A/B testing tools help you move beyond guesswork by comparing two versions of a page or element to see which performs better using real data.
Landing pages are one of the best assets to test first. With a single, focused goal, they make it easy to measure results, identify friction points, and optimize for action. That’s why they’re often the most effective starting point for conversion rate optimization.
In this guide, we’ll cover 10 top A/B testing tools to help you experiment smarter—from landing pages to email campaigns, and from UX improvements to full website tests.
We begin with Landingi, a user-friendly landing page builder that enables split testing without requiring any coding. Its core strength is making A/B testing both accessible and impactful, particularly when fine-tuning landing pages for conversions.
Let’s explore the top tools.
Category | Tool |
1. Best A/B Tool For Landing Pages | |
2. Best A/B Tool for E-commerce Websites | |
3. Best A/B Tool for Mobile Apps | |
4. Best A/B Tool for Email Campaigns | |
5. Best A/B Tool for User Experience (UX) Optimization | |
6. Best A/B Tool for Small Businesses | |
7. Best A/B Tool for Large Enterprises | |
8. Best A/B Tool with AI Capabilities | |
9. Best A/B Tool for Multi-channel Testing | |
10. Best A/B Tool for Reporting and Analytics |
Which A/B Testing Tools Are Considered Industry Leaders?
Many A/B testing tools stand out in the market for their functionality, ease of use, and performance. Below are ten leading options widely used for conversion rate optimization (CRO):
- Landingi
- Shoplift
- Google Firebase
- Mailchimp
- Optimizely
- VWO (Visual Website Optimizer)
- Adobe Target
- AB Tasty
- Dynamic Yield
- Crazy Egg
Choosing the right tool depends on your specific needs—such as testing scope, integration requirements, budget, and team experience. Evaluating each platform’s core features, support, and scalability can help you determine which solution best supports your CRO goals.
The next section provides an overview of each tool and highlights its key capabilities to help guide your selection.
1. Best A/B Tool for Landing Pages: Landingi
Landingi is widely recognized as one of the best A/B testing tools for landing pages. Its intuitive interface and landing-page-first focus allow marketers to quickly design, test, and optimize pages without coding knowledge.
Key CRO Features in Landingi:
- Multivariate testing
- Drag-and-drop, pixel-precise builder
- Quick duplication and page modifications
- AI Assistant – helps generate copy, edit images, and enhance SEO
- EventTracker – in-app tool for measuring visitor behavior
- Dynamic text replacement
- Built-in campaign scheduler
User-Friendly Page Creation:
- Visual editor with no coding required
- 400+ customizable templates
- Mobile optimization options
- 170+ tool integrations
- Access to live support, tutorials, and a full knowledge base
Landingi Pricing
| Plan | Monthly | Annually (per month) | Key Limits & Features |
|---|---|---|---|
| Free | $0/mo | – | 5 active pages, 100 visits, 1 domain, basic analytics, lead tools, 3 subaccounts |
| Lite | $29/mo | $24/mo | 10 pages, 5,000 visits, unlimited conversions, custom fonts, autoresponder |
| Professional | $69/mo | $64/mo | Unlimited pages, 50,000 visits, 10 domains, Smart Sections, e-commerce features, advanced A/B testing |
| Enterprise | $1,399/mo | $1,150/mo | Unlimited traffic, 100+ domains, EventTracker, domain whitelisting, SSO, dedicated manager |
If your focus is landing page optimization, Landingi stands out as a purpose-built solution that supports testing, analytics, and customization from a single platform.
2. Best A/B Tool for E-commerce Websites: Shoplift
Shoplift is one of the top A/B testing tools for e-commerce, particularly for Shopify users. It integrates directly with Shopify templates, allowing online retailers to test and optimize key elements of product pages and checkout flows—two critical areas that directly impact conversion rates and cart abandonment.
Key Features:
- Native integration with Shopify
- Test recommendations based on performance data
- Lift Assist – automated suggestions for improving page templates
- Advanced segmentation and reporting for granular analysis
Shopify Pricing:
| Plan | Monthly Price | Traffic Limit | Key Features |
|---|---|---|---|
| Starter | $149/mo | Up to 50,000 visitors | Unlimited A/B tests |
| Growth | $299/mo | Up to 100,000 visitors | Unlimited A/B tests |
| Scale | $499/mo | Unlimited traffic | Dedicated rep + unlimited A/B tests |
Shoplift is built for e-commerce brands that want to optimize conversions without custom development. Its deep integration with Shopify and easy-to-use testing tools make it ideal for product page optimization, reducing cart abandonment, and boosting return on ad spend (ROAS).
3. Best A/B Tool for Mobile Apps: Google Firebase
Google Firebase is a top choice for A/B testing in mobile apps. It offers a robust set of tools—including analytics, crash reporting, user segmentation, and messaging—seamlessly integrated into one platform. Firebase A/B Testing helps app developers test changes and measure their impact on user behavior, retention, and engagement.
Key A/B Testing Features:
- User segmentation for controlled experiments
- Tailored content delivery to test groups
- Integration with Remote Config for dynamic updates
- Performance tracking to measure the impact of changes
- Support for dynamic content and layout placements
Google Firebase Pricing:
| Plan | Cost | Included Features |
|---|---|---|
| Spark | Free | A/B Testing, Analytics, Cloud Messaging, Remote Config, limited quotas |
| Blaze | Pay-as-you-go | Scales with usage, retains Spark plan features, no upfront fees |
Firebase’s pricing is flexible, allowing new developers to start free and scale as needed. The pay-as-you-go model ensures that you only pay for what you use, making it ideal for startups and enterprise teams alike.
Firebase is more than just an A/B testing tool—it’s a full mobile app optimization suite. Its integration with core app services allows you to run experiments, analyze results, and deploy improvements without app store updates. It’s an ideal solution for growth-focused app teams that prioritize user experience and performance.
4. Best A/B Tool for Email Campaigns: Mailchimp
Mailchimp is a leading A/B testing tool for email marketing. Its intuitive interface makes it easy to test variables like subject lines, content, sender names, and send times—key elements that influence open and click-through rates.
Key A/B Testing Features:
- Subject line testing
- Email content variations
- Sender name comparisons
- Send-time testing
- Multivariate testing for newsletters
These features help marketers improve engagement and increase conversions from their email campaigns.
Mailchimp Pricing:
| Plan | Monthly Price | Email Sends/Month | Key Features |
|---|---|---|---|
| Free | $0 | 1,000 | Basic email tools, limited contacts, ideal for beginners |
| Essentials | From $13 | 5,000 | A/B testing, custom branding, basic automations |
| Standard | From $20 | Varies by contacts | Multivariate testing, advanced segmentation, comparative reports |
| Premium | From $350 | Unlimited | Advanced analytics, unlimited users, full audience management features |
Mailchimp is a strong choice for marketers focused on optimizing email performance. Its built-in testing tools and flexible pricing make it accessible for both small businesses and enterprise teams looking to improve conversions through data-driven email strategy.
5. Best A/B Tool for User Experience (UX) Optimization: Optimizely
Optimizely is one of the top A/B testing platforms for optimizing user experience (UX). It supports advanced testing methods—like multivariate and multi-page experiments—along with personalization features that help teams deliver targeted experiences based on user behavior.
Key UX-Focused Testing Features:
- No-flicker snippet for seamless experiment delivery
- Collaborative experimentation tools for team alignment
- Multi-page and multivariate testing
- Visual editor and design tools
- Fast test execution
- Granular audience targeting
- Built-in statistical analysis for test validity
These capabilities allow designers, product teams, and marketers to fine-tune every part of the user journey to maximize conversions.
Optimizely Pricing:
Optimizely does not offer fixed pricing for its Experiment platform. Instead, pricing is customized based on your business size, goals, and use case. This tailored approach ensures that each client receives the right mix of features and support for their testing needs—whether for small-scale UX experiments or enterprise-level optimization programs.
Optimizely is ideal for businesses that want to go beyond basic A/B testing and take a strategic, data-driven approach to UX improvement. Its powerful experimentation engine and customizable pricing make it a strong fit for teams looking to deliver personalized, conversion-optimized experiences at scale.
6. Best A/B Tool for Small Businesses: VWO
VWO (Visual Website Optimizer) is a powerful yet accessible A/B testing platform ideal for small businesses. Its no-code visual editor makes it easy to create and launch experiments without technical support, while built-in insights help guide users toward conversion improvements.
Key Features for Small Businesses:
- A/B testing
- Multivariate testing (MVT)
- Split URL, mobile app, and server-side testing
- Heatmaps and visitor recordings
- Conversion tracking
- Audience segmentation
- Campaign scheduling
VWO’s user-friendly interface and guided experimentation features make it especially valuable for teams with limited resources or CRO experience.
VWO Pricing:
| Plan | Price Range | Key Features |
|---|---|---|
| Starter | Free | Basic testing tools for small websites |
| Growth / Pro | From $339/month | Advanced testing (MVT, server-side), segmentation, and analytics |
| Enterprise | Up to $9,806/month | Full-stack experimentation, enterprise-level integrations, and custom support |
VWO offers an excellent entry point for small businesses looking to improve conversions without technical complexity. With scalable plans and an intuitive interface, it supports both basic testing and advanced experimentation as your business grows.
7. Best A/B Tool for Large Enterprises: Adobe Target
Adobe Target is a top-tier A/B testing and personalization platform designed for large enterprises. Built to support high-traffic environments and complex user journeys, it integrates seamlessly with Adobe Experience Cloud to deliver real-time, AI-driven optimizations at scale.
Key Enterprise Features:
- AI-powered automation and personalization
- Real-time optimization across web, mobile, and other channels
- Multivariate and multi-armed bandit testing
- Cross-channel testing and targeting
- Personalization engine with advanced segmentation
- Enterprise-level governance and workflow control
Adobe Target Pricing:
Adobe Target uses a custom pricing model, tailored to each organization’s needs. Pricing is influenced by:
- Number of digital properties
- Volume of traffic
- Product modules selected
- Scope of omnichannel testing and delivery
Adobe Target is ideal for large enterprises needing advanced experimentation and personalization tools. Its AI capabilities, scalability, and integration with Adobe’s marketing ecosystem make it one of the most powerful solutions for conversion rate optimization at the enterprise level.
8. Best A/B Tool with AI Capabilities: AB Tasty
AB Tasty stands out as a leading A/B testing platform with advanced AI capabilities. Its predictive algorithms and automation tools enable marketers to deliver personalized user experiences at scale—boosting engagement and conversion rates with minimal manual input.
Key AI-Powered Features:
- Predictive testing and performance forecasting
- Dynamic traffic allocation based on real-time results
- AI-based targeting for audience segmentation
- Stat Engine using Bayesian statistics for faster, more reliable outcomes
- WYSIWYG editor for no-code experiment creation
- Advanced campaign triggers and segment builder
- Dynamic widgets like social proof, urgency messaging, and image auto-optimization
These features allow teams to launch targeted campaigns, test user experiences, and personalize journeys—all from one platform.
AB Tasty Pricing:
AB Tasty offers custom pricing based on your business size, traffic volume, and testing needs. There are no public tiers; instead, companies receive a tailored quote that includes the right combination of features for their experimentation and optimization goals.
AB Tasty is an excellent choice for organizations looking to combine A/B testing with AI-driven personalization. Its flexible pricing model and powerful automation tools make it a scalable solution for businesses aiming to optimize user experiences with precision and efficiency.
9. Best A/B Tool for Multi-channel Testing: Dynamic Yield
Dynamic Yield is a top choice for multi-channel A/B testing, allowing businesses to test and personalize experiences across web, mobile apps, email, kiosks, and other digital channels. This helps ensure consistent messaging and optimized performance at every customer touchpoint.
Key Features for Multi-Channel Optimization:
- A/B/n testing across multiple channels
- Journey optimization across the full user lifecycle
- AI-driven revenue optimization and predictive targeting
- Unified client- and server-side testing
- Agile statistical engine for fast and reliable test results
- Automatic traffic allocation
- WYSIWYG editor for visual editing
- Advanced analytics and reporting
These tools enable brands to deliver personalized, data-backed experiences regardless of where or how users interact with them.
Dynamic Yield Pricing:
Dynamic Yield uses a custom quote-based pricing model. Pricing is determined based on factors such as:
- Number of users
- Monthly traffic volume
- Channels used
- Required support level
- Access to advanced features
Interested businesses should contact Dynamic Yield directly to receive a tailored quote.
Dynamic Yield is ideal for companies focused on optimizing user experiences across multiple digital channels. With a strong blend of AI, personalization, and cross-platform testing tools, it empowers teams to deliver cohesive, conversion-focused experiences everywhere their users engage.
10. Best A/B Tool for Reporting and Analytics: Crazy Egg
Crazy Egg is a powerful A/B testing platform with a strong emphasis on visual analytics. Its heatmaps, scrollmaps, and confetti reports provide detailed insight into user behavior, helping businesses identify where to focus their optimization efforts for maximum impact on conversions.
Key Features for Analytics and Testing:
- Unlimited A/B testing
- Heatmaps and scrollmaps to visualize user attention and movement
- Confetti and overlay reports to analyze traffic sources and click behavior
- Snapshot analysis and visitor recordings
- Goal tracking
- Surveys and call-to-action (CTA) analysis
These tools allow businesses to understand not just what users do, but why they do it—supporting more informed, data-driven CRO decisions.
Crazy Egg Pricing:
| Plan | Price (Monthly) | Pageviews | Snapshots | Key Features |
|---|---|---|---|---|
| Basic | $29 | 30,000 | 25 | Unlimited A/B tests, heatmaps, recordings |
| Standard | $49 | Increased | More snapshots | Includes all Basic features |
| Plus | $99 | Higher limits | Advanced tools and support | |
| Pro | $249 | Expanded | Designed for high-traffic sites | |
| Enterprise | Custom | Custom | Custom | Tailored plans and advanced support |
Crazy Egg is ideal for businesses focused on understanding user behavior through visual data. Its robust analytics, paired with unlimited A/B testing and flexible pricing, make it a strong choice for companies seeking to improve conversions through deeper user insight.
Why Landing Pages Are the Core of Any A/B Testing Strategy?
Landing pages are the core of A/B testing strategies because they provide the most effective starting point for measuring and optimizing user behavior.
Unlike general site pages that serve multiple purposes, landing pages are designed with a single goal: driving user action. This focused structure makes it easier to measure the impact of changes. Every element—headline, form, image, or call to action—exists to support one objective, so test results are directly linked to user behavior.
These pages also generate fast, reliable feedback. Because most paid campaigns send targeted traffic to landing pages, tests reach relevant users, leading to quicker insights and more actionable data.
Whether you’re refining copy, rearranging layout, or adjusting form fields, even small changes on a landing page can lead to significant improvements in conversion rates. It’s not just about aesthetics—it’s about maximizing the value of every visitor.
Boost your brand with a professionally designed landing page tailored to your needs.
FAQ – Best A/B testing tools
If you’re exploring ways to improve website performance, email campaigns, or app experiences, A/B testing tools are essential for making data-driven decisions that increase conversions. Below are some of the most common questions about A/B testing and how these tools help.
What is A/B Testing?
A/B testing is a marketing experiment that involves splitting your audience to test different versions of a webpage, email, or app element to determine which performs better. It’s a method for validating whether a design change, copy adjustment, or layout update leads to improved outcomes.
This approach helps businesses make decisions based on data—not assumptions—ultimately increasing conversion rates, which represent the percentage of users who complete a desired action (such as making a purchase or signing up). Improving these rates is critical for long-term growth and profitability.
Beyond just numerical results, A/B testing can also reveal behavioral insights by highlighting how and why users respond to certain changes. This makes it a valuable tool for both quantitative and qualitative analysis.
As defined in Optimizely’s Optimization Glossary, “Testing takes the guesswork out of website optimization and enables data-informed decisions that shift business conversations from we think to we know.”
However, effective testing requires the right platform. That’s where A/B testing tools come in—they provide the functionality, structure, and analytics necessary to run successful experiments and scale your optimization efforts.
How is A/B Testing Done?
A/B testing follows a structured process designed to measure the impact of specific changes on user behavior. It involves creating two or more versions of a webpage or app element—typically labeled A (control) and B (variation)—and randomly distributing traffic between them. Performance is measured using predefined metrics such as conversion rate or click-through rate.
The version that performs better provides evidence of which change is more effective for your target audience.
A 7-Step Framework for Running an A/B Test:
- Collect Data
Identify high-traffic areas and pages with high bounce or drop-off rates. - Define Goals
Establish clear metrics to evaluate success—such as sign-ups, purchases, or engagement. - Generate Hypotheses
Propose changes you believe will improve performance and prioritize them by expected impact and implementation effort. - Create Variations
Use A/B testing tools to develop the modified version(s) of your page or feature. - Run the Experiment
Randomly assign users to either the control or variation to ensure unbiased results. - Wait for Statistical Significance
Allow the test to run until enough data is collected to make a valid comparison. - Analyze Results
Determine which version performs better and whether the difference is statistically meaningful.
Before starting, it’s important to plan your testing strategy. As Anthony Brebion notes in his article “Before You Start A/B Testing, Define Your Roadmap,” creating a clear roadmap is essential for aligning your team, defining priorities, and tracking progress throughout the project.
High-quality A/B testing tools make this process more manageable by handling version delivery, tracking user behavior, and analyzing performance results—enabling data-driven decision-making at every stage.
What are A/B Testing Tools?
A/B testing tools are software platforms that support controlled experiments to compare different versions of digital content. They simplify tasks such as creating variations, splitting traffic, collecting user behavior data, and analyzing performance. These tools play a key role in conversion rate optimization by identifying which changes lead to increased engagement and better conversion outcomes.
Many A/B testing tools allow experiments without altering the underlying website or app code. Features like real-time testing, pattern matching, and failover protection enhance reliability. Some tools are tailored for specific use cases, such as e-commerce or mobile app testing, and choosing the right one depends on your business goals and technical setup.
While some platforms require coding knowledge, many now offer visual editors or no-code interfaces, making experimentation accessible to marketers and product teams without technical backgrounds.
Although pricing varies, the cheapest tools may not deliver reliable results. As VWO notes in its guide, it’s important to use tools that either integrate with strong research platforms or offer robust analytics to ensure that results are statistically meaningful and actionable.
What are the Primary Features to Look For in an A/B Testing Tool?
There are eight primary features to look for in an A/B testing tool: usability, statistical analysis capabilities, targeting options, reporting, integration with other tools, visual editing capabilities, multivariate testing, and support resources.
Usability is one of the most important factors when selecting an A/B testing tool. A tool with an intuitive interface enables users to set up and run tests quickly, even if they have limited technical skills. This accessibility helps teams across different departments optimize websites, apps, or marketing campaigns without requiring developer intervention.
Statistical analysis capabilities form the foundation of reliable decision-making. The tool should use established statistical methods—such as frequentist or Bayesian approaches—to deliver accurate and trustworthy test results.
Targeting options enable more precise and relevant testing. For example, the ability to segment users based on device type, location, or behavior allows for more meaningful experiments and actionable insights.
Clear and detailed reporting is essential. A/B testing tools should provide easy-to-read reports that highlight key performance metrics, statistical significance, and conversion rates to help users understand and act on test results.
Integration with existing marketing, analytics, and data platforms helps maintain a streamlined workflow. A testing tool that connects smoothly with platforms like Google Analytics, CRMs, or customer data platforms reduces duplication of effort and improves data consistency.
Visual editing tools allow non-technical users to modify webpages or app interfaces directly through drag-and-drop editors or WYSIWYG (What You See Is What You Get) interfaces. This speeds up experimentation by reducing the need for developer support.
Multivariate testing supports experiments involving multiple elements on a page, such as headline, image, and call-to-action variations. This method reveals how combinations of variables influence user behavior, offering deeper optimization insights.
Strong support and learning resources contribute to successful implementation. Comprehensive documentation, video tutorials, case studies, and responsive customer service can help teams overcome challenges and make the most of their testing tools.
Choosing a platform with the right mix of these features can significantly improve your ability to run effective experiments and optimize marketing performance.
What are the different types of tests that can be conducted using these tools?
In addition to standard A/B tests, these tools support several other testing methods:
- Multi-Page (Funnel) Testing: Analyzes the user journey across several pages to identify where users drop off and which changes improve conversions throughout the funnel.
- Split URL Testing: Compares two or more versions of a webpage hosted on different URLs to evaluate performance differences.
- Multivariate Testing: Assesses how combinations of multiple page elements—such as headlines, images, and buttons—impact user behavior.
Which A/B testing tool is deemed the most user-friendly for beginners?
VWO and Landingi are among the most user-friendly A/B testing tools for beginners. Both offer intuitive interfaces that simplify test creation and analysis. They also provide onboarding support, help centers, e-books, webinars, case studies, and access to technical experts, making it easier for new users to learn and succeed with experimentation.
Is prior knowledge of coding necessary to use A/B testing tools?
No, prior coding knowledge is not required to use most A/B testing tools. While some platforms may offer advanced features that benefit from technical skills, many tools include visual editors and no-code interfaces designed for non-technical users. For instance, tools like Adobe Target, Landingi, and Mailchimp allow users to run experiments without writing code.
Are there certain campaign objectives that can’t be effectively measured using A/B testing?
Yes. A/B testing is not effective for measuring long-term or indirect objectives, such as brand awareness, customer loyalty, or lifetime value. These outcomes require broader research methods like longitudinal studies, customer surveys, or cohort analysis to capture their impact over time.
In what ways do A/B testing tools provide insights that inform campaign strategy adjustments?
A/B testing tools provide data on how users respond to different campaign elements, such as headlines, images, or calls to action. This feedback shows which variations perform best, helping marketers adjust strategies to improve engagement, conversion rates, and overall campaign effectiveness.
How do A/B testing tools handle user privacy, especially in light of regulations like GDPR?
A/B testing tools handle user privacy by supporting compliance features such as consent management, data anonymization, and secure data storage. These tools ensure personal information is processed according to legal standards like GDPR.
How do you write an A/B testing report?
An A/B testing report should clearly present the test objective, hypothesis, methodology, results, and conclusions. It should highlight statistically significant findings and offer actionable recommendations to guide future decisions.
How do A/B testing tools ensure the accuracy and reliability of test results?
A/B testing tools apply statistical models to determine result significance and reliability. They include controls to manage sample size, filter out anomalies, and ensure that test outcomes reflect genuine user behavior.
Get More Conversions with High-Performing Landing Pages and Smart A/B Testing
With so many conversion optimization tools available, trying a platform before committing can help determine if it fits your needs. Landingi offers a 14-day free trial and a free plan, giving users access to key features like A/B testing, campaign scheduling, third-party integrations, and a mobile page editor. This allows you to evaluate its functionality before choosing a paid option. Go ahead and give Landingi a try!
