, heatmaps, and session recordings. Strong for marketing and CRO teams.
Strengths
- Complete CRO toolkit (testing, heatmaps, surveys)
- Visual editor for non-technical users
- Strong for marketing and website optimization
- Established player with good documentation
Considerations
- Less suited for product/engineering experimentation
- Feature flags are secondary focus
- Pricing can add up with multiple modules
Best for: Marketing teams focused on website conversion optimization
Warehouse-native experimentation platform. Runs experiments on top of your data warehouse without moving data.
Strengths
- True warehouse-native (data never leaves your warehouse)
- CUPED for faster experiment conclusions
- Modern architecture built for data teams
- Strong statistical rigor and methodology
Considerations
- Requires existing data warehouse infrastructure
- Newer platform, smaller user base
- Best suited for data-mature organizations
Best for: Data-mature teams with warehouse infrastructure wanting statistical rigor
Quick Decision Framework
You're an Enterprise (500+ employees)
Look at Optimizely if you want a complete digital experience platform with professional services. Choose LaunchDarkly if feature flag reliability is critical and you have engineering resources. Consider Amplitude if you're already using their analytics.
You're a Growing Startup (50-500 employees)
Start with Statsig for its generous free tier and modern architecture. Try Split if you want developer-friendly tooling at mid-market pricing. Look at GrowthBook if you prefer open-source and have warehouse infrastructure.
You're Data-First
If your data team drives experimentation, choose warehouse-native options. Eppo offers the strongest statistical methodology. GrowthBook gives flexibility with open-source. Statsig balances ease-of-use with warehouse integration.
You're Marketing-Focused
VWO offers the best marketing-oriented toolkit with heatmaps, surveys, and visual editing. Optimizely works well if you also need content management. Both have visual editors that don't require engineering for every test.
How ExperimentBets Fits In
ExperimentBets is not a replacement for these platforms. It's the engagement layer that makes your existing experimentation program more effective.
Runs experiments, assigns users, tracks metrics
Syncs experiments to Slack. Team bets on outcomes. Engagement goes up.
Pays attention to experiments. Builds product intuition.
Frequently Asked Questions
What's the difference between feature flags and A/B testing platforms?
Feature flags control who sees what features. A/B testing platforms add statistical analysis to measure the impact of those features. Most modern platforms offer both. If you only need flags, LaunchDarkly or Split excel. If you need rigorous experimentation, look at Statsig, Amplitude, or Eppo.
Should I choose Bayesian or frequentist statistics?
Both approaches are valid when implemented correctly. Bayesian methods (LaunchDarkly, GrowthBook) give probability statements and work well with smaller samples. Frequentist methods (Amplitude, Eppo) are more traditional and easier to explain. What matters more is whether the platform applies the methodology correctly and helps you avoid peeking problems.
What is warehouse-native experimentation?
Warehouse-native platforms like Statsig, GrowthBook, and Eppo run experiment analysis on your existing data warehouse (Snowflake, BigQuery, Redshift). Your data never leaves your infrastructure. This is ideal for data-mature teams with privacy requirements or complex metric definitions.
How do I estimate pricing for my team?
Pricing varies by model. Statsig charges by events, LaunchDarkly and Split by seats, and enterprise platforms like Optimizely use custom contracts. Calculate your monthly active users, number of experiments, and team size. Most platforms offer free tiers or trials to test before committing.
Can I use multiple platforms together?
Yes. Some teams use one platform for feature flags (LaunchDarkly) and another for experiment analysis (Eppo, GrowthBook). This adds complexity but lets you pick best-in-class for each function. If you go this route, standardize on one assignment mechanism to avoid conflicts.
How does ExperimentBets work with these platforms?
ExperimentBets is not an A/B testing platform. It's a gamification layer that sits on top of your experimentation platform. We sync experiments from Amplitude, Statsig, or LaunchDarkly into Slack where your team can bet on outcomes. This drives engagement without replacing your testing infrastructure.