7 Best A/B Testing Tools I Trust to Boost Conversions

When you work in marketing, you’re constantly making decisions that could go either way. Should that CTA say “Get Started” or “Try It Free”? Should the landing page headline focus on value or urgency? I’ve lost count of how many times I thought I knew what would convert better… only to be proven wrong by the data.

That’s why the best A/B testing tools aren’t just nice to have, they’re essential. Whether you’re tweaking headlines, testing button colors, or experimenting with entire page layouts, these tools take the guesswork out of optimization.

And if you’re anything like me, you’re juggling traffic goals, conversion targets, campaign deadlines, and maybe a dash of impostor syndrome for flavor.

In this list, I’m sharing some of the best A/B testing tools I’ve come across, tools that can help marketers, growth teams, and startup founders test smarter, not harder. Some are beginner-friendly. Some are built for scale. But all of them have one thing in common: they make decisions less risky and results more real.

7 best A/B testing tools I recommend for better optimizations 

Before I started using A/B testing tools, I used to rely on guesswork, tweaking headlines, changing button colors, or rewriting CTAs just hoping they’d perform better. But hope isn’t a strategy. That’s where A/B testing tools completely shifted how I approached optimization.

At its core, an A/B testing tool lets you compare two (or more) versions of a webpage, email, CTAs, or element to see which one performs better. You create a variation, set a goal (like clicks, sign-ups, or revenue), and the tool splits your traffic between the original and the test version. Then it shows you, with real data, which one actually works. It’s like having a marketing crystal ball, except it’s backed by numbers, not gut feelings.

These tools usually handle everything behind the scenes, from splitting traffic to tracking behavior and running the numbers. Some offer drag-and-drop editors so you can make changes without coding. Others go deeper with features like audience targeting, heatmaps, or detailed analytics. The goal is simple. Make decisions based on what works, not what you hope will work.

My criteria for the best A/B testing tools 

There’s no one-size-fits-all when it comes to A/B testing platforms. Here’s what I looked for to find tools that actually support real-world experimentation across teams.

• Ease of use with flexible setup: A tool only works if your team can actually use it. I looked for platforms with intuitive interfaces that work for marketers, designers, and product folks, while still offering flexibility for developers when needed.
• Targeting and segmentation capabilities: Not every test should go to every user. I prioritized tools that allow targeting by behavior, device type, traffic source, geography, or other custom rules to keep tests relevant and accurate.
• Statistical reliability and transparent reporting: Clean reporting matters. I looked for tools with built-in statistical significance thresholds, clear confidence levels, and reports that make sense to marketers, product teams, and analysts alike.
• Integrations with existing tools: Testing in isolation doesn’t help anyone. I favored platforms that integrate with tools teams already use, like Google Analytics, HubSpot, Segment, Mixpanel, or internal data pipelines.
• Server-side and multivariate testing support: While simple A/B tests are great, I wanted tools that could also handle deeper product experiments. Server-side testing and multivariate capabilities are key for teams running complex or logic-based tests.
• Collaboration and experiment management: A/B testing usually involves more than one team. I looked for features that support shared access, comments, permissions, or experiment history so teams can collaborate without chaos.
• Cost and scalability: Budgets vary. I paid attention to tools that offer transparent pricing, flexible plans, and the ability to scale up as traffic, test complexity, or team size grows.

After evaluating more than 15 A/B testing tools, I narrowed the list down to seven that truly stood out. These tools offer a strong mix of functionality, efficiency, and reliability. While none of them are perfect, each one brings something worthwhile to the table, whether it’s ease of use, advanced features, or the ability to scale with different team needs.

The list below contains genuine user reviews from the best A/B testing tools. To be included in this category, a solution must:

• Conduct split-traffic experiments with defined, trackable goals to determine best best-performing web content.
• Deploy multiple versions of any web content in real time.
• Perform split-URL experiments.
• Adjust and manage traffic volume to experiment with variations.
• Provide tools for both technical and non-technical users to perform tests.

*This data was pulled from G2 in 2025. Some reviews may have been edited for clarity.  

I’ve known VWO as one of the more established names in A/B testing, so I was curious to see how it holds up in a modern optimization workflow.

I gave it a spin during its 30-day free trial, and right off the bat, the onboarding felt thoughtful and guided. The “Get Started” dashboard walked me through setup with clean progress indicators and step-by-step tasks.

Connecting a domain to generate the SmartCode was straightforward, and I appreciated the option to automatically track subdomains. For someone without a dev background, this made installation a lot less intimidating.

Where VWO really started to shine was in the testing interface. Setting up A/B tests felt intuitive, and even the sample report made the experience feel real. The reporting dashboard was clean and detailed, highlighting the winning variation with metrics like conversion uplift, probability of outperforming the baseline, and segmented visitor data.

There’s a lot more to like in my view. VWO combines A/B testing with features like heatmaps, session recordings, and funnel analysis, all under one roof. This makes it a solid choice for teams that want more than just simple split tests. It’s especially useful if you’re managing conversion rate optimization at scale or juggling multiple testing goals across landing pages, product features, or campaigns.

One thing I noticed is that with all the power VWO offers, there’s naturally a bit of a learning curve. It’s not overwhelming, but there’s a lot happening on the platform. During my trial, I had to click around a few times to get familiar with the flow. Once I got the hang of it, the setup and navigation felt much smoother.

The other thing to keep in mind is pricing. VWO includes a wide range of features like testing, heatmaps, and behavioral insights, which makes it a strong all-in-one platform. But for smaller teams or those just starting with experimentation, the cost might feel a little high. If you’re running consistent tests and need deeper insights, though, the value is absolutely there. I saw this echoing in a few G2 reviews, too.

If you’re in marketing, product, UX, or even CRO at a mid-sized or enterprise company, I’d say VWO is definitely worth a closer look. And with a 30-day free trial, there’s no harm in seeing how it fits into your workflow.

What I dislike about VWO Testing:

• There’s definitely a learning curve at the beginning, and I had to spend time getting familiar with where everything lives in the interface.
• The pricing might be a bit much for smaller teams, especially if you’re not using all of the advanced features right away.

What G2 users dislike about VWO Testing: 

“Getting used to the tool was a bit of a learning curve, but this was my first experience in using a third party for creating AB tests, so I imagine it would be a similar experience with any other competitor. However, support was easy to reach and helped to answer any questions or doubts.” 

– VWO Testing Review, Tay A, Senior UX Analyst. 

Bloomreach is a newer find for me, but it quickly caught my attention as an AI-powered platform built specifically for e-commerce. It brings together product discovery, content personalization, email, and search into one place, which makes it feel more like a full experience engine than just an A/B testing tool.

What surprised me most was how deeply A/B testing is baked in across the platform. Whether it’s email, SMS, in-app content, ads, or even offline channels, you can test almost anything.

While I didn’t get to run a live test, I took a detailed product tour and spent time digging into how A/B testing works inside the platform. 

I could immediately tell it was built for teams that want to optimize digital experiences at the structural level. This isn’t just a tool for swapping headlines or tweaking CTA colors. Bloomreach lets you test deeper changes, like product ranking logic, personalization rules, site search redirects, and even algorithm-level decisions.

Looking at user feedback on G2, I wasn’t the only one impressed by its flexibility. Many reviewers mention how reliable and feature-rich Bloomreach is, especially when it comes to personalization and customer journey control. People also praise the support team, which aligns with the helpful documentation I came across during my research.

That said, the depth of functionality also comes with a bit of a trade-off. A few reviewers noted that some features don’t offer as much flexibility out of the box as they’d like. And also, it’s not the kind of tool you casually poke around in. It is difficult to get started with. It does take a bit of time to get comfortable with everything, but once it clicks, the possibilities are pretty exciting. I’d say it’s better suited for teams with a clear testing strategy and the desire to customize experiences across a large catalog.

That said, I can say Bloomreach feels incredibly powerful for brands that want to go beyond surface-level A/B tests. If you want to fine-tune how products are delivered, personalize journeys, and back those decisions with real experiments, this is the kind of platform you should turn to.

What I dislike about Bloomreach:

• I noticed several reviewers mentioning that Bloomreach has a bit of a learning curve. With all its capabilities, I imagine it takes some time to fully understand how everything connects, especially when setting up more complex journeys or experiments.
• A few users also pointed out that certain features can feel limited,  and that getting things exactly how you want sometimes requires a workaround. It’s not a dealbreaker, but it’s something I’d expect if I were customizing heavily.

What G2 users dislike about Bloomreach:

“It is not so much of a dislike – however, some advanced features require you to have semi-technical expertise to maximise the gains.” 

– Bloomreach Review,  Sanket M, Digital Marketing Manager. 

With a name like AB Tasty, I expected a solid A/B testing experience. Based on what I gathered from user reviews and their documentation, the platform seems to live up to that expectation.

What really stood out is how accessible it appears to be. Many reviewers mentioned that even non-technical teams are able to launch experiments quickly without relying too much on developers. The interface is often described as clean, intuitive, and easy to navigate, which makes a big difference when you’re trying to move fast.

Between the visual editor, personalization engine, and test setup tools, it looks like the platform is built for fast iteration and idea validation, especially when optimizing site experiences or conversion paths.

There are a few recurring downsides I noticed as well. Some users mentioned that advanced features can take more time to implement or may require technical support.

A few reviewers also mentioned that it can feel a bit slow at times. It’s not a major issue, but it’s something I’d keep in mind if I were managing a fast-paced testing schedule or trying to roll out changes quickly.

From what I’ve seen, AB Tasty strikes a good balance between being user-friendly and feature-rich. It seems like a strong choice for digital marketing teams that want to run meaningful experiments without getting stuck in complicated setup processes. 

If you’re looking for a tool that empowers marketers and product managers to take the lead on testing, this one feels like a smart pick.

What I dislike about AB Tasty:

• A few users did mention that the tool can be a bit slow at times. It’s not a widespread or major concern from what I saw, but just something to keep in mind. 
• Some reviewers pointed out that while basic tests are quick to launch, the more advanced features can take time to implement and might still need technical support.

What G2 users dislike about AB Tasty: 

“Sometimes the Editor can be slow and depending on the technical structure, a bit painful.” 

– AB Tasty Review, Thomas C, Senior Consultant, CRO and Web Analytics. 

I’ve known about Netcore for a while, but taking a closer look at its A/B testing capabilities gave me a new appreciation for how versatile the platform really is, especially when it comes to orchestrating personalized customer journeys across channels.

From what I gathered in the demo and reviews, it’s built right into the journey builder, so testing different variants across email, SMS, in-app nudges, or push notifications is easy to set up and manage.

I walked through the journey builder via an interactive demo that set up an A/B test using different nudge variants, and found the experience pretty intuitive. Choosing between rollout options, whether all at once or in phases, was simple, and it felt like something I could hand off to a marketer without needing constant dev support.

The platform seems to shine most when it comes to accessibility. Multiple G2 reviewers pointed out how smooth their experience has been when launching campaigns, which definitely tracks with what I saw in the demo. 

Reviewers also mentioned it helps uncover customer behavior trends, which makes sense given how connected the platform is across channels.

That said, not everything is perfect. I saw a few users mentioning that the platform can feel laggy at times, particularly when working with large datasets or switching between modules. There were also a couple of mentions about reporting being harder to navigate, especially when tracking engagement across multiple channels.

Overall though, Netcore comes across as a strong contender for teams that want to move quickly and test messaging at scale. It’s built with customer engagement in mind, in my opinion and it feels like a good fit for CRM teams, growth marketers, and product-led organizations looking to optimize experiences without needing to build custom testing flows from scratch.

If I were running in-app experiments or nudges across channels, I’d seriously consider giving this one a go. 

What I dislike about Netcore Customer Engagement and Experience Platform:

• Some users pointed out that parts of the platform can feel a bit laggy, especially when handling large data sets. I’d probably find that frustrating if I were working under tight deadlines.
• I also noticed a few users mentioning that there’s a bit of a learning curve. That’s pretty common with platforms like this, but it’s still something I’d keep in mind going in.

What G2 users dislike about Netcore Customer Engagement and Experience Platform: 

“The thing I dislike about Netcore is that it’s a bit difficult to understand at first. And there is no user guide video. If we want to create or use any analytics, we need to connect with the POC. If there are any tutorial videos, it will be better for new users.”

– Netcore Customer Engagement and Experience Platform Review, Ganavi K, Online Marketing Executive. 

I’ve known LaunchDarkly primarily as a feature management and feature flagging platform, not your typical A/B testing tool. But after looking into it more closely and digging through user reviews, it’s clear that it plays a valuable role in experimentation, just in a different way than most visual or marketer-friendly platforms.

It’s geared more toward development and product teams who want to test, release, and roll back features without redeploying code.

What stood out most to me from the reviews is how widely appreciated LaunchDarkly is for helping teams safely ship new features and run backend experiments.

I could see reviewers consistently talking about using feature flags to control releases and run A/B tests by segmenting users or gradually rolling out new functionality. The platform gives teams control over who sees what and when, which makes it ideal for testing changes in real production environments without risking a full release.

The big win here seems to be around flexibility and safety. One user described it as their go-to for selective releases and targeted rollouts. Another mentioned that it helps them run experiments at the infrastructure level, where performance, functionality, or user experience might vary. For me, this means we’re not dragging and dropping elements on a landing page. We’re flipping switches under the hood with precision.

 But, a few reviewers did mention some friction. The interface can get a little overwhelming when you’re managing a large number of feature flags, especially across different teams or environments. Some users also noted that the UI update rolled out last year took some time to adjust to. It wasn’t a dealbreaker, but for teams juggling a complex flag strategy, it might take a bit of upfront effort to get fully comfortable.

Overall, LaunchDarkly feels like the right fit for dev-heavy teams that treat experimentation as part of the release pipeline, in my opinion.

If you’re a product manager, engineer, or growth team working closely with code, it’s a powerful way to run safe, targeted experiments. Just know that it’s not designed for quick visual tweaks or content-based split tests. It’s more about managing risk and testing logic at scale.

What I dislike about LaunchDarkly:

• Managing a large number of feature flags can feel messy at times. I saw a few users mention that it gets confusing to track everything when you’re working across multiple projects or environments.
• The UI redesign from last year came up a few times. Some folks said it took a while to get used to, especially if you were already familiar with the older layout. It sounds like a small adjustment, but still something I’d want to be aware of.

What G2 users dislike about LaunchDarkly: 

“”The new UI that LaunchDarkly recently launched for feature flagging is not something that I like, I had built muscle memory for using the tool hence it has become a little tough for me to use it.”

– LaunchDarkly Review, Aravind K, Senior Software Engineer.  

I’ve always thought of AppMetrica as more of a mobile analytics and attribution tool, but after reading through reviews and looking deeper into what it offers, I realized it’s actually capable of much more.

From what I could gather, it’s not a visual A/B testing platform in the traditional sense, but for data-driven product teams, it offers the kind of backend insight you need to understand what’s working and why.

What stood out most to me from user reviews is the ease of integration, the detailed technical documentation, and the ability to slice data quickly with flexible filters.

The A/B testing features are praised for being straightforward, especially when testing mobile app flows or messaging variants. A few users highlighted how valuable it is for monitoring errors, tracking installs, and analyzing in-app events in real time, which makes experimentation feel much more responsive and actionable.

Of course, no tool is perfect. I saw some reviewers note limitations, like inadequate reporting functionalities. A couple of developers mentioned that the UI can be slightly clunky at times, especially when working with larger datasets or trying to drill down into specific performance metrics. These aren’t huge issues, but I’d definitely want to keep en eye out for.

If I were running growth experiments or behavioral testing within a mobile app, AppMetrica would definitely be on my radar. It’s especially useful for product teams and mobile marketers who care more about what happens under the hood than flashy UI tools

What I dislike about AppMetrica:

• I’ve noticed that users often call out limited reporting functionalities, which could be a challenge for certain use cases.
• Some reviewers mentioned that the interface can feel a little clunky when you’re working with a lot of data or trying to dig into deeper metrics. I could see that slowing things down.

What G2 users dislike about AppMetrica: 

“Being a developer and App metrica provides limited customization in reports and also in ad tracking limitations.”

– AppMetrica Review, Mani M, Developer. 

I’ve always seen MoEngage as one of those solid, go-to platforms when it comes to customer engagement and automation, especially if you’re looking to work across channels like push, email, in-app, and SMS. It’s designed for scale, and it shows.

You get real-time analytics, user segmentation, campaign automation, and the ability to run A/B tests across your entire funnel. What stood out to me is how often reviewers mention how intuitive the platform feels once you’re inside. A lot of people talked about how easy it is to create and segment campaigns, even for more complex workflows, and how quickly they were able to push live experiments with personalized variants.

MoEngage’s A/B testing features really come to life when paired with its segmentation tools, from what I gathered. The platform gives you fast feedback on what’s working.

Reviewers highlighted how useful it is to test across multiple audience segments without having to set up separate campaigns. And since everything sits on top of a unified customer view, the test results feel tightly connected to actual behavior, not just vanity metrics.

That said, a few reviewers did mention that it can be a little tricky to implement at first, especially if you’re comparing it to lighter tools. One user also mentioned pricing being a bit on the higher side, which tracks with the level of capability you’re getting. But overall, complaints were rare and I’d say things to be aware of rather than major red flags.

If I were on a CRM or lifecycle marketing team looking to run cross-channel experiments with deep behavioral insights, MoEngage would absolutely be on my shortlist.

What I dislike about MoEngage:

• A few users mentioned that the initial setup can be a bit tricky. I get the sense that while the platform is powerful, it might take some time to get comfortable with everything if you’re new to it.
• There were also some comments about pricing being a little steep. It’s something I’d definitely want to factor in before going all in.

What G2 users dislike about MoEngage: 

“While MoEngage is a powerful platform, there are a few areas that could use improvement. The platform’s reporting capabilities, although robust, could benefit from more customization options to better tailor insights to our specific needs. Occasionally, the system can be a bit slow when handling large datasets, which can be frustrating when working under tight deadlines.

Additionally, while the platform is generally intuitive, there is a slight learning curve for new users when navigating more advanced features. However, these issues are relatively minor compared to the overall benefits the platform provides.“

– MoEngage Review, Nabeel J, Client Engagement Manager.

Need more help? Explore the best conversion rate optimization tools on G2 to find the right platform for your goals.