Top 22 A/B Testing Companies in 2026

Gilzor provides A/B testing services to help clients evaluate different versions of their digital interfaces and features in a structured manner. We integrate testing into the development flow so that decisions rely on actual user behavior and preferences rather than assumptions alone. Our work supports smoother iterations that align with project requirements and user expectations.

We combine quality assurance practices with user-centered approaches to deliver clear results from each test cycle. This allows us to identify what works well and make adjustments that fit naturally into ongoing development efforts. We keep the process straightforward and focused on practical outcomes that matter for the product.

Optimizely brings full-stack experimentation capabilities designed for larger organizations that need reliable testing across different environments. The company developed a platform that combines A/B testing with feature testing and server-side experiments while incorporating AI features to support decision making. It allows teams to run tests on websites, mobile apps, and even backend systems through various integration points.

Optimizely includes tools for personalization and audience targeting that work together with its experimentation engine. Companies often connect it to their existing content management setups and marketing technology stacks. The platform features a stats engine for analyzing results and predictive models that help forecast potential outcomes. This setup gives product and marketing teams more control over how they launch and measure changes without heavy reliance on developers for every test.

VWO built its reputation as a popular choice for web testing through a platform that combines a visual editor with behavioral insights. The company offers tools that let marketers create and launch experiments without deep coding knowledge while still providing solid data analysis. It brings together quantitative test results and qualitative user behavior data in one place for a better understanding of customer actions.

VWO supports feature experimentation alongside traditional A/B tests and includes personalization features driven by customer data. The platform comes with session recordings, heatmaps, and form analytics that help uncover friction points. Companies can run server-side tests through SDKs available in several programming languages. This mix of visual tools and deeper analytics makes it practical for teams working on continuous website improvements.

AB Tasty created a low-code and no-code platform that works particularly well for marketing teams and e-commerce businesses. The company focuses on making experiment setup fast through visual editing tools that reduce the need for developer involvement. It includes personalization options based on user segments and real-time behavioral data to adjust experiences dynamically.

AB Tasty handles feature rollouts with progressive delivery methods and supports testing across web, mobile, and other channels. The platform offers AI assistance for building experiences and generating test ideas. Companies use it to run experiments on different customer touchpoints while maintaining control over how changes go live. This approach helps marketing and product teams move quicker without sacrificing technical reliability.

Convert Experiences specializes in privacy-focused A/B testing while offering advanced targeting capabilities that many CRO agencies rely on. The company built its platform around reliable experiment delivery with features like flicker-free testing and strong server-side support. It emphasizes compliance and data protection alongside solid testing functionality.

Convert Experiences provides full-stack experimentation tools including feature flags and controlled rollouts. The platform includes detailed segmentation with many available filters and supports multiple statistical approaches for result analysis. Companies value its lightweight implementation that does not slow down websites. This combination of privacy features and technical depth makes it suitable for organizations with strict data requirements and complex testing needs.

Kameleoon delivers flicker-free experimentation along with Bayesian statistics in its platform. The company built tools that let teams create and run tests quickly through AI assistance while maintaining performance on modern websites and applications. It focuses on real-time reporting and reliable data handling that works well for European markets and regulated environments.

Kameleoon supports both visual editing and code-based approaches for experiments. Companies use its progressive rollout features and consent management options to control how changes reach users. The architecture emphasizes low latency and compatibility with single page applications without disrupting user experience.

Dynamic Yield combines personalization capabilities with A/B testing in its Experience OS platform. The company now operates as part of Mastercard and offers tools for audience segmentation, targeting, and recommendations across digital channels. It provides options for journey orchestration and optimization on web, email, and mobile apps.

Dynamic Yield includes AI features for automation and experience building. Companies connect the platform to their existing tech stack through APIs and integrations. The setup allows testing and personalization while maintaining flexibility for different business needs.

LaunchDarkly specializes in feature flagging combined with experimentation capabilities. The company created a platform that helps development teams control releases and run tests directly in their code environments. It supports safe feature rollouts with targeting and monitoring options.

LaunchDarkly integrates experimentation into the development workflow so teams can validate changes before full exposure. The tools include analytics for measuring impact and options for progressive delivery. Companies use it to reduce risk when shipping new functionality across different platforms.

Statsig offers a modern platform with a generous free tier and advanced statistical methods. The company brings together feature management, experimentation, and product analytics in one place. It supports warehouse-native setups so teams can work with their existing data infrastructure.

Statsig includes session replay and no-code editing features alongside its core tools. Companies run sophisticated tests and analyze results with its stats engine. The platform works across different frameworks through multiple SDKs and emphasizes speed in decision making.

Monetate focuses on server-side experimentation for enterprise environments. The company provides tools that operate at the network layer for testing and optimization without affecting page load performance. It supports both client-side and server-side approaches depending on team needs.

Monetate handles complex testing scenarios including authenticated flows and regulated industries. Companies use its capabilities for A/B testing, multivariate experiments, and feature rollouts with strong security controls. The platform emphasizes control and measurement across different digital touchpoints.

GrowthBook provides an open-source platform for experimentation, feature flags, and product analytics. The company built a warehouse-native solution that connects directly to existing data infrastructure. It supports A/B testing along with feature management in a way that keeps costs low through its free tier and self-hosted options.

GrowthBook includes SDKs for different frameworks and allows teams to run experiments with minimal code changes. Companies define metrics using SQL in their own warehouse and get access to a statistical engine for analysis. The setup works for both small projects and larger scale needs without vendor lock-in.

PostHog offers an open-source suite that includes experimentation features alongside product analytics. The company combines session replay, funnels, and heatmaps with feature flags in one platform. It supports self-serve analysis and works well for product engineering teams.

PostHog includes AI assistance for data questions and experiment creation through natural language. Companies run tests on web, mobile, and other touchpoints while keeping data in-house. The usage-based pricing model comes with generous free tiers for most features.

Crazy Egg delivers heatmaps and session recordings together with simple A/B testing capabilities. The company focuses on making website optimization accessible through visual behavior data. It helps teams understand visitor interactions without complex setup.

Crazy Egg includes surveys and pop-up tools that work alongside its testing features. Companies get real-time traffic reporting and AI-assisted analysis in an affordable package. The platform emphasizes ease of use for marketers and smaller teams.

Unbounce specializes in landing page creation with built-in Smart Traffic for optimization. The company offers a no-code builder that supports A/B testing and personalization directly on pages. It uses AI insights drawn from conversion data across campaigns.

Unbounce allows dynamic text replacement and custom code for better alignment with marketing efforts. Companies launch variants quickly and let the platform direct traffic to better-performing versions automatically. The setup integrates with common marketing tools and CRMs.

Geteppo provides a data-driven experimentation platform with warehouse-native architecture. The company supports A/B testing, feature management, and advanced use cases like AI model evaluation. It focuses on statistical rigor and metric governance for different teams.

Geteppo includes tools for contextual bandits and incrementality measurement across channels. Companies run experiments on core business metrics while keeping data secure in their own warehouse. The platform works for data teams, engineers, and marketers through self-serve features.

Split.io offers feature experimentation as part of its intelligent feature management platform. The company now operates under Harness and provides tools for creating, targeting, and managing feature flags at scale. It supports safe releases with monitoring for system performance and user behavior impacts.

Split.io includes experimentation capabilities that let teams test changes without bottlenecks. Companies run tests across code environments and use gradual rollouts with real-time alerts. The platform integrates with development workflows to support faster innovation while reducing risk in production.

AB Smartly delivers an experimentation platform focused on building a strong experimentation culture in enterprise settings. The company uses advanced group sequential testing methods to reach decisions faster without losing statistical integrity. It supports real-time data access for quick bug detection and metric monitoring.

AB Smartly provides in-platform documentation and activity feeds that help keep different teams aligned. Companies run experiments across websites, native apps, emails, and algorithms through multiple SDKs. The setup emphasizes transparency in program reporting alongside practical tools for product, engineering, and data teams.

Personizely combines personalization with A/B testing in an all-in-one conversion optimization suite. The company offers a no-code approach for launching tests on content, themes, pricing, and full pages. It includes tools for dynamic content delivery based on visitor segments and real-time context.

Personizely provides widgets such as popups and overlays triggered by user behavior. Companies set up precise targeting using actions, customer data, location, and device information. The platform connects with existing marketing tools and CMS systems for smoother workflows.

Zoho serves as an accessible all-in-one platform that includes A/B testing along with various conversion tools. The company brings together web analytics, heatmaps, session recordings, and funnel analysis in a single interface. It supports goal tracking and form analytics without requiring technical expertise.

Zoho offers personalization features based on visitor data and behavior patterns. Companies create pop-ups, push notifications, and polls using pre-designed templates. The platform maintains low impact on page load times and includes privacy compliance options.

Airship specializes in mobile A/B testing. The company focuses on native app experiences with no-code tools for creating and optimizing in-app journeys. It supports testing of variants alongside real-time intelligence for personalization.

Airship enables cross-channel orchestration that includes push, in-app messages, and web elements. Companies use AI-driven agents to build experiences and analyze results quickly. The setup works for mobile-first strategies with emphasis on measurable outcomes across different touchpoints.

Varify.io provides a budget-friendly visual editor for creating and running experiments. The company built the platform with direct integration to GA4 and added AI features to support test creation and analysis. It works particularly well for mid-sized websites and marketing teams that want quick setup without heavy technical resources.

Varify.io focuses on simplicity while delivering the core tools marketers need for optimization. Companies use its interface to make changes visually and launch tests across pages and elements. The combination of affordability, GA4 connectivity, and AI assistance makes it a practical choice for teams looking to start testing regularly.

Omniconvert delivers an all-in-one platform that brings A/B testing together with surveys and segmentation features. The company developed tools with a clear emphasis on e-commerce needs, helping stores understand customer behavior through multiple data points. It combines experiment results with qualitative feedback in the same interface.

Omniconvert supports segmentation based on visitor actions and characteristics for more targeted tests and experiences. Companies run surveys at key moments to gather direct input while experiments run in the background. This setup gives e-commerce teams both quantitative lift data and deeper insights into why changes perform the way they do.