Artificial Intelligence

Here are the 20 top CRO-worthy AB testing software you must consider to help you increase your conversion rates in 2024.

There are a ton of AB testing tools on the market right now, and that number is only going to increase. When evaluating these tools for use in your own business, it can be difficult to wade through the marketing rhetoric and identify exactly which tools are a good fit. That’s why we reached out to our network of CRO specialists in order to bring you a comprehensive look at the best AB testing tools on the market.

Our goal here isn’t necessarily to give you a complete review of each tool, but rather, to show you which split testing tools are preferred by full-time CRO experts — people whose businesses depend completely on the results they are able to deliver to their clients.

We’ll cover two primary categories of tools:

1. Tools for running the actual AB tests: Most Recommended AB Testing Tools
2. Tools for collecting data in order to make good hypotheses: 12 Tools For Gathering Data

Key Features To Look For in A/B Testing Tools

Before you go all-in on the fanciest AB testing tool on the market (bonus points if the vendor’s sales deck has more animations than your last holiday party), you’ll want to take a close look at the specific features that will actually move the needle for your team. Here’s what our CRO experts repeatedly told us matters most—whether you’re optimizing landing pages, mobile apps, or the entire customer journey.

1. Visual Editor

A user-friendly visual editor can be a lifesaver, especially if you want to test page variations without calling in your developer cavalry every time you tweak a headline. Look for platforms that offer intuitive drag-and-drop or WYSIWYG interfaces, making it easy for non-technical folks to create, preview, and launch tests.

2. Feature Flags & Server-Side Testing

If your experiments need to go deeper than basic page changes—or you want to avoid “flash of original content” issues—feature flags and server-side support become essential. These allow you to roll out backend changes, experiment with features, and personalize user experiences seamlessly, even on mobile apps.

3. Mobile Testing Capabilities

With so much web traffic coming from smartphones and tablets, robust mobile testing is a must. The best tools let you launch experiments across devices—desktop, tablet, mobile web, and native apps—without losing sleep over compatibility headaches.

4. Analytics & Reporting

Don’t get caught flying blind. Look for tools with real-time analytics, clear test performance dashboards, and granular reporting. Being able to dig into audience segments, conversion events, and behavioral patterns will help you turn “we think this won” into “we know why this won.”

5. Feedback Mechanisms

Data is great—feedback is gold. Many CRO specialists recommend platforms that support in-context surveys, polls, or feedback widgets. This allows you to capture not just what users are doing, but why they’re doing it (or abandoning your cart at the last step).

6. Ease of Use (and Integration)

Finally, take stock of how steep the learning curve really is. Can your marketers and product managers pick it up quickly? Does it play nicely with analytics suites like Google Analytics, Mixpanel, or e-commerce platforms you already use? Integration headaches are a surefire way to kill CRO momentum.

By prioritizing these features, you’ll be able to narrow your shortlist, avoid shiny object syndrome, and select a tool that empowers your team—without getting bogged down in unnecessary bells and whistles.

How Different Tools Advance Hypothesis Generation and Validation

When it comes to A/B testing, having the right toolkit at your disposal can make all the difference between guesswork and confident decision-making. Tools designed for behavioral analytics—think heatmaps, session recordings, scroll tracking, and in-page feedback widgets—bridge the vital gap between “what happened” on your site and “why.”

Instead of just using these platforms to confirm your test results, many leading CROs rely on them earlier in the process to formulate better test hypotheses. Here’s why these tools matter:

• Hypothesis Generation: Tools like Hotjar, Crazy Egg, and FullStory capture granular data on where users are clicking, how far they scroll, and where they abandon your funnel. Watching real user journeys can highlight unexpected friction points, reveal which elements go unnoticed, or spark ideas for creative test variations.
• Hypothesis Validation: Once you’ve designed a test, these same tools offer a deeper layer of evidence to show why a winning (or losing) experience works the way it does. Rather than relying on conversion numbers alone, behavioral insights help explain the story behind the stats—so you’re not left guessing.

For those newer to experimentation, leveraging these insights early on helps eliminate blind spots by highlighting patterns you might otherwise miss. More seasoned teams, on the other hand, find that combining rigorous data collection with behavioral analysis sharpens their focus, ensuring every test counts.

At the end of the day, the “right” tool is going to vary depending on the business. As Paul Rouke, former Founder and Director of Customer-Centricity at CX agency PRWD, explains:

We see it time and time again: companies sign up to multi-year contracts for feature rich, enterprise level tools which have a fantastic looking client list, and it ends up burning through their entire CRO budget. Companies invest without considering the need for resource and skills, or they are simply sold on the tool’s ‘ease of use’.

Many companies don’t have the internal skills in place yet to actually utilize this tool, and so the all-singing, all-dancing tool hardly gets used. Also, people using the tool don’t understand the need for or cost of customer research, data, psychology, design, UX principles, etc., meaning they’re ultimately testing the wrong things.

The tools that in my experience deliver the most long-term value are those which are reasonably priced, allowing companies to spend more of their budget on making sure they are testing intelligently and developing an effective testing process.

Best Practices for Writing Clear AB Test Hypotheses

When it comes to AB testing, clarity in your hypotheses is essential. Vague or overly complex tests—where you’re attempting to swap multiple elements at once—tend to muddy your results and make it nearly impossible to pinpoint what actually influenced a user’s behavior. The solution? Focused, testable statements that guide your experimentation.

Here’s how to craft solid AB test hypotheses:

• Isolate One Variable at a Time: Resist the urge to bundle several changes into one test. For example, don’t change headlines, button colors, and layout in a single experiment. Test one element at a time to attribute results with confidence.
• Write it Out, Explicitly: Before touching any code, put your hypothesis in writing as a clear, single sentence. For instance: “We believe that changing the CTA button from gray to green will reduce friction and increase signups.”
• Ground Your Reasoning in Data: Use observational data or research to justify your hypothesis, whether it’s from analytics, heatmaps, or user feedback. This ensures your test isn’t just a shot in the dark.
• Define Success Upfront: Attach a measurable metric to your hypothesis (e.g., clicks, conversions, form submissions) so you know what winning looks like.
• Keep it Actionable: A strong hypothesis should suggest a specific action—if the test proves successful, the change should be easy to implement permanently.

By developing clear and concise hypotheses, you’ll be able to iterate intelligently, learn faster, and ultimately drive more meaningful improvements for your business.

No tool on this list will be the right fit for every business. That said, without breaking up our list into tiers, we would like to note 4 tools that came up very consistently from the experts we queried.

The two most popular AB testing tools by a wide margin were Optimizely and VWO. These are the most common AB testing tools used by Conversion Sciences clients, and virtually every single expert we chatted with is using both of these tools on a regular basis.

Another two tools that came up on our original poll (in about a third of responses), were Convert Experiences and UsabilityHub. Both of these tools received consistently strong reviews from the experts who used them and fill key needs in the CRO space, which we’ll discuss in their respective entries.

Quick Wins vs. In-Depth AB Testing: Choosing the Right Tool

When it comes to selecting an AB testing tool, your choice often depends on whether you need fast, actionable results or a platform robust enough for comprehensive, data-driven experimentation.

Tools for Quick Wins

If your goal is to implement rapid changes and validate ideas without a steep learning curve, look for tools designed with simplicity and speed in mind. These platforms typically offer:

• Intuitive interfaces that allow marketers, designers, and product teams to launch tests quickly—no coding required.
• Templates and visual editors for fast setup of variants.
• Real-time reporting that highlights the best-performing versions so you can act immediately.

These tools shine when you want to test headlines, call-to-action buttons, or landing page layouts to earn rapid conversion lifts.

Tools for In-Depth Experimentation

For more complex testing—like multi-page funnels, dynamic content, and intricate audience segmentation—you’ll want a testing suite built for robust experimentation. These tools generally provide:

• Advanced targeting options for detailed audience segmentation.
• Support for multivariate tests and sophisticated experiment designs.
• Deep integrations with analytics platforms for comprehensive analysis.
• Developer-friendly features for teams with the resources to maximize flexibility and customizations.

These platforms are ideal for organizations with the capability to invest time and resources into iterative testing, customized user journeys, and data-rich optimization processes.

How to Decide?

Ultimately, the best AB testing tool for you will depend on your goals, resources, and team structure:

• Looking for quick wins? Pick a straightforward tool that lets you launch and analyze experiments in minutes.
• Need to dig deeper? Choose a platform with advanced capabilities that supports nuanced hypotheses and granular reporting.

This approach ensures you won’t get lost in unnecessary features—or outgrow your tool as your experimentation program matures.

Collaboration Tips for Product, Growth, and UX Teams

When it comes to running effective AB tests, getting your product, growth, and UX teams on the same page is crucial. The best results happen when each team brings its expertise to the table without stepping on each other’s toes—or duplicating efforts.

Here’s how high-performing teams typically collaborate on AB testing:

• Unified Analytics: Ensure everyone is plugged into the same analytics platform (like Google Analytics or Amplitude) so insights are accessible across teams. This creates a single source of truth and cuts down on conflicting interpretations.
• Clear Experimentation Workflow: Establish a workflow where ideas for AB tests are openly shared and prioritized together—think regular experiment review meetings or a shared backlog in tools like Jira or Trello.
• Defined Roles: Assign clear responsibilities. For example, product teams might own test design, growth handles hypothesis generation and scaling, and UX ensures the experience stays user-centric.
• Transparent Documentation: Keep test plans, results, and learnings documented and accessible—Google Sheets is a favorite around here—so no one’s left in the dark as tests progress.
• Integrated Tools: Choose AB testing software (like Optimizely or VWO) that allows multiple team members to collaborate, comment, and review tests before launch.

The key is to make experimentation a team sport. When everyone’s aligned and data is easily shared, AB testing becomes a powerful tool for growth, rather than a battleground for resources and credit.

Several experts also pointed to the value of open-source experimentation and feature flagging platforms—especially for startups or engineering-heavy businesses who prioritize data privacy and internal control.

Here are a few reasons these tools are making waves among CRO professionals:

• Full Ownership and Privacy: You host everything yourself, from experiments to data storage, so sensitive business information and test metrics never leave your hands. This is a huge plus for any organization with strict compliance needs or a zero-tolerance policy on vendor lock-in.
• Customization and Flexibility: Open-source systems aren’t set in stone. Whether your team needs to integrate with an existing data warehouse like BigQuery or Snowflake, or run experiments directly from familiar BI tools, you’re not stuck with out-of-the-box limitations. Many of these tools also support a range of SDKs (from Node.js and React to Python and PHP), making adoption seamless for most development stacks.
• Dev and Marketer Collaboration: Unlike tools that feel like they’re built for either developers or marketers—but rarely both—open-source options often provide both powerful, code-level feature toggling and accessible, UI-based dashboards. This makes it practical to run server-side and client-side tests, track results visually, and keep experimentation closely tied to business goals.
• Cost Effective and Transparent: With no licensing fees and a transparent codebase, startups can iterate rapidly without worrying about hidden costs or black-box algorithms. And, as your team grows more sophisticated, you maintain the ability to tweak, extend, or completely redesign your testing infrastructure according to your own roadmap.

If your company values privacy, wants end-to-end control over experimentation, and isn’t afraid to get a little technical, open-source solutions present a compelling alternative to traditional commercial platforms.

Why Developer-Led Teams Gravitate Toward Open-Source, Self-Hosted Experimentation Platforms

For developer-led teams, the allure of open-source, self-hosted experimentation platforms is strong—and for good reason. These teams often need significant flexibility, the kind that allows them to tailor their experimentation processes and analytics tools exactly to the needs of their product and workflow.

Here’s what stands out about these platforms:

• Complete Customization: With a self-hosted, open-source solution, your development team controls every lever. This means they can shape everything—from how tests are managed to how results are reported—without restriction. If your team wants to integrate feature flags with custom analytics or build unique dashboards, nothing’s off-limits.
• Data Privacy and Compliance: For organizations in regulated industries—finance, healthcare, SaaS, you name it—keeping user data in-house is critical. Self-hosted solutions ensure that sensitive information never leaves your infrastructure, helping you meet strict compliance requirements with confidence.
• Unified Tooling for Fast Iteration: Product and growth teams working hand-in-hand with development often want a single tool for experiments, analytics, and feature rollouts. This keeps everything in one place, reducing context switching and speeding up deployment cycles.
• Ownership and Transparency: Open-source platforms provide transparency into how data is handled and tests are run. Your developers can audit, modify, and extend the platform as needed, building trust and supporting complex experimentation strategies that fit your exact needs.

In short, developer-led teams are drawn to these platforms because they can move quickly, control their stack, and meet security standards—all without paying for hefty, locked-down enterprise tools.

What Enterprises Should Prioritize in Omnichannel Personalization and Experimentation Tools

When it comes to enterprise-grade experimentation, the landscape is packed with tools promising the moon—but what are the make-or-break features savvy companies should actually require? Here’s what consistently rises to the top among CRO professionals in our discussions:

• Comprehensive Testing Options
  Look for platforms that can handle not just standard A/B tests, but also multivariate testing, split URL tests, and more advanced experimentation. Flexibility here ensures your team can evolve beyond basic experiments as your CRO maturity grows.
• Advanced Personalization Capabilities
  Today’s best solutions leverage machine learning or AI to deliver personalized experiences in real time. This may mean adapting content and offers based on user behavior, demographics, or even predictive signals, allowing you to serve up what’s most likely to convert—right when it matters.
• Real-Time Audience Segmentation and Targeting
  Top enterprise tools allow you to define audience segments on the fly and target experiments or experiences to those groups instantly, across devices and platforms. This is critical for orchestrating consistent, personalized journeys regardless of where users land.
• Robust Recommendation Engines
  For e-commerce or content-heavy businesses, being able to target users with relevant product or content recommendations (based on behavior and context) is a proven driver of engagement and revenue.
• Strong Integrations with Analytics and Data Ecosystem
  The best tools don’t operate in a vacuum. Tight integrations with analytics suites (think Google Analytics, Adobe Analytics), tag managers, data warehouses, and customer data platforms are non-negotiable. This breaks down silos and powers deeper insights after tests conclude.
• Support for Mobile and Emerging Channels
  Omnichannel means everywhere—so enterprise tools need to support web, mobile apps, even OTT apps or in-store digital experiences, all within a unified platform.
• Enterprise-Grade Governance and Collaboration
  Mature organizations need tools that support granular user permissions, workflow management, and audit trails. These features ensure that experimentation can scale safely across multiple teams and geographies.

Ultimately, choosing the right experimentation platform is about more than a laundry list of features—it’s about enabling your teams to test confidently, personalize meaningfully, and, above all, translate those capabilities into measurable growth.

Omniconvert: Bridging Quantitative and Qualitative Optimization

One tool that stood out among CRO experts for its versatility is Omniconvert. What makes Omniconvert particularly compelling is the way it integrates both quantitative testing—think A/B and multivariate tests—and qualitative data gathering, like surveys and popups, all within a single platform.

For teams aiming to optimize the whole customer journey, this means you’re not just running experiments on button colors or headlines and hoping for a conversion lift. Instead, you’re also capturing direct input from users to understand why a variant is performing better or how customers perceive proposed changes.

Key strengths include:

• Multiple Experiment Types: From classic A/B or multivariate tests to split URL experiments, you get a solid range of testing capabilities to measure user behavior and impact on metrics like conversion rate or average order value.
• Integrated Surveys and Feedback: Directly layer in surveys and lead forms to capture on-the-spot qualitative feedback, so you can validate your hypotheses with real user opinions instead of just guesswork.
• Deep Segmentation: The platform allows you to target specific audiences based on behavior, referral source, location, or metrics like customer lifetime value—which means you can test and personalize at a granular level.
• Unified Workflow: Rather than toggling between separate tools for testing, surveys, and on-site personalization, Omniconvert ties them together. This saves time and ensures your quantitative data is always in context with qualitative feedback.
• Ease of Use: Thanks to a visual editor and integrations with popular tools such as Google Analytics, Shopify, and HubSpot, most teams can launch and analyze experiments without a steep learning curve.

So, if you want to uncover not just what is working but why, and roll those insights directly back into your CRO strategy, Omniconvert gives you the all-in-one toolkit to do it—no patchwork of apps required.

Without further ado, let’s talk a look at our list of recommended AB testing tools.

What We Use at Conversion Sciences

Our use of AB testing tools allows us to do post-test analysis of different segments.

But running the test is only half the story. The real value comes in what happens after the test ends. It’s easy to call a winner and move on, but without a structured debrief, you risk losing the hard-won insights that could guide your next round of experiments. That’s why we put a strong emphasis on capturing and reviewing results in a way that compounds learning over time.

Our post-test analysis stack:

• An AB Testing Tool (see below)
• Google Sheets (https://www.google.com/sheets/about/)
• Google Analytics Spreadsheet Add-on (https://developers.google.com/analytics/solutions/google-analytics-spreadsheet-add-on)

So important is this stack to us that we’ve created a Google Sheets add-on for Google Analytics 4 (GA4) (https://support.google.com/analytics/answer/10089681?hl=en).

After each test, we make it a point to log the details—what we tested, the hypotheses, segmented results, and any notable customer feedback—into a shared document. This can be as simple as a Google Doc or Notion page, but the key is consistency. By recording not just the numbers but also qualitative insights, we ensure that learnings aren’t lost in the shuffle. This post-test habit helps us spot patterns, avoid retesting the same ideas, and build a playbook of what resonates with different segments.

With this discipline in place, we’re able to extract lasting value from every experiment, making our future testing smarter and more strategic.

Key Challenges with Mobile-Focused A/B Testing Tools

When it comes to mobile-centric A/B testing solutions, there are a few hurdles that come up again and again in conversations with seasoned practitioners and clients alike. While these platforms promise flexibility and insight, there are a few realities worth keeping in mind:

• Integration Headaches: Many mobile A/B tools tout integration with popular data platforms (like mParticle or Segment), but the setup is often trickier than advertised. Don’t be surprised if you run into limits syncing data or mapping complex user actions, especially when you’re stitching together multiple sources.
• User Interface Growing Pains: Mobile-first tools often lag behind their web counterparts when it comes to polish and stability. Glitches, inconsistent reporting, and dashboards that feel a step behind are still common, which can add friction to an already busy workflow.
• Resource-Heavy Administration: One of the most common pain points is the need for ongoing campaign management. While a truly “set it and forget it” solution is the dream, most tools still require you to be fairly hands-on with setup, monitoring, and optimization—time not every team has.
• Cost vs. Value: Finally, mobile-focused A/B solutions sometimes come with startup costs that can outweigh their day-to-day utility, especially for organizations that aren’t running experiments at scale or that lack the in-house expertise to squeeze value out of advanced features.

In short, while mobile A/B testing is crucial as mobile traffic continues to rise, it’s important to go in eyes-open about the tradeoffs: be prepared for a bit of technical wrangling, ongoing supervision, and a realistic match between tool investment and CRO maturity level.eets add-on for Google Analytics 4 (GA4).

Most Recommended AB Testing Tools

Now, let’s look at our experts’ recommended options for running AB tests. We’ve listed these in order of frequency with which they were mentioned by our experts. This is not to be confused with a quality ranking.

Personalization & Optimization Platforms Featuring AI-Driven A/B Testing

What sets modern personalization and optimization platforms apart is their ability to combine classic A/B testing with intelligent automation and advanced targeting. Instead of simply showing every visitor two versions of a headline or landing page, these tools leverage AI and machine learning to pinpoint exactly which content should be displayed to whom—based on detailed user behavior, demographics, or context.

This level of sophistication means the experience is no longer one-size-fits-all. For example, an AI-powered platform might determine in real time whether a returning customer should see a different offer from a first-time visitor, or adjust what’s presented depending on the device, campaign source, or even the user’s geographic location. These tools don’t limit the experimentation to just the website; they often extend to mobile apps, emails, or other digital touchpoints, helping coordinate a consistent experience across channels.

It’s important to note, though, that this comes with increased complexity. Implementation usually requires solid technical foundations and a steady stream of website traffic for statistically meaningful results. For organizations ready to invest in a more tailored, data-driven optimization approach, however, the potential for nuanced targeting and continuous, automated improvement can be game-changing.

Capabilities That Matter for Teams Demanding Full Analytics Control

If your team requires the highest level of control over both product analytics and experimentation, there are certain features you’ll want to prioritize in your AB testing tool. Many expert-recommended platforms share these key capabilities, which are particularly vital for developer-led teams or those operating in privacy-focused industries:

• Self-Hosting and Open-Source Options: The ability to run the tool on your own infrastructure ensures sensitive data never leaves your servers, supporting strict compliance and security needs.
• Integrated Product Analytics: Beyond simple AB tests, advanced platforms provide built-in analytics so you can track events, behaviors, and outcomes—all tied directly to your experiments.
• Customizable Experimentation (A/B, Multivariate, Rollouts): Support for a range of test types—whether it’s traditional A/B, multivariate, or targeting specific user segments—lets you tailor experiments to your unique product goals.
• Feature Flag Management: Feature flags give you granular control over exactly which users experience what changes, enabling safer rollouts and more targeted experimentation.
• Developer Tooling and API Access: For engineering-driven teams, robust APIs, CLI tools, and integrations with platforms like GitHub and Slack significantly streamline custom workflows and automated deployments.
• Session Replay and Heatmaps: Built-in session recording and heatmapping can surface qualitative insights, helping your team understand user interactions in-depth alongside quantitative outcomes.

For teams that need to move quickly and retain full sovereignty over their data and testing processes, these features are non-negotiable. When evaluating tools, look for solutions that provide both flexibility and the power to manage experimentation and in-depth analytics under one roof.

Mobile-Focused App Testing: Why Native Really Matters

When it comes to experimentation for mobile and cross-platform applications, relying on web-based testing tools is a bit like trying to fit a square peg into a round hole. Tools purpose-built for mobile provide advantages that web-centric platforms simply can’t touch.

Here’s why mobile-first testing platforms stand out:

• Seamless Integration With Native Apps: These platforms are designed to plug directly into iOS, Android, React Native, and even OTT (over-the-top) apps. That means you can test right where your users are—on their phones, tablets, or smart TVs.
• Rapid Iteration Without App Store Delays: One of the largest hurdles in mobile app testing is waiting for app store approvals every time you want to push a change. With a mobile-focused solution, you can deliver real-time updates, deploy test variations, or roll back features instantly. No more bottlenecks in your release process.
• Enhanced Targeting and Personalization: Dig deeper into behavioral segmentation. Target users based on in-app actions, locations, or other custom criteria. This leads to more meaningful experiments and actionable insights—fuel for growth teams.
• Feature Flags and Controlled Rollouts: Want to quietly test a new feature with a specific audience before releasing it to everyone? Feature flags and phased rollouts make it simple, allowing for safer experimentation and swift reversals if something breaks.
• Strong Cross-Platform Coordination: If your product lives across mobile, web, and even TV, you can manage experiments holistically instead of cobbling together separate workflows for each environment.
• Robust Integrations: Connect your experiments directly into analytics suites like Mixpanel, GA4, and Firebase. This turbocharges your data analysis and streamlines reporting efforts.

For teams building and iterating on native apps—especially those working with complex products across multiple platforms—a true mobile-first testing tool isn’t just a nice-to-have. It’s the difference between nimble, effective testing and falling behind in the update race.

Feature Flagging and Feature Management: Enhancing Deployment and Experimentation

In the world of rapid deployments and high-stakes releases, robust feature flagging and feature management have become game-changers for engineering teams and enterprises alike. At Conversion Sciences, we’ve seen how these tools fundamentally reshape not just what gets shipped, but how it’s delivered and iterated.

Why Feature Flags Matter

Gone are the days when every new feature required an all-or-nothing product launch. Feature flags—sometimes called feature toggles—give you fine-grained control over which users see which features, and when. This flexible approach allows you to:

• Release New Features Gradually: Control rollouts by audience, region, or user cohort—no need to deploy to everyone at once.
• Test in Production, Safely: Experiment with live traffic while minimizing risk. If a change underperforms or causes issues, you can instantly disable it without a hotfix or rollback.
• Reduce Deployment Anxiety: Developers and product managers can decouple feature launches from code releases, dramatically lowering the risk of a failed deployment.
• Empower Data-Driven Decisions: Feature flags tie directly into experimentation, allowing you to run A/B and multivariate tests with proper user segmentation and real-time metrics.

Key Benefits of Modern Feature Management

• Risk Isolation: If a new experience causes unexpected problems, a real-time “kill switch” takes it offline—instantly and safely.
• Iterative Improvement: Teams can gather feedback early and often, making incremental adjustments based on real user data instead of assumptions.
• Governance and Compliance: Advanced tools support compliance needs (like SOC 2, GDPR, HIPAA) and help large organizations maintain control over who can launch what, and when.
• Seamless Integration: Feature flags now work hand-in-hand with your CI/CD pipelines, analytics platforms, and observability tools—so experiments and monitoring happen together.

Who Benefits Most?

• Engineering-Led Teams: Especially useful for organizations embracing agile development and continuous delivery.
• Enterprises and Fast-Growing Startups: Where scale, speed, and reliability are non-negotiable.
• Anyone Focused on Experimentation: Ideal for those who want to test hypotheses with rigor and react to customer insights in real time.

Points to Consider

Some platforms excel at granular targeting and integration across mobile, backend, and frontend frameworks. Others make it easy to define custom success metrics (like session-based or domain-specific outcomes), though advanced measurement sometimes requires additional setup.

When used thoughtfully, feature flagging and robust management empower teams to move faster, break less, and learn more. This ultimately means better products—and happier users.

What Makes Mobile-First A/B Testing Tools Effective?

When it comes to mobile app experimentation, not all A/B testing platforms are created equal. For teams focused on optimizing app experiences—whether on iOS, Android, or even cross-platform environments—a truly effective tool is built for mobile from the start.

Here are the core features our experts highlight as differentiators in this space:

• Native SDK Support: The best tools offer robust, platform-specific SDKs, ensuring tests run smoothly on iOS, Android, and frameworks like React Native. This allows for seamless integration without awkward workarounds.
• Real-Time Test Deployment: Effective platforms enable changes to be rolled out instantly, bypassing lengthy app store approval processes. This means teams can iterate, learn, and implement winning variants without waiting for a new release cycle.
• Feature Flags and Controlled Rollouts: Look for options that provide granular control over who sees which features or tests. Phased rollouts and instant rollbacks minimize risk while maximizing flexibility for product and engineering teams.
• Rich Segmentation and Targeting: Advanced in-app targeting capabilities let teams tailor experiments to specific user groups based on behavior, demographics, or device, rather than relying solely on broad audience definitions.
• Deep Integrations: Effective tools play nicely with analytics suites like Mixpanel, Google Analytics 4, and Firebase—helping teams track the right metrics and share insights across their stack.
• Cross-Platform Testing: For companies building beyond mobile—think smart TVs or web apps—strong tools enable coordinated tests across multiple environments without added complexity.

The bottom line: a mobile-first A/B testing solution empowers product and engineering teams to move fast, collaborate confidently, and optimize the app experience with minimal friction or technical hurdles.

Supporting Rapid Iteration in Mobile Experimentation

When it comes to mobile A/B testing, the ability to move quickly without grinding your release schedule to a halt is crucial. That’s where a well-designed mobile experimentation platform makes all the difference.

Instead of waiting on app store approvals every time you want to launch a new experiment, these tools utilize native SDKs that seamlessly integrate with your app. This means you can launch, pause, or adjust experiments in real time—right from your dashboard—without submitting new versions for approval. Product and growth teams are empowered to test ideas rapidly, respond instantly to user data, and iterate multiple times within a single release cycle.

This approach not only accelerates learning but keeps your development pipeline flowing smoothly. By decoupling experimentation from major app updates, teams can optimize user experience and drive growth, all without slowing down the dev team or complicating release timelines.

Advantages of Gradual Rollouts and Real-Time Rollbacks for Engineering Teams

For engineering-led organizations, having the ability to release features gradually—rather than in one sweeping change—delivers a crucial safety net. Instead of flipping the switch for all users at once, you can introduce updates to a small, targeted segment first. This staged rollout means any unanticipated issues can be caught early, before they impact your broader user base.

But the real game-changer comes with instant rollback controls. If a newly released feature starts causing trouble, teams can immediately revert that change for affected users—no time-consuming redeploys or firefighting required. This rapid response protects uptime, minimizes disruptions, and builds confidence in the deployment process.

Key benefits include:

• Risk Isolation: Only a subset of users are exposed to potential bugs, allowing for safer experimentation.
• Faster Recovery: Immediate rollback options limit downtime and user impact, letting teams recover quickly from errors.
• Controlled Experimentation: Teams can target releases to specific cohorts or environments, leading to more reliable data and insights.
• Efficient Collaboration: Large engineering teams benefit from clear controls, versioning, and governance, reducing the risk of unintended consequences.

By taking this cautious, data-driven approach, engineering teams can deploy with greater speed and confidence—turning releases from nerve-wracking events into routine, reversible processes.

Why Real-Time Experience Delivery and Omnichannel Orchestration Matter

When it comes to advanced optimization, real-time experience delivery and omnichannel orchestration are true game changers. Instead of just running classic A/B tests to determine which button color or headline performs best, these capabilities allow you to serve the right message, offer, or variation to the right user at precisely the right moment—no matter where they’re interacting with your brand.

Why does this matter so much? Today’s users seamlessly jump from browsing your website on a laptop, to reading an email on mobile, to checking your app on a tablet. Orchestration ensures the experience stays smart and consistent across every touchpoint, increasing your chance to connect and convert. With real-time delivery, you’re not reacting after the fact; you’re dynamically responding as your visitors engage.

• Personalization at Scale: Tailor experiences for individual users based on their behavior, preferences, or location—on any device or channel.
• Faster Learning: Instantly test and adjust content, layouts, and calls-to-action based on how your audience is actually behaving right now.
• Seamless Consistency: Maintain continuity as users move from one platform or device to another, building trust and reducing friction.

For organizations that are ready—i.e., with enough traffic and the technical chops—these features empower smarter, more agile optimization. This means less guesswork, smarter investments, and, ultimately, better results for your efforts.

1. Optimizely
2. VWO
3. Convert Experiences
4. SiteSpect
5. AB Tasty
6. Evolv
7. Kameleoon
8. Qubit
9. Adobe Target
10. Marketing Tools With Built-In Testing

Top AB Testing Tools for User Behavior and Actionable Insights

Now, let’s talk about tools that go above and beyond traditional A/B testing—they not only help you run experiments but also reveal why users make the choices they do. These platforms fuse behavioral analytics with A/B testing, giving you the heatmaps, click maps, and session replays that illuminate the user’s path (and their detours) through your site.

If you’re wondering which tools excel at capturing user behavior and turning it into actionable insights, these regularly get the nod from experts:

• Hotjar: A fan favorite for visualizing user journeys. Hotjar offers heatmaps, scroll tracking, and session replays, all supported by in-the-moment feedback tools (like feedback polls) so you can actually ask users why they did what they did. It’s a lifesaver when quantitative results tell one story but hidden usability issues lurk beneath the surface.
• Crazy Egg: Perfect for teams who want actionable visual insights without feeling buried in data. With its easy-to-use interface, Crazy Egg gives you click maps, scroll maps, and the ability to quickly set up simple A/B tests. It’s especially handy for marketers and designers who want to spot an issue and try a fix—fast.
• Zoho PageSense: If you’re keen to balance behavioral research and testing, Zoho PageSense packages heatmaps, goal funnels, and experiment tools all in one platform. It’s particularly attractive for startups and small businesses looking for robust capabilities without enterprise pricing.

When Should You Use These Tools?

• Early in the CRO process, to pinpoint where users are struggling or abandoning.
• When you want to test new designs and immediately see how user behavior shifts.
• To supplement raw test results with real user feedback and journey mapping.

Ultimately, these hybrid tools help you move beyond “which version won?” to “why did this version convince users?”—a critical leap for building better tests and, more importantly, better experiences.

Typical Challenges with Open-Source Experimentation Tools

When it comes to open-source experimentation solutions, there are a few common hurdles that teams often encounter—especially if they’re used to the slick onboarding and dashboards of major commercial AB testing platforms.

Initial Learning Curve
One of the biggest differences is the steeper learning curve. Unlike established players like Optimizely or VWO, which surface a lot of site and user data right out of the box, open-source platforms often require more manual setup. For folks transitioning from Google Analytics or similar tools, it can feel like starting with a blank canvas—visitor counts, landing page metrics, or search term data may need to be manually configured before you get real value from the tool.

Onboarding and Integration Nuances
Integrating these solutions isn’t always plug-and-play. It’s pretty common to spend extra time ensuring everything is loading in the correct sequence so that experimental elements appear as intended. If elements load out of order or scripts aren’t prioritized, early tests can get skewed or produce unreliable results.

User Interface and Support
The user interface on many open-source offerings may not match the polish or simplicity of their commercial counterparts. Some teams find it takes extra effort to train new users or troubleshoot confusing workflows. However, active user communities and responsive forums can help bridge the gap—though it may take additional initiative compared to built-in customer support.

Bottom Line
All in all, while open-source tools can be powerful and flexible, they often require a bit more “roll up your sleeves” effort—both in setup and in day-to-day operations. That investment pays off in customizability, but it’s wise to be prepared for a hands-on experience, especially if you’re coming from a platform where “it just works” out of the box.

The Power of Dynamic Content and Personalization

One of the fastest ways to capture a user’s attention—and keep it—is to make them feel like your website was designed just for them. That’s where dynamic content, tailored recommendations, and personalized layouts really shine.

By presenting visitors with content and product suggestions that fit their individual interests and behaviors, you dramatically increase engagement. For example, when an apparel site highlights men’s jackets to one visitor and women’s scarves to another, both users immediately see products aligned with their tastes—no hunting required.

Personalized website layouts can also adapt in real time, arranging banners, calls-to-action, or recommended products to match browsing habits. The result? Shoppers are nudged down the path that’s most likely to lead to a conversion, all while feeling seen and understood.

Crucially, this isn’t just about making things look flashy. Personalization impacts the bottom line: brands like Amazon and Netflix have shown that tailored recommendations keep users browsing longer and coming back more often. When every piece of your site—from hero images to product grids—adapts to the visitor, engagement and measurable conversion lift often follow.

Statsig

Statsig is a newer name on the scene, but it’s quickly earning attention—especially among product and engineering teams looking to bake experimentation directly into their workflows. Designed with both A/B testing and deeper telemetry in mind, it stands apart by combining feature flagging, robust experimentation tools, and real-time analytics into one platform.

Free vs. Paid Plans

Statsig offers a free tier to get you up and running, which is great for small teams or those just starting with experimentation. The free plan includes core A/B testing functionality, feature flags, and access to basic dashboards—enough to run simple experiments and monitor key metrics. However, it comes with notable limits: advanced governance tools are restricted, and the plan caps the number of users and tracked events before requiring an upgrade.

For teams who need to scale, paid plans start at $150 per month. These unlock a full suite of governance and transparency features, more detailed analytics, higher usage thresholds, and priority support. As your experimentation needs grow—think more users, more tests, or complex integrations—upgrading becomes necessary to avoid hitting those free plan ceilings.

So, in summary:

• Free plan: Ideal for early-stage projects, limited governance, lower user and event caps.
• Paid plans: Remove most restrictions, increase visibility and control, scale with your needs.

This model lets you test the waters before making a commitment—just keep a close eye on usage if you’re starting for free, as costs can ramp up once experiments expand.

1. Optimizely

Optimizely is basically the big kid on campus. It’s our experts’ go-to choice for working with enterprise level clients, and despite the significant price increases over the years, it remains the king.

It’s also reasonably user friendly for such a complex tool, as Shanelle Mullin summarizes:

Optimizely is the leading A/B testing tool by a fairly large margin. It’s easy to use – you don’t need to be technical to launch small tests – and the Stats Engine makes testing easier for beginners.

True to that, I was able to deploy our first test within a couple of hours, not days. The platform hits a sweet spot: visual editors for marketers, feature flags for developers, and AI-powered recommendations for personalization—without overwhelming complexity. This means both marketers and developers can collaborate smoothly, tailoring experiments and personalizations without getting bogged down by the tool itself.

Here at Conversion Sciences, we use this tool every single day, so I asked them to give me a few thoughts on what they like and dislike about it.

According to the team, Optimizely offers some of the following benefits.

• Easy editing access through the dashboard
• Retroactive filtering (e.g., IP addresses)
• Intuitive data display and goal comparison
• Saved Audiences (not available in VWO)
• Great integration with 3rd-party tools

On the flip side, Optimizely is a bit lacking in these ways:

• Test setup is not as intuitive compared to other tools
• Slow updates for saved changes to the CDN
• Doesn’t carry through query params/cookies within a certain test
• Targeting is more difficult

Optimizely’s multivariate testing setup is simple and intuitive, and it’s the leading split testing tool for a reason. For businesses with the budget and team to utilize Optimizely to its fullest potential, it is clearly a must-own.

2. VWO

Coming in just behind Optimizely in the AB testing pantheon is Visual Website Optimizer (VWO). VWO is incredibly popular in the marketing space, and in addition to serving as a top choice for businesses with smaller budgets, it is also frequently used in conjunction with Optimizely by businesses who run complex testing campaigns.

Our Conversion Scientists® feel VWO offers some of the following benefits as compared to Optimizely:

More intuitive interface with color coding

• Faster updates
• Easier goal setup
• Easier to download data
• Better customer support

On the flip side, VWO is lacking in the following areas:

• Can’t view goal reports all at once, which makes them harder to compare
• No saved targeting, so you must start fresh with each test unless you clone
• No cumulative CR graph if you have low traffic (or what VWO considers low traffic). Instead it gives CR ranges. You must export the data to get any usable information.

This perspective is mostly shared by the ConversionXL team as well, as explained by Shanelle Mullin:

VWO is very easy to use, especially with its WYSIWYG editor. They have something similar to Optimizely’s Stats Engine called Smart Stats, which is based on Bayesian decisions. VWO also offers heatmaps, clickmaps, personalization tools and on-page surveys.

For those new to experimentation, VWO stands out as a user-friendly option for A/B testing and gathering site insights. Its interface streamlines setup, and the addition of AI-driven suggestions can help identify potential test ideas—though these suggestions may sometimes feel a bit generic. The Copilot tool, which generates test variations, is especially handy for making quick changes to smaller page elements, but isn’t as flexible for larger or more complex experiments.

Keep in mind, VWO doesn’t currently allow you to set multiple primary metrics for a single test, nor does it provide recommendations across several metrics at once. This can make it a bit limiting if you’re trying to balance multiple priorities in a single experiment. Nonetheless, for most marketing teams and growing businesses, VWO’s balance of features and usability hits a sweet spot for everyday website optimization.

Overall, VWO is an intriguing solo option for small to midsize businesses and also works very well in conjunction with Optimizely for enterprise clients.

VWO: Pricing and Integration Advantages

When it comes to pricing, VWO stands out as a strong contender for businesses seeking powerful experimentation capabilities without the enterprise-level price tag. While Optimizely is positioned firmly in the premium tier, VWO offers a more accessible entry point, starting around $393/month—making it a much friendlier option for small to midsize businesses and larger marketing teams that may not have massive testing budgets. This cost-effectiveness is especially attractive for those eager to move beyond basic button tweaks and into advanced testing strategies, but who aren’t quite ready for the financial leap to a tool like Optimizely.

VWO also shines in its integrations, particularly with popular platforms such as Shopify, HubSpot, Google Analytics 4, and Mixpanel. These integrations are straightforward to set up, allowing teams to sync experiments and funnel data from their sites without significant developer involvement. Many of our Conversion Scientists® appreciate how seamless it is to connect VWO with existing marketing stacks, enabling robust tracking, user segmentation, and goal analysis—without jumping through technical hoops.

In short, if you’re looking for an A/B and multivariate testing suite that balances budget with an impressive array of features and integrations, VWO delivers an excellent blend of power, price, and flexibility for growing teams.

3. Convert Experiences

While Optimizely and VWO were the tools most commonly mentioned, Convert Experiences received some of the most effusive praise from those who had worked with it.

It seems to have hit a sweet spot for SME/SMBs, combining an exceptional power-to-price ratio with an intuitive interface and highly regarded customer support.

We are platform agnostic, so if our client already has a tool in use, then we try to use that.  But in cases where the client has never done any testing before, we typically look first to use Convert (convert.com).  I like Convert for a number of reasons.  From the very beginning, it has been one of the easiest tools to integrate with Google Analytics.  Also, for tricky variations, I’ve had better luck with Convert than others (Optimizely) at getting the variation to display just the way we want.  And the support at Convert has always been excellent—again, better than most of their competitors.

We focus on small to medium size clients, and Convert is excellent for that segment with flexible pricing.  It’s a great solution for small businesses doing in-house conversion optimization, but it can also work very well for agencies.

– Tom Bowen, Web Site Optimizers

Convert Experiences also stood out as the type of tool that catches new fans wherever it’s discovered, leading me to believe that it will continue to grow and pick up market share.

We have come across convert.com more and more in recent months working on client campaigns.  If you are a true marketer and want actionable data then they are a good choice.  The user interface is actually pretty good and you can actually understand the data they give you on experiments.  They run on the typical drag and drop style experiment setup engine that most others do and can be manipulated even if you aren’t a technical wizard.

The price isn’t too bad either as they fall somewhere in the middle of Optimizely and VWO.  I would recommend them to someone who has a bit of budget constraints but wants a bit more testing power.  We have used them on multi million dollar per month campaigns with much success.

– Justin Christianson, Conversion Fanatics

Convert Experiences is known for having some of the most robust multivariate testing options in it’s class. At the same time, it is also one of the few tools in its class to not offer any sort of email split testing capabilities.

Overall, it’s a highly recommended AB testing tool that is worth trying out.

Convert has great customer support (via live chat) and is easy to use. We’d recommend it to the same people who are considering using Optimizely and VWO.

– Karl Blanks, Conversion Rate Experts

4. SiteSpect

SiteSpect initially distinguished itself as one of the first server-side testing solutions on the market, and it has remained a top choice for more technically sophisticated users and security-conscious clients.

For a long period, SiteSpect was one of the few platforms offering a server-side solution. This has given them a huge advantage by allowing more complex testing, by adapting to newer JavaScript technologies, and by accommodating security-conscious clients. – Stephen Pavlovich, Conversion

SiteSpect has the advantage that it works in a different way. It’s tag-free. SiteSpect edits the HTML before it even leaves the server, rather than after it has hit the user’s browser. It tends to be popular with companies that want to self-host and are technically sophisticated. – Karl Blanks, Conversion Rate Experts

As a server-side testing solution, SiteSpect avoids many of the issues that can arise with the more typical browser-based testing platforms that utilize javascript tags.

• Tag-based solutions typically charge by the number of tag calls you make, even if those tags don’t end up being used.
• Tag-based solutions often require third-party cookies, which certain browsers or browser settings might not support, causing you to lose the ability to test a large percentage of traffic.
• Tag-based solutions can have imprecise reporting because the javascript doesn’t always fire.

While this value proposition won’t be the deciding factor for many businesses, for those requiring a server-side solution, SiteSpect is one of the best options on the market.

5. AB Tasty

AB Tasty is a solution for testing, re-engagement of users, and content personalisation, designed for marketing teams. Paul Rouke had a good bit to say here, so I’ll let him take it away.

The tools that in my experience deliver the most long-term value are those which are reasonably priced, allowing companies to spend more of their budget on making sure they are testing intelligently and developing an effective testing process. I talk about this in-depth in my article The Great Divide Between BS and Intelligent Optimization.

On this note, my favorite tool would be something like AB Tasty, which is priced sensibly, yet has a powerful platform that facilitates a wide range of testing, from simple iterative tests through to innovative tests, along with strategic tests which can help evolve a business proposition and market positioning.

I would recommend AB Tasty (and similarly Convert.com) to the following types of companies:

(1) Companies just starting to invest in conversion optimisation – they won’t break the bank, they won’t overwhelm you with add-ons you will never use as you’re starting out, but they have the capability to match your progress as you scale up your testing output

(2) Companies who have been investing in conversion optimisation but who want to start using a higher portion of their budget (75% or more) on people, skills, process and methodology in order to deliver a greater impact and ROI

(3) Companies frustrated at investing significant amounts of money in enterprise testing platforms, which aren’t being used anywhere near their potential and are taking away from the budget for investing in people, skills and developing an intelligent process for strategic optimisation.

6. Evolv AI

Evolv brings advanced machine learning algorithms to the CRO space, helping you identy exactly why your customers aren’t converting, how to fix it, and the potential revenue impact. It was one of the first conversion optimization apps to leverage AI, and it’s becoming exponentially more precise over time.

This is important because it speeds up multivariate testing. Evolutionary, or genetic algorithms do a better job of finding optimum combinations, isolating the richest local maximum for a solution set.

Our team of scientists love being able to assemble our highest rated hypotheses and throw them in the mix to have the machine sort them for us. This really is the future of conversion optimization.

Why Evolv AI Stands Out

While most platforms limit you to standard A/B or simple multivariate tests—running two or three variants and hoping for a clear winner—Evolv supercharges the process. Instead of being boxed into a handful of options, you can test dozens (even hundreds) of creative combinations at once. The AI continuously blends, evolves, and prioritizes what’s working, adapting in real time as your visitors interact with your site.

Who Will Benefit Most

Evolv is especially well-suited for mid-sized to enterprise brands that need optimization beyond the basics. If you’re wrestling with complex journeys (think pricing pages or multi-step forms), or you simply want your experiments to run while you’re sleeping, Evolv keeps iterating and learning from live traffic.

Core Features at a Glance

• Evolutionary testing across a vast range of variations
• Continuous deployment—no more one-and-done winners
• AI-driven optimization that learns with real traffic
• Visual editor for marketers; dev integrations for advanced use cases
• Real-time dashboards showing top performers and incremental lift
• Support across web, mobile, and connected devices
• Enterprise-grade support and services

What You’ll Really Like

Evolv takes the guesswork out of optimization. Instead of lining up a queue of manual tests, you set your best hypotheses, plug them in, and let the algorithms do the heavy lifting. The result? Faster, smarter insights and the ability to uncover combinations you might never have tried manually.

In short, Evolv isn’t just about finding a needle in the haystack—it’s about letting the haystack organize itself so the needle jumps out at you.

7. Kameleoon

Kameleoon is a web experimentation tool that offers some of the most well-thought-out reporting of any tool we’ve used. They offer features for websites and apps with a dash of AI to identify segments and predict conversions.

Kameleoon makes it easy for our product managers and marketing teams to build experiments. It fits into our tech stack and our existing product release process. Developers get feature flagging and we get to experiment without taking up all their time.

Alexandre Suon, Head of Experimentation, Accor Group

How Kameleoon Pricing Works—and Integration Highlights

Kameleoon doesn’t post set rates online; instead, they tailor pricing depending on your unique business needs, usage, and scale. This means you’ll want to reach out directly for a custom quote that matches your experimentation goals and team size.

On the integration front, Kameleoon is impressively flexible. You can connect with major analytics powerhouses such as GA4, Segment, and Mixpanel. CRM systems? No problem. They also offer strong collaboration tools and can slip right into a wide range of tech stacks. Whether you’re running A/B or multivariate tests on the web or server side, or managing privacy, Kameleoon brings full-stack SDKs and privacy controls to the party—so your team can work smarter, not harder.

What Sets Kameleoon Apart for Experimentation and Personalization?

Kameleoon shines with its emphasis on precision, flexibility, and compliance—qualities that make it especially appealing for organizations with strict regulatory needs, like healthcare and finance.

• AI-Powered Targeting: The platform’s AI-driven segmentation does more than just identify basic user behaviors. It predicts which visitors are most likely to convert, enabling you to act quickly on intent signals for more effective campaigns.
• Comprehensive Experimentation Tools: Whether you’re testing new UI elements or launching controlled rollouts for backend features, Kameleoon provides both visual and code-based editors, alongside full-stack SDKs. This means tech and product teams, regardless of their setup, can easily design and implement experiments.
• Built-In Privacy Safeguards: For industries where data privacy isn’t merely a checkbox, Kameleoon has robust consent and privacy management baked in. It’s designed to help you stay on the right side of regulatory requirements, with minimal fuss.
• Personalization at Scale: Real-time personalization capabilities let you create dynamically tailored experiences for each segment—combining the best of automation and human oversight.
• Smooth Collaboration: Large teams can work efficiently with built-in collaboration and version control tools, ensuring that changes are well-documented and smoothly implemented.

All in all, if your organization requires both the power to experiment freely and the assurance of rock-solid compliance, Kameleoon manages to deliver both—without over-complicating your workflow or overwhelming your teams.

8. Qubit

Qubit is a testing platform focused primarily on personalization. Accordingly, it has some of the strongest segmentation capabilities of any tool on this list.

Qubit has a strong focus on granular segmentation – and the suite covering analytics through to testing gives it an advantage. They’ve now broken out of their traditional retail focus to become a strong personalisation platform across sectors.

– Stephen Pavlovich, Conversion

If advanced segmentation or personalization are a priority for your business or clients, Qubit is a tool worth checking out.

9. Adobe Target

Long known for being the most expensive AB testing tool on the market, we’ve found that Adobe Target works best with sites that already use Adobe Analytics.

If your business is already paying for Adobe Analytics, adding Adobe Target is virtually a no-brainer. If your business is not using Adobe Analytics, ignoring Adobe Target is virtually a no-brainer.

Here’s how Stephen Pavlovich feels about it:

I like Adobe Target. The integration of Adobe Analytics and Target is strong – especially being able to push data two-ways. And the fact that Target is normally an inexpensive upsell for Analytics customers is a bonus.

2 Marketing Software Tools With Built-In AB Testing

In addition to dedicated AB testing tools, there are some great marketing software out there that include built-in split testing capabilities. This is fairly common with tools like landing page builders, email service providers, or lead capture solutions.

As Justin Christianson explains, there are some positives and negatives to relying on these built-in tools:

Most page builders out there such as LeadPages and Instapage have split testing capabilities built into their platforms.  The problem is you don’t have much control over the goals measured and the adaptability to test more complex elements.  The good thing is they are extremely easy to setup and use for those quick and dirty type tests.  I recommend the use of this to just get some tests up and running, as constantly testing is extremely important.  If you are currently using a platform with these native testing capabilities then this is a good place to start.

1. Unbounce

One particular tool that was highlighted by several of our experts was Unbounce, one of the web’s more popular landing page builders.

I also like Unbounce, and not just because I like Oli Gardner. It seems most everyone there lives and breathes landing pages, so the expertise that comes with the tool is virtually unmatched.  Their support is also excellent.  Unbounce works really well when we’re creating a new landing page from scratch and want to try different variations, since it’s so easy to create brand new pages using the tool.

– Tom Bowen, Web Site Optimizers

Unbounce is an excellent tool for A/B testing your landing pages. While many landing page tools also offer A/B testing, I think Unbounce has the best and most flexible page editor when creating variations of your pages to be tested, and their landing page templates have the most CRO best practices included already.

Unbounce is outstanding for online marketing teams that want the most flexibility when creating and A/B testing their landing pages – many other landing page tools are limited to a fixed grid system which makes it much harder to make changes.

– Rich Page

2. OptinMonster

Another popular tool was OptinMonster, which began as a popular popup tool and has evolved into a more fully featured lead generation software.

Optin Monster is an outstanding tool that lets you easily A/B test visitor opt-in incentives to see which converts best – not only headlines, images and CTAs, but also which types perform best (like a discount versus a free guide). In particular it offers great customization options and many popup styles, and exit intent popups.

Optin Monster is particularly useful for the many website marketers who don’t have enough traffic to do formal A/B testing (using tools like Optimizely or VWO) but still want to get a better idea of their best performing content variations. It has great pricing options suitable for online businesses on a low budget.

– Rich Page

12 Tools For Gathering Data

As every good split tester knows, your AB tests are only as good as the hypotheses you are testing. The following tools represent our experts’ favorite choices for collecting data to fuel effective AB tests.

1. UsabilityHub
2. Google Analytics
3. Crazy Egg
4. UserTesting.com
5. UserZoom
6. ClickTale
7. HotJar
8. Mouseflow
9. Inspectlet
10. SessionCam
11. Lucky Orange
12. Adobe Analytics

1. UsabilityHub

UsabilityHub was by far the most frequently mentioned analytics tool by our group of CRO experts. UsabilityHub is a collection of 5 usability tests that can be administered to visitors in order to collect key insights.

UsabilityHub is great for clarity testing and getting quick indications of potential improvements. It is also great for uncovering personal biases in the creation of page variations. I would recommend it to anyone doing conversion optimization or even basic usability testing.

– Craig Andrews, allies4me

While many of the tools on this list deal primarily with quantitative data, UsabilityHub offers uniquely efficient ways to collect valuable qualitative data.

Once I’ve identified underperforming pags, the next step is to figure out what’s wrong with those pages by gathering qualitative data. For top landing pages, including the homepage, I like to run one of UsabilityHub’s “5 Second Tests” to gauge whether people understand the product or service offered. The first question I always ask is “what do you think this company sells?”. I’ve gotten some surprisingly bad results, where large numbers of respondents gave the wrong answer. In these cases, running a simple A/B test on a headline and/or hero shot to clarify what the company does is an easy win.

– Theresa Baiocco, Conversion Max

It also can be a cost-effective alternative if your website doesn’t get enough traffic to facilitate use of an actual split testing tool.

UsabilityHub is essential if you want to do A/B testing but your website doesn’t have enough traffic to do so. Instead it enables you to show your proposed page improvements to testers (including your visitors) to get their quick feedback, particularly using the highly useful ‘Question Test’ and ‘Preference Test’ features.

UsabilityHub can be particularly useful for the many website marketers who don’t have enough traffic to do formal A/B testing (using tools like Optimizely or VWO) but still want to get a better idea of their best performing content variations.

– Rich Page

2. Google Analytics

To the surprise of exactly no one, Google Analytics was high up on the list of recommended analytics tools. Yet despite its popularity, very few marketers or business owners are using this free tool to its full potential.

Theresa Baiocco makes the follow recommendations for getting started:

There’s so much data in Google Analytics that it’s easy to suffer from paralysis by analysis. It helps to have a few reports you use regularly and know what you’re looking for before jumping in. The obvious reports for finding the most problematic pages in your funnel are the funnel visualization and goal flow reports. But I also like to look at top landing pages, and using the “comparison” view, I see which of them have higher bounce rates than average for the site. Those 3 reports together are a good starting point for identifying which pages to work on first.

When it comes to applying Google Analytics to your AB testing efforts, John Ekman of Conversionista offers some advice:

Most of the AB testing tools provide an easy integration with Google Analytics. Do not miss this opportunity in your AB testing setup!

When you integrate your testing tool with GA it means that you will be able to break down your test results and look at A vs. B in all dimensions available in GA. You will be able to see behavior segmented by device, returning vs new visitors, geography etc.

For example: if you are using Enhanced Ecommerce setup for GA you will be able to compare your E-commerce funnel for the A version vs. the B version. Maybe the A version gets more add to carts, but then that effect withers off and the result in the checkout is the same?!

Word of warning: as soon as you start segmenting your data you might lose statistical significance in the underlying segments. Even if your AB test results are statistically significant on the overall level that does not mean that the deviations you see in smaller segments of your test data are significant. The smaller the data sample size, the harder it is to reach significance. What you think is a strong signal is just some data noise.

For those interested in tapping into the full potential of Google Analytics, here’s some resources you may need..

3. Crazy Egg

Crazy Egg is one of the more popular heatmap and click-tracking tools online, thanks to an attractive interface, an affordable price point, and a deceptively powerful feature set.

Our Conversion Scientists not only use Crazy Egg, we highly recommend it. Here’s what they says about it:

Crazy Egg offers tools to help you visually identify the most popular areas of your page, help you see which parts of your pages are working and which ones are not, and give you greater insight as to what your users are doing on your pages via both mobile and desktop sites.

4. UserTesting.com

UserTesting.com is a unique service that provides videos of real users in your target market experiencing your site and talking through what they’re thinking.

This service is recommended by Craig Andrews, who had the following to say:

UserTesting.com is great for hypothesis generation and uncovering personal biases. It is an absolutely fantastic tool for persuading clients on the reality and importance of certain site issues, and I would recommend it to anyone doing conversion optimization or even basic usability testing

5. UserZoom (formerly Validately)

UserZoom provides a complete online user testing service.

For a somewhat less expensive alternative to UserTesting.com we have found UserZoom to be an effective solution. The quality of the panel members is good, and their panel is large enough that user tests are completed quickly.

6. ClickTale

Clicktale is a cloud-based analytic system that allows you to visualize your customer’s experience on your website from their perspective. It’s an enterprise-level tool that combines session recording with click and scroll tracking, and while it comes with an enterprise price tag, it’s made some significant quality strides over the last few years.

As Dieter Davis summarized recently for UX Magazine:

There has been a huge improvement in Clicktale over the past three years, in tracking, reporting and accuracy. If you want “any old session recording JS”, boxed-product application out there, there are a variety of options. If you want accurate rendering that is linked to your existing analytics and a company that will help you tune as your own website evolves, then Clicktale is a good choice. It’s the one I’ve chosen as I wouldn’t want to risk the privacy of my customers or risk degrading the performance of my website. Clicktale also gives me a representative sample that is accurate by resolution and responsive design.

What sets Clicktale apart is how smoothly it integrates into your broader analytics ecosystem. You can easily connect it with your existing analytics tools, triggering tests on specific variables and measuring results in real time—without having to push an update to your site. This means you can roll out changes as your needs evolve, all while maintaining site performance and user privacy. The ability to view session data by device resolution or user journey, combined with enterprise-level support, makes it especially valuable for teams who want both flexibility and actionable insights as their website grows and changes.

7. Hotjar

HotJar is a jack of all trades type tool: an all-in-one tool that does heatmaps, scroll tracking, recordings, funnel tracking, form analysis, feedback polls, surveys, and more.

And from what a few of our Conversion Scientists have seen so far, it does all of those things about as well as you would expect from a jack of all trades.

On the plus side, Hotjar has prioritized creating an exceptional user experience, so if you are a solo blogger wanting a feature-rich, easy-to-use toolkit in one place with a reasonable price tag, Hotjar might be the perfect choice for you.

Stephen Esketzis had the following to say about his experience with the tool:

So overall, HotJar really is a great tool with a lot of value to offer any online business (or website in general at that). There’s not many businesses that work online I wouldn’t recommend this tool to.

With a no-brainer price point (and even a free plan) it’s pretty hard to go wrong.

Hotjar sits comfortably among the top behavioral analytics tools, offering a balance of breadth and accessibility that makes it a favorite for many online businesses. While it may not compete with some enterprise-level platforms on advanced features like full server-side testing or robust feature flagging, it covers the essentials for most marketers and site owners: heatmaps, scroll tracking, session recordings, funnel tracking, form analysis, surveys, and feedback polls.

A Quick Comparison With the Field

Hotjar stands out for its ease of use, flexible pricing, and generous free tier (limited to three surveys and feedback widgets). This makes it especially appealing for solo bloggers, small businesses, and anyone wanting actionable insights without heavy upfront investment. In the broader landscape, here’s how it matches up:

• Ease of Use: Hotjar is consistently rated as easy to implement and navigate, even for non-technical users.
• Analytics-Focused: Unlike platforms that double as full-featured A/B testing suites, Hotjar excels at visual analytics and qualitative feedback—think heatmaps and user recordings, not multivariate tests.
• Pricing: Starts at $48/month, but the free plan covers a lot, making it a risk-free way to start gathering insights.
• Mobile Testing: While not as deep as some competitors, it covers mobile basics, which is plenty for most use cases.

If you’re after an all-in-one behavioral analytics tool that won’t break the bank and doesn’t require a PhD to use, Hotjar is a solid choice.

8. Mouseflow

Mouseflow is another Swiss army knife of user intelligence. The service bundles screen recording, heatmap reports, on-site surveys, funnel tracking and form analysis.

We like it because it provides advanced segmentation. Filters include traffic source, platform, location, and more. It also supports segmentation by custom variables.

On the Intended Consequences podcast, Evan Hill said of the power of data:

“So I would I think that’s one of the most exciting things for a marketer who finally grabs this tool installs it, because they’re about to get the data they need to have really really interesting meetings.”

9. Inspectlet

Inspectlet is primarily a session recording tool with additional heatmaps as well. Here’s what Anders Toxboe had to say about it in a recent review:

Inspectlet is simple to use. It gets out of the way in order to let the user do what he or she needs. The simple funnel analysis and filtering options is a breeze to use and covered my basic needs.Inspectlet does what it does good with a few minor glitches. It doesn’t have the newer features that have started appearing lately such as watching live recordings, live chatting, surveys, and polls.

In other words, Inspectlet is an easy-to-use, budget-friendly session recording tool that might be right for you depending on your needs.

10. SessionCam

SessionCam is a session recording tool that has also added heatmaps form analytics to its offering. It’s a classic example of a tool that combines better-than-average functionality with a more-difficult-than-average user interface.

Peter Hornsby had the following to say in his review for UXmatters:

SessionCam provides a lot of useful functionality, but its user interface isn’t the easiest to learn or use. Getting the most out of it requires a nontrivial investment of time.

And later:

UX designers have long known that, where there is internal resistance to change, showing stakeholders clear evidence of users experiencing problems can be a powerful tool in persuading them to recognize and address issues. SessionCam meets the need for a tool that provides this data in a much more dynamic, cost-effective way than using traditional observation techniques.

SessionCam [also] manages [to protect user data] effectively by masking the data that users enter into form fields, so you can put their concerns to rest.

Users often find that while SessionCam delivers in terms of features—like advanced session recording, heatmaps, and form analytics—the overall experience can feel less intuitive compared to other tools. The learning curve is noticeably steep, especially for teams without dedicated technical resources. Some have pointed out that certain features feel more complicated than they need to be, and navigating between different functions may require extra steps. Additionally, the interface can feel clunky at times, which may slow down workflows, particularly if you need to manually filter or analyze specific user journeys.

Despite these drawbacks, once you’re over the initial hurdles, the depth of data and insights available make SessionCam a valuable option for those willing to put in the effort.

If you are looking for a more robust session recording and form analytic tool that keeps user data safe, SessionCam is worth checking out.

11. Lucky Orange

Lucky Orange is kind of like Crazy Egg with a bit of UserTesting.com, a bit of The Godfather, and a bit of a hundred other things. It’s a surprisingly diverse package of conversion features that make you start to believe their claim as “the original all-in-one conversion optimization suite”, despite the incredibly low price point.

Despite the hundred new tools that have popped up since Lucky Orange hit the market, Theresa Baiocco still swears by the original:

No testing program is complete without analyzing how users behave on the site. Optimizers all have their favorite tools for gathering this data, and while the newest and hottest kid on the block is Hotjar, I still like using my old go-to: Lucky Orange. Starting at just $10/month, Lucky Orange gives you visitor recordings, conversion funnel reports, form analytics, polls, chat, and heat maps of clicks, scroll depth, and mouse movements – all in one place.

12. Adobe Analytics

Adobe Analytics is a big data analysis tool that helps CMOs understand the performance of their businesses across all digital channels. It enables real time web, mobile and social analytics across online channels, and data integration with offline and third-party sources.

In other words, Adobe Analytics is a $100k+ per year, enterprise level analytics tool that has some serious firepower. Here’s what David Williams of ASOS.com had to say about it:

After a thorough review of the market, we chose Adobe Analytics to satisfy our current and future analytics and optimization needs. We needed a solution that could scale globally with our business, improve productivity, and offer out-of-the box integration with our key partners to deliver more value from our existing investments. Adobe’s constant pace of innovation continues to deliver value for our business, and live stream (the event firehose) is the latest capability that opens up exciting opportunities for how we engage with customers.

AB Testing Tools Conclusion

Well that’s that: 20 of the most recommended AB testing tools from a diverse collection of the web’s leading CRO experts.

Have you used any of these tools before? Do you have a favorite that wasn’t included? We’d love to hear your thoughts in the comments.

And if you are looking for a quick way to calculate how a conversion lift could increase your bottom line, be sure to check out our Optimization Calculator.