Best A/B Testing Tools 2026
Compare the top 18 A/B testing and experimentation platforms. Features, pricing, pros & cons for enterprise, startups, and everything in between.
Quick Comparison
Overview of all A/B testing tools at a glance
| Tool | Best For | Platforms | Free Tier | Starting Price | Stats Engine |
|---|---|---|---|---|---|
 Optimizely | Enterprise experimentation | Web, Mobile, Server-side | $36,000/year | Frequentist + Bayesian | |
 VWO | Marketing teams | Web, Mobile, Server-side | Custom | Frequentist + Bayesian | |
 LaunchDarkly | Feature management | Web, Mobile, Server-side | Custom | Frequentist | |
 Statsig | Developer-first teams | Web, Mobile, Server-side | Free - $450K/year | Sequential + Bayesian | |
 GrowthBook | Data transparency | Web, Mobile, Server-side | Free / $20/user/month | Bayesian + Frequentist | |
 PostHog | All-in-one product analytics | Web, Mobile, Server-side | Free / Usage-based | Bayesian + Frequentist | |
 AB Tasty | Personalization + testing | Web, Mobile, Server-side | ~$20,000/year | Bayesian | |
 Amplitude Experiment | Product-led experimentation | Web, Mobile, Server-side | Free / $49/month | Sequential + Bayesian | |
 Eppo | Statistical rigor | Data warehouse | Custom | Bayesian + Frequentist | |
 Firebase A/B Testing | Mobile-first apps | iOS, Android | Free | Frequentist | |
 Split.io | Engineering teams | Web, Mobile, Server-side | Custom | Frequentist | |
 Convert | SMB experimentation | Web | $399/month | Frequentist | |
 Mida | Lightweight no-code testing | Web, SPA | Free / $199/month | Frequentist | |
 Kameleoon | Full-stack enterprise | Web, Mobile, Server-side | Custom | Frequentist | |
 Crazy Egg | Quick visual tests | Web | $99/month | Basic Frequentist | |
 Flagsmith | Open source flags | Web, Mobile, Server-side | Free / $45/month | Basic | |
 Unleash | Open source enterprise | Web, Mobile, Server-side | Free / $80/month | Basic | |
 Apptimize | Mobile A/B testing | iOS, Android | Custom | Frequentist |
Detailed Reviews
In-depth analysis of each A/B testing platform
Category
Features
Showing 18 of 18 tools
Best for: Enterprise experimentation
Starting at
$36,000/year
Free tier
No
Pros
- Industry-leading platform with proven track record
- Comprehensive feature set for enterprise needs
- Strong statistical engine with multiple methodologies
Cons
- Very expensive for SMBs and startups
- Steep learning curve for advanced features
Best for: Marketing teams
Starting at
Custom
Free tier
Yes
Pros
- All-in-one platform (testing + analytics + insights)
- Intuitive interface for non-technical users
- Strong visual editing capabilities
Cons
- Advanced features only on expensive plans
- Less developer-friendly than pure feature flag platforms
Best for: Feature management
Starting at
Custom
Free tier
Yes
Pros
- Best-in-class feature flag management
- Excellent developer experience with top-tier SDKs
- High uptime and performance (local caching)
Cons
- Expensive at scale (dual charging for flags + MAU)
- Experimentation features less advanced than specialized platforms
Best for: Developer-first teams
Starting at
Free - $450K/year
Free tier
Yes
Pros
- Exceptional value (50-80% cheaper than LaunchDarkly at scale)
- Feature flags completely free, unlimited
- Advanced statistical methodology (sequential testing)
Cons
- Newer platform (less market maturity)
- Smaller ecosystem and community
Best for: Data transparency
Starting at
Free / $20/user/month
Free tier
Yes
Pros
- Open source with no vendor lock-in
- Complete data transparency and control
- Unlimited traffic, flags, and experiments
Cons
- Self-hosted requires DevOps resources
- Less enterprise governance than proprietary platforms
Best for: All-in-one product analytics
Starting at
Free / Usage-based
Free tier
Yes
Pros
- Open source with generous free tier (1M flag requests/month)
- All-in-one: analytics, flags, experiments, session replay, surveys
- Both Bayesian and Frequentist statistical engines
Cons
- Experimentation features less mature than dedicated platforms
- Stops ingesting data when free limits are exceeded
Best for: Personalization + testing
Starting at
~$20,000/year
Free tier
No
Pros
- Comprehensive suite for A/B testing and personalization
- Strong visual editor for marketers
- European data hosting options (GDPR-friendly)
Cons
- Expensive for SMBs
- Learning curve for advanced features
Best for: Product-led experimentation
Starting at
Free / $49/month
Free tier
Yes
Pros
- Unified analytics and experimentation in one platform
- Unlimited feature flags on all plans including free
- Advanced statistics with sequential testing and CUPED
Cons
- Full experimentation requires Growth plan (custom pricing)
- Primarily analytics-focused, experimentation is add-on
Best for: Statistical rigor
Starting at
Custom
Free tier
Yes
Pros
- Uncompromising statistical rigor
- Warehouse-native for data control
- Automatic quality checks (SRM detection)
Cons
- Requires data warehouse infrastructure
- Higher barrier to entry
Best for: Mobile-first apps
Starting at
Free
Free tier
Yes
Pros
- Completely free for most use cases
- Seamless integration with Firebase ecosystem
- Zero setup if already using Firebase
Cons
- Mobile-only focus (limited web support)
- Basic statistical features
Best for: Engineering teams
Starting at
Custom
Free tier
Yes
Pros
- Strong balance of feature flags and experimentation
- Engineering-friendly with robust SDKs
- Flexible pricing that scales with usage
Cons
- Less visual/marketing-friendly
- Pricing not transparent
Best for: SMB experimentation
Starting at
$399/month
Free tier
No
Pros
- Transparent, affordable pricing
- Strong focus on education and support
- Privacy-focused with GDPR compliance
Cons
- Limited mobile app support
- Less advanced than enterprise platforms
Best for: Lightweight no-code testing
Starting at
Free / $199/month
Free tier
Yes
Pros
- Ultra-lightweight 8KB script with ~20ms load time
- AI-powered test generation with MidaGX
- No-code visual editor for non-technical teams
Cons
- Web-only (no native mobile app support)
- Limited to 5 active projects on Growth plan
Best for: Full-stack enterprise
Starting at
Custom
Free tier
No
Pros
- Strong security and compliance (GDPR, HIPAA)
- AI-powered personalization
- European data hosting options
Cons
- Very steep learning curve
- Limited native third-party integrations
Best for: Quick visual tests
Starting at
$99/month
Free tier
Yes
Pros
- Very affordable entry point
- Fast setup and easy to use
- Combines heatmaps with A/B testing
Cons
- Basic A/B testing features
- Limited statistical rigor
Best for: Open source flags
Starting at
Free / $45/month
Free tier
Yes
Pros
- Open source with no vendor lock-in
- Self-hosting for complete control
- Generous free tier for cloud
Cons
- Less focus on experimentation vs feature flags
- Self-hosted requires infrastructure management
Best for: Open source enterprise
Starting at
Free / $80/month
Free tier
Yes
Pros
- Enterprise-grade open source
- Strong governance and compliance
- Both self-hosted and managed options
Cons
- Self-hosted requires infrastructure expertise
- Experimentation less mature
Best for: Mobile A/B testing
Starting at
Custom
Free tier
No
Pros
- Mobile-specialized platform
- Visual editing without code changes
- No app store resubmission needed
Cons
- Mobile-only (no web support)
- Expensive compared to alternatives
How to Choose the Right Tool
Key factors to consider when selecting an A/B testing platform
Team Structure
- Marketing-led teams:VWO, Optimizely, AB Tasty
- Engineering-led teams:LaunchDarkly, Statsig, Split.io
- Small teams/startups:GrowthBook, Firebase, Crazy Egg
Platform Requirements
- Web-only:Any platform (most supported)
- Mobile-first:Firebase, Apptimize, Statsig
- Multi-platform:Optimizely, LaunchDarkly, Statsig
Budget Constraints
- Free/Low budget:Firebase, GrowthBook OSS, Flagsmith
- Mid-market ($100-$10K/mo):Convert, Statsig, GrowthBook cloud
- Enterprise ($10K+/mo):Optimizely, VWO, LaunchDarkly
Statistical Rigor
- Basic testing:Most platforms sufficient
- Advanced methodology:Statsig, Eppo, GrowthBook
- Warehouse-native:Eppo, GrowthBook, Statsig
2026 Trends in A/B Testing
What's shaping the experimentation landscape this year
Warehouse-Native
Platforms like Statsig, Eppo, and GrowthBook are leading the shift to warehouse-first architectures.
Better Statistics
Sequential testing and Bayesian approaches are becoming standard for faster, more accurate results.
Privacy Focus
GDPR compliance and data sovereignty are critical factors in platform selection.
Feature Flags + Testing
The line between feature management and experimentation continues to blur.
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