Best A/B Testing Tools in 2026
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Featured A/B Testing Tools At A Glance
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Buyer's Guide: A/B Testing
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of VWO Testing, enabling quick starts and efficient implementation of testing ideas.
Users appreciate the responsive customer support of VWO Testing, which enhances the overall testing experience.
Users appreciate the fast and user-friendly A/B testing features of VWO, enabling effective testing and data-driven decisions.
Users note missing features like scrollmaps and more templates, limiting ease for non-technical users in complex tests.
Users find the platform has limited features, requiring developer help for advanced experiments and custom coding.
Users find the limited features and integrations of VWO Testing restrictive, impacting test effectiveness and flexibility.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of AB Tasty, highlighting its intuitive interface and clear reporting.
Users value the responsive customer support of AB Tasty, enhancing their testing experience with quick assistance.
Users value the outstanding customer support from AB Tasty, enhancing their overall experience and problem-solving abilities.
Users face testing difficulties due to QA bugs and challenges in identifying optimal test versions.
Users notice that certain features lack clarity, making them difficult to understand and utilize effectively.
Users find difficulties in learning AB Tasty, especially due to technical requirements and limited guidance for tests.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of Statsig, enabling quick and confident decision-making through simple experiment execution.
Users value the rapid experimentation capabilities of Statsig, enabling quick decisions and efficient feature performance analysis.
Users value the ease of running experiments and the depth of analytics provided by Statsig.
Users experience a steep learning curve with Statsig's advanced analytics and feature complexities that require time to master.
Users find the steep learning curve for advanced analytics in Statsig challenging, requiring extra effort to master.
Users note the absence of comprehensive features for various experiments, impacting the overall versatility of Statsig.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of Netcore's platform, enabling seamless campaign creation and customer engagement.
Users value the responsive support from Netcore, ensuring effective use and quick issue resolution for their needs.
Users commend the exceptional customer support of Netcore, emphasizing their dedication to effective integration and ongoing assistance.
Users find missing features problematic, highlighting issues with campaign uploads and the repetitive content entry for notifications.
Users experience slow performance during segmentation and report generation, impacting their overall efficiency with the platform.
Users find the learning curve challenging, especially during initial setup and when navigating advanced features.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users find LaunchDarkly to be intuitive and easy to navigate, greatly enhancing their workflow and collaboration.
Users praise the ease of managing feature flags with LaunchDarkly, enhancing deployment efficiency and flexibility.
Users value the intuitive feature management of LaunchDarkly, enabling safe and efficient application updates without downtime.
Users struggle with feature flag management issues, finding the process tedious and time-consuming across multiple environments.
Users face inconsistencies and limitations in feature flags management, affecting randomization and overall ease of use.
Users desire missing features like simultaneous editing of environments and better integration with GitHub for improved usability.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users commend the ease of use in Bloomreach, facilitating smooth integration and efficient campaign management.
Users commend the exceptional customer support from Bloomreach, particularly appreciating the quick responses and professional assistance.
Users appreciate the exceptional support from Bloomreach, noting quick responses and helpful assistance that enhance their experience.
Users find the learning curve steep, but acknowledge that the benefits justify the initial effort.
Users indicate limited features in Bloomreach, particularly in analytics and campaign setup, affecting overall usability.
Users find Bloomreach has a difficult learning curve, needing extensive training to navigate its features effectively.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of MoEngage, finding it simple to navigate and integrate with tools.
Users appreciate the robust analytics and automation features of MoEngage, enhancing user engagement and campaign effectiveness.
Users appreciate the responsive support and innovative features of MoEngage, enhancing user engagement and campaign effectiveness.
Users feel MoEngage lacks essential features such as AI tools, autosave, and more campaign customizations.
Users find the learning curve steep, making it challenging for beginners to get accustomed to MoEngage.
Users find MoEngage to be expensive, complicating the pricing structure with high-tier plans for essential features.
This description is provided by the seller.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users love the ease of use of EngageBay, appreciating its intuitive interface and time-saving automation tools.
Users value the effortless workflows and responsive support in EngageBay, enhancing their marketing efficiency and customization.
Users appreciate the excellent customer support of EngageBay, always ready to assist and enhance their experience.
Users find the missing features of EngageBay disappointing, especially regarding integrations and advanced data analysis.
Users find the limited features of EngageBay lack advanced analytics and modern design in templates.
Users experience slow loading during bulk actions and campaign stats, impacting overall performance and usability.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of PostHog, finding the intuitive interface simplifies analytics and fosters engagement.
Users appreciate the easy setup of PostHog, allowing them to quickly integrate and start using the platform.
Users value the powerful analytics in PostHog, enjoying its simplicity and clean interface for tracking traffic.
Users experience a steep learning curve with PostHog, finding it challenging to navigate its features effectively.
Users face a steep learning curve with PostHog, finding it challenging to navigate its complex features and data.
Users find the missing features in PostHog limiting, particularly the lack of real-time session replay functionality.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users value the ease of use of Webflow, appreciating its intuitive interface and powerful CMS features.
Users value the design flexibility of Webflow, enabling quick, customizable site development without relying on plugins.
Users praise the speed and ease of building with Webflow, allowing for rapid development and client autonomy.
Users find the learning curve steep, needing guidance to navigate Webflow's complex features and design options.
Users note limited features in Webflow, affecting complex content handling and e-commerce capabilities.
Users note missing features in Webflow, including CMS nesting limits and slow performance on large websites.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use in AppMetrica, making tracking and managing analytics straightforward and efficient.
Users appreciate the easy integrations with AppMetrica, allowing for seamless setup and efficient event tracking.
Users appreciate the user-friendly interface and comprehensive analytics of AppMetrica, making data interpretation effortless.
Users find missing features in AppMetrica, particularly related to ad tracking and report customization limits.
Users face challenges with reporting issues, citing lack of customization and slow performance with large datasets.
Users find the inadequate reporting in AppMetrica limits insights on ROAS and ad spend significantly.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users value the helpful customer support at Kameleoon, enhancing their experience with quick and effective assistance.
Users find Kameleoon to be a user-friendly platform, with excellent support facilitating easy implementation and use.
Users value the ease of use and flexibility of Kameleoon, facilitating efficient A/B testing and analysis.
Users find that developer dependency complicates Kameleoon, making A/B test setup challenging without technical skills.
Users find the difficult learning curve for Kameleoon challenging, requiring advanced technical skills for effective use.
Users find the learning curve steep, making it challenging to utilize Kameleoon's full potential effectively.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users praise the ease of use of Optimizely Web Experimentation, simplifying experiment management and user understanding.
Users find the ease of launching experiments with Optimizely Web Experimentation straightforward, promoting continuous customer experience improvements.
Users value the customizable personalized UX and strong analytics in Optimizely Web Experimentation for enhancing user understanding.
Users experience a challenging learning curve with Optimizely Web Experimentation, requiring prior knowledge for effective use.
Users find Optimizely Web Experimentation to have difficult learning curves, requiring prior experience for effective use.
Users find the platform difficult to use, especially for newcomers lacking prior experience or adequate documentation.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the swift and insightful customer support offered by Omniconvert, addressing issues effectively and promptly.
Users find Omniconvert's ease of use exceptional, allowing smooth A/B testing, personalization, and effective support.
Users find the helpfulness of Omniconvert's insights crucial for understanding audience engagement and enhancing website effectiveness.
Users find a steep learning curve challenging, especially those unfamiliar with digital marketing and analytics.
Users note a significant developer dependency for complex A/B tests, which can hinder easier use of the tool.
Users note the limited data analysis capabilities of Omniconvert, restricting insights and functionality for complex reporting needs.
Learn More About A/B Testing Tools
What are A/B Testing Tools?
A/B testing tools measure how customers interact with a brand’s digital creative content. Through conducting tests on customer interaction, companies can extract real data and metrics to optimize products.
A/B testing tools allow marketers, advertisers, and web developers to test different versions of digital content to find the customer-preferred digital experience and personalization for various personas. Website visitors subconsciously react to every element on a web page—such as the color and aggressiveness of a live chat pop-up, the phrasing of a call-to-action (CTA) button, or the positioning of the search bar. A/B testing solutions give web content creators the tools to deploy the tests, determine the target audience, and analyze the experiment results. These tools are used to improve conversion rate and bounce rates, as well as the overall success of a website.
The main way that digital creativity is tested is through a rotating A/B test. This is done by using two iterations of a design and seeing which one gets the highest click-through rate. A company can conduct a test with version A for 500 users from the target audience and then another test on version B for 500 users with a completely different variant. The company can then see which one gets the highest click-through rate and, ultimately, determine which variant should be used.
A/B testing can offer the following use cases to improve a company’s performance:
- Create the most successful version of the e-commerce site, especially the home page and calls-to-action (CTA)
- Increase website traffic and reduce bounce rates
- Gain insight into user behavior
- Analyze any and all test segments to discover key opportunities
- Increase conversion rates and e-commerce profits
- Tailor e-commerce content and goals through continuous testing
- Determine the consumer impact of differing designs and formats on website optimization
What Types of A/B Testing Tools Exist?
Proprietary A/B testing
Proprietary solutions will require time and resources but will adapt to very specific case studies and customizations. Proprietary products also provide customer support and streamline the process of setting up, tracking, and analyzing tests.
Open-source A/B testing
Open-source solutions come with a very small price tag (if any at all). While open-source software doesn’t offer the same kinds of reports and finetuned features as proprietary solutions, it gives access to an entire community of programmers and developers with bountiful testing experience.
What are the Common Features of A/B Testing Tools?
A/B/n testing: This type of split testing takes A/B testing to the next level by analyzing multiple versions of a creative product, one variable at a time. This allows a company to determine the best variation across a multitude of tests that measure KPIs on several iterations. The analytics tools used for a simple A/B test will also measure the same KPIs for the multiple variations.
Multivariate testing: Multivariate testing uses the same methods as A/B testing, but instead of testing only two variables, it tests a higher number. This is essentially like having two tests combined into one. This is a way to conduct test combinations. For example, one multivariate test can test whether the combination of a blue header and white text works better than a red header with grey text. Then, it can test what happens when the combination is flipped—whether a blue header would work better with grey text or a red header would work better with white text. A successfully performed multivariate test would then show which combination had the highest click-through rate. The major benefit of multivariate testing is saving time and ensuring that the best combination with the highest conversion rate is being presented on the website.
Multipage funnel testing: Multipage funnel testing is a way to test variations of several consecutive website pages. This is a great way to see if customers are finding what they’re looking for in the quickest way possible. The use case of multipage funnel testing can be easily applicable to retail, e-commerce, and any other website where the company is selling a product. This can test how quickly a user went through the buyer funnel from initial interest all the way to the final goal of purchasing the product. A multipage funnel test can help test the most effective way to convert customer interest into a customer purchase.
Audience targeting: Audience targeting provides the ability to choose where the test will run and for whom. A/B test can be conducted to see which visitor conditions to show the experiment to and which specific URLs the experiment should run on the site. To increase engagement from mobile users who are using Google Chrome, audience targeting can conduct the A/B test on these specific users. This helps increase engagement with a particular audience.
Funnel analysis: Funnel analysis allows companies to analyze the data in the buyer's journey and make necessary changes to facilitate conversion rate optimization. A/B test with funnel analysis helps understand if things such as registration pages or website subscription options are driving more people to convert or if they’re turning customers away. This allows the tester to see if they need to make adjustments to certain stages to increase engagement.
Heat maps: Heat maps are a very effective tool for visualizing which links users click on when they visit a website. Heat maps applied to an A/B test will show certain links on a webpage in either blue, yellow, or red to indicate how often those links are clicked. This way, testers can analyze how to effectively set up a page and ensure that the most important links are in spots that are being clicked on the most.
Surveys: A valuable feature in A/B testing software is surveys. This enables companies to directly ask users which type of variant they prefer through a variety of different questions. The data from the survey can then be translated into graphs or charts, which makes it easier for the tester to visualize the results. This can help companies target which specific variants are working well and which variants are failing. It also may give companies more detail on where to head in order to improve their designs by asking questions that make users explain in detail rather than asking simple yes or no questions.
Statistical relevance analysis: Statistical relevance analysis helps confirm if an A/B test has a large enough sample size. Users can track their data in real time and see if the test needs more time or if there’s enough traffic to confirm that one variant performed better than another. This helps users stop the test and not use more time on it than needed. Achieving the right sample size ensures the statistical significance of test results is achieved during the testing process.
Test scheduling: A/B testing platforms allow users to schedule tests in advance to ensure that they are conducted during a time when the website is expected to get a lot of traffic.
What are the Benefits of A/B Testing Tools?
A/B testing software is an essential tool for optimization and growth. The best way to improve a product's performance is by continuously conducting new trials to see what works and what doesn't. The following are reasons why vendors benefit from using these tools.
Higher conversion rates: Companies can conduct a test to see what will produce the best conversion rate. Rotating A/B tests can give content creators an accurate representation of how quickly users can find what they’re looking for on a website. This can lead to customers purchasing more quickly or subscribing to newsletters more frequently, leading to greater conversions and higher revenue for the company.
Real-time testing: A/B testing can save companies plenty of time by testing variations in real time. Instead of having to pull people aside to conduct trials, rotating tests are conducted on users who are currently visiting the website.
Genuine testing: Another major benefit of A/B testing is genuine testing. Tests are conducted on actual visitors who are coming to the website, which means that the results are not skewed by incentives or preconceived knowledge within a trial. Since the testing is done on completely random visitors, the company will get the most accurate picture of how customers are behaving in real time.
Reduced bounce rate: One of the main goals of A/B testing tools is to test ways to keep people on a website for as long as possible. This can be done by incorporating different page layouts, links that lead back to the website, and CTA buttons. High bounce rates are the main reason for low conversion rates, so testing ways to reduce the bounce rate of a landing page is a critical way to keep customers engaged.
Who Uses A/B Testing Tools?
While A/B testing tools and personalization software generally integrate with systems that work on both the front end and back end of websites, the software isn’t just for technical website developers who specialize in coding. Users with varying skill sets can use the software to enhance their currently existing websites. Appropriately, A/B testing software vendors clearly advertise either their ease of use (embedding just one line of code) or the flexibility with which their tests can be conducted (conducting split-level experiments). Here are some ways various team members can use these tools to enhance performance:
Digital marketing teams: Digital marketing teams can utilize A/B testing software in a variety of ways. They can measure the efficacy of CTAs, headlines, images, and copy to see which variations will have higher click-through rates with users. In addition, they can measure the frequency of cart abandonment to test how likely a customer is to convert into a sale.
Design teams: Perfecting the design of a website is an ongoing process. Design teams can utilize A/B testing to optimize a website’s performance and quality of the user experience by making sure visitors are staying on for an ample amount of time. They can do this by testing how quickly people find what they’re looking for, where to place links on a page to get the most clicks, and other web layout adjustments in order to increase customer engagement.
Research and development teams: Research teams that focus on optimizing website performance can use surveys within A/B testing tools to see which variants appeal to more users. They can ask about customer desires, demographics, and any other details that they can extract to improve their product and website.
Software Related to A/B Testing Tools
A/B testing can be supplemented with a wide variety of other software that also test for conversion rates and lead generation:
Email marketing software: Email marketing software includes A/B testing features, which can be used to test which of two email campaign options will be more successful. During this process, two variations of an email campaign are sent out to two different pools of recipients. Whichever pool has the higher click rate on the email campaign will indicate which one will be more successful. The results can indicate the open rate, click-through rate, and the number of subscribers that were influenced by the email campaign. This is a great tool to guarantee that the marketing campaign is effective and that it will generate more revenue and happier customers.
Web content management software: Web content management (WCM) systems allow users to create, edit, and publish digital content such as text, embedded audio and video files, and interactive graphics for websites. WCM tools offer an assortment of templated web pages, from which site administrators can browse and choose. Since the main goal of web content management is to maximize customer engagement, it is a great software to integrate with A/B testing. A/B tests can be conducted on certain web content and provide higher conversion rates.
Digital analytics software: Digital analytics software tracks website visitors and measures web traffic. Marketers, web developers, and analysts use digital analytics suites to report on the effectiveness and popularity of web experiences and to determine how visitors are finding and interacting with their sites. Digital analytics supplement A/B testing by showing companies which areas need improvement on their website. This can indicate what areas need help from a test to determine what will improve customer engagement.
Heatmap tools: Marketers and web developers use heat maps and in-page analytics to visualize where on a web page visitors click, hover, and scroll. Heat maps can be integrated with A/B testing software to effectively set up a page and ensure that the most important links are in spots that are being clicked on the most.
Challenges with A/B Testing Tools
Ensuring random testing: It is difficult to ensure that a test is truly random. For example, if a company wanted to conduct an A/B test on page traffic on any random day, it might be difficult to assess whether visitors were less likely to come on that day. If the weather was nice or it was too close to the holidays, people might be less likely to be on their computers, which can skew the test's results.
Testing too many variables: Product teams are constantly trying to reimagine product pages with new designs to increase sales. However, overtesting can be a problem, especially when users are more familiar with one design over another. This can lead product teams to be overfocused on certain website designs that will most likely not have an effect on the user. The best way to avoid this issue is to focus on major design changes, such as page layouts, rather than the font size of certain words.
Small sample sizes: Often, A/B tests are conducted on too small a sample. This means that there is not enough data to confidently say that a variation is more successful than another variation because not enough people were tested. The best way to avoid this issue is to conduct a test that is concluded when the test reaches 95% confidence. While this may take some time, it can ensure that it was conducted effectively.
How to Buy A/B Testing Tools and Software
Requirements Gathering (RFI/RFP) for A/B Testing Tools
When searching for the right A/B testing tool, it’s important to create a long list based on products that contain some of the most necessary features for an effective experiment. After the available pool has been segmented based on crucial features, one can then sort based on nice-to-haves, bells and whistles, and industry-specific software requirements.
Compare A/B Testing Software Products
Create a long list
In order to create a long list, buyers must ensure the products being considered meet these core criteria:
- The software is compatible with one’s technology and computer programs
- Cloud storage is available for experimental data
- The software offers the scalability needed to perform experiments with a certain n-size
- Cost aligns with budget
Create a short list
Once a long list based on core features is created, a short list should be further narrowed based on nice-to-haves and bells and whistles:
- What you see is what you get (WYSIWYG) editing
- Little to no coding options for businesses that don’t have employees with a computer science background
- Multivariate testing capacities should experiment with more than one variable need to be tested simultaneously
- Mobile app testing capabilities if a business has mobile content
Conduct demos
Buyers must schedule calls with the vendors on the short list to ensure their product is the right fit. The most foolproof way to make the right decision is to actually test out the software. It is important to ask vendors about how their product addresses the business’ most pressing needs.
Selection of A/B Testing Tools
Choose a selection team
The selection team should include the CEO and other executives from finance, marketing, and IT. The CEO will be there to represent the whole company and its business objectives. Finance will be able to represent the company and IT will determine if the product fits well into existing tech stacks and company technology. Most importantly, representatives from marketing will be able to speak fluently on the goals of A/B testing and company needs with software, since the marketing team will be the end user for these tools.
Negotiation
A/B testing software vendors will be bringing their strongest team to seal the deal with a potential client. Therefore, it’s important to come to the negotiation process with questions on certain key features one needs. These include (but are not limited to) multivariate testing and WYSIWYG capabilities, how much coding experience is needed to use the interface, and AI or machine learning. Buyers must ask questions about the total costs and fees associated with purchasing, implementing, and using the product. In order to prevent surprises later, it is crucial to ensure the terms and conditions are read in full and discussed.
Final decision
It could be useful to create a scoring template that measures the various features mentioned in the long and short list, as well as notes from calls between the client and vendor.
A/B Testing Tools Trends
Calls-to-action (CTA): CTAs have become the most popular test to conduct within A/B testing. Calls to action are phrases that try to induce urgency in the buyer, like a certain offering will expire soon or must be purchased immediately. More companies are using CTA links, as they help with end-of-funnel marketing and can lead to a sale in the quickest way possible. Common A/B tests to run on a CTA button include bigger text size, brighter button colors, and any other adjustments to make the button more visually appealing or engaging.
Mobile A/B testing: These tests are seeing a huge spike in growth as more users are shifting away from desktops and onto their phones. Mobile A/B testing trends can help companies analyze how their mobile app’s layout is performing and how to make mobile purchases for consumers as simple as possible. Since the screen size is so drastic from the desktop to the mobile screen, it’s important to make necessary changes so users can see product offerings on a smaller screen.
Website personalization: A/B tests enable users to run tests based on customers’ personal information. Companies can utilize big data to offer tailored content (based on assumptions about the way a visitor will behave) to invoke the feeling of a personalized shopping or browsing experience. Testers can run A/B tests to examine if the tailored content leads to more conversions or engagement.
