Best A/B Testing Software & Tools

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Eppo is an A/B testing platform for product teams, offering centralized reporting, feature flagging, and infrastructure integration for reliable metrics boost.
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OptiMonk is a tool for marketers, offering popups, website personalisation, and A/B testing for increased sales. It features AI-driven optimization and flexible pricing.
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Convertful is a comprehensive tool converting visitors into leads, sales with features like pop-ups, scroll boxes, and integration with popular apps.
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Price: From 49.00 $ / Monat
Rewardful is a tool for SaaS companies to increase revenue through referral and affiliate programs. Features include tracking referrals, discounts, and commissions.
Price: From 299.00 € / Monat
ConversionBuddy optimizes landing pages for product ads, enhances sales, promotes additional deals, and utilizes an easy, fair pricing model.
Zoho PageSense
Price: From 20.00 € / Monat
Zoho PageSense offers heatmap monitoring for website optimisation, funnel analysis for customer interaction, and facilitates on-site surveys.
Price: From 5.00 $ / Monat
Codesphere is a cloud platform for collective code reviews and deployments. Easy integrations and no DevOps experience required. Supports varied release methods.
Price: From 0.00 €
EngageBay is an all-in-one tool for startups, offering integrated marketing, sales, and support software, including CRM, sales automation, and free live chat.
Price: From 0.00 € uses machine learning for efficient, stable automated software test cases, reducing the need for regular maintenance with each code change.
Price: From 0.00 €
Iridion is a comprehensive conversion optimization tool with a 7-level analysis for product enhancement.
Price: From 29.00 $ / Monat
Crazyegg uses heatmap technology to visualize customer data, identifying issues such as form errors and navigation confusion. Ideal for audience-targeted analysis.
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SiteSpect offers A/B testing, insights, personalization of customer journey, multivariate testing, and website optimization.
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Yieldify is an AI-supported platform optimizing customer journeys through personalization, testing and measurement.
Price: From 320.00 $ / Monat
Omniconvert drives growth for eCommerce firms through advanced segment algorithms, AB testing, web personalization, and customer research.
Price: From 0.00 €
XCAMPAIGN is an email marketing tool with robust analytics, personalization, and automation features.

More about Best A/B Testing Software & Tools

A/B Testing Tools Definition: What is an A/B Tool and Why is A/B Testing Software Needed?

Just like physical goods, digital products like websites and apps are not necessarily perfect immediately after they are manufactured. Furthermore, they do not remain ideally functional in the long term without further tweaks. Typical examples of optimization needs are as follows:

  • Individual pages or specific features on the pages do not function as desired or do not deliver the expected performances immediately after launch.
  • Long-term deficits in the usefulness of certain pages and their content or special functions emerge.

When such a case or a similar one occurs, it is initially necessary to estimate what might be causing the difficulties. Often, texts, buttons and/or layouts that are unfavorable or no longer contemporary for the respective target group are reasons why some areas of websites or apps no longer perform as originally intended.

This is where A/B testing tools come into play. As the name suggests, they support users in carrying out and evaluating so-called A/B tests.

These are a type of experimental method, in which website visitors or app users are presented with two or more separate versions of a page. These variants usually only deviate slightly from each other – typically in one specific point. The difference ideally affects the exact point most likely responsible for the desired performance not being achieved.

In A/B tests, the "A" refers to the original version, i.e., the one to be tested. The "B", on the other hand, stands for the optimized variant, i.e., the version with the changed variable. If an increase in performance compared to the A version is registered with the adjusted B version, this is a clear indication that the B variant is more appropriate.

In this procedure, an A/B testing tool primarily takes on the tasks of tracking users and analyzing performance. This is particularly based on user interaction with the digital product and the specification of specific objectives and KPIs within the respective testing software. The A/B program finally delivers concrete data on the basis of which the benefit of one or more subsequent adjustments can be demonstrated. Website or app operators as well as sellers of corresponding products can thus optimize their solutions based on data.

By the way: Since A/B testing tools always examine separate variants of pages, they are also called split testing software (especially in the English-speaking world).

How do A/B Testing Tools Work?

Different objectives and respective services or areas of websites or apps can be examined using A/B testing tools. Typical goals are more conversions (purchases, registrations, contact initiation, etc.), longer dwell time and a lower bounce rate.

Achieving these concerns can be checked and subsequently optimized via the A/B tests of button layouts, call-to-actions, headlines, form structures, checkout processes and other elements of websites or apps.

The strategic approach varies from context to context. However, the pure software-supported A/B test on websites or in apps almost always works according to the same pattern.

  1. Set up a campaign: Before a testing tool is used, the initial situation/problem is usually identified, the objective and KPIs defined and the improvement measures decided. Now a campaign needs to be set up in the A/B testing tool. Depending on the A/B test provider, code snippets need to be placed at the right locations on the page variants, or the changes need to be set in a special editor. Measurement is based on the KPIs, i.e., metrics on the respective objectives. In addition, segmentation by mobile A/B test and desktop A/B test is frequently made. A distinction of visitors according to their origin is also typical.

  2. Let the A/B testing tool work: Depending on how much traffic is needed for the test, significant results are available sooner or later. It is possible to see a first tendency after just a few sessions. Users have the opportunity to specify exactly how much traffic should be used for the test in the settings of their AB testing tool. This setting is very important as the test can also turn out negatively. If this happens with a very business-critical application, only a portion of the traffic was "wasted" for the test.

  3. Evaluate results: Once the test is finished, a definite statement can be made on the performance or attainment of the respective goal based on the previously set KPIs. The central question here is whether the change had a positive effect or not?

  4. After the test is before the test: If positive effects are suggested by the data, the change can be finally implemented. Sometimes, however, the A variant is better than the B variant. Then the latter should be discarded. In both cases, another test usually follows quickly after a test. There is always something to optimize!

What are the Advantages and Disadvantages of Tools for A/B Tests?

A/B testing software is an important tool for optimizations and growth on websites or apps. The best way to improve the performance of a product is to continually conduct new tests to see what works and what doesn't. The following lists the central reasons why website and app providers can greatly benefit from the use of these tools.

  • Higher engagement and conversion rate: Companies can perform A/B testing to find out which orientation of a page yields the best conversion rate and optimal engagement. For example, web designers in e-commerce are able to determine, among other things, how quickly users can find a sought-after product on the relevant website through successive A/B tests. The corresponding data can then be used to optimize a page so that customers purchase more quickly and securely. The engagement and conversion rate can also be factually improved in other areas (contact initiation, downloads, etc.) using A/B testing. This ultimately leads to higher revenues for the company.

  • Testing in real-time: With A/B tests, companies can save a lot of time as they can test variants in real time. Instead of pulling people aside to carry out tests, rotating tests are conducted with actual users who are currently visiting the website or the app.

  • Authentic tests: Another major advantage of A/B tests is that they provide authentic results. The tests are conducted with actual visitors, not with test subjects in a special experimental context. This means that the results are not distorted by a specific situation.

  • Easy analyses: In the past, the metrics for A/B tests were more or less raw numbers. You had to interpret them manually. Today, on the other hand, there are increasingly intelligent split test tools that can remove many manual steps or decisions from their users with statistical engines and best practices.

  • Flexible use: With the help of A/B testing software, users can investigate all sorts of issues or objectives of websites or apps and then initiate data-based optimizations. The conversion rate and the engagement are just two central examples. In addition, bounce rate, shopping cart abandonments, content, lead generation and many other factors can be examined in their individual components. Every element of a page or app can be tested!

Are there any disadvantages associated with tools for A/B testing on websites or apps? As long as a program has been chosen that fits the user's requirements, there should be no drawbacks. However, certain challenges can certainly arise when using a split-test tool. The most common problems are as follows.

  • Testing too many variables: Websites and apps are always supposed to achieve as much as possible as quickly as possible. To get immediate results, those responsible are often tempted to carry out overly complex tests. If too many variables are tested, it is hardly possible to definitively determine which of them particularly influence the result. This problem can best be avoided by focusing on small test steps.

  • Too small sample sizes: A/B tests are often carried out with too small a sample or over too short a period. This means that there is not enough data to safely say that one variant is more successful than another. Simply not enough people have accessed to get reliable facts. Modern A/B testing tools can offer users tips on sensible test periods and volumes.

How to Choose the Right A/B Testing Platform and What to Pay Special Attention to?

There are many different A/B testing solutions on the market that serve very different requirements. To filter out the best testing tool for their purposes, those interested should primarily consider the following factors:

  • The technical know-how: If you want to use an A/B tool, you first have to install it or implement it within a CMS. The question here is whether an IT specialist is needed for this or whether the respective steps can be taken by yourself? If there are no IT experts in the team, one should rather rely on a broad service package for set-up or a solution that is generally easy to start.

  • The capabilities for using the A/B software: Technical resources are one thing, but the analytical abilities of the team (both quantitative and qualitative) should also be taken into account when looking for a suitable A/B testing tool. Inexperienced users can quickly produce errors. Is the team capable of efficiently conducting A/B tests with the targeted tool? If no detailed analytical skills are present, software is needed that takes on as many tasks as possible. Most A/B testing tools do have a built-in statistical analysis, but they often apply very different statistical approaches. Keep in mind that choosing a tool with a less sophisticated statistical calculator can significantly prolong the duration of the tests.

  • The level of support: The less experience there is in the team with A/B testing, the more beneficial it is to rely on a system that offers good support. Those interested should take a close look at what kind of support is offered with the targeted tool. Possibilities include a live customer service via phone or live chat, automated support via chatbot and/or FAQ, classic email support, online tutorials, documentation and/or community support. One should also consider whether the team needs access to CRO experts to accompany the process. It is rather rare that free support is provided by real professionals. Sometimes, even specific A/B test courses are possible.

  • Features: A/B testing always runs according to a similar pattern. Corresponding tools, however, can still bring more or fewer functions to support this process. To identify the most advantageous functions for their own purposes, those interested should consider which means and in which points they want to test or optimize their website or app. The appropriate A/B testing tool is then selected based on these criteria. Modern software for A/B testing on websites or in apps can bring a variety of automations and even artificial intelligence. These enable particularly easy checks. Especially when it comes to selecting the functions, a practical tool test is usually indispensable.

  • Additional tools: An A/B testing tool is sometimes only a part of a more extensive software suite. Indeed, for the efficient optimization of websites or apps, additional programs usually have to be used alongside the software for A/B testing. These are especially heatmap and scroll map tools. To better understand the visitors, a survey tool might also make sense. Often, a tool is needed to analyze the customer journey. An A/B testing tool is not an analysis platform, but an analysis platform can contain a software for A/B tests on website or app pages.

What do A/B Testing Tools Cost?

At the core, the type of program to be used and the functional scope it brings are crucial for the cost of split test software. There are proprietary A/B testing tools and open source solutions on the one hand.

Proprietary programs can often be used quite comfortably. They include – as needed – numerous features and sometimes additional services, which are supposed to make use more convenient and efficient. They also offer specific support. Ideally, the entire process of setting up, monitoring and analyzing tests can be streamlined in a single application using proprietary testing software. But that can also cost a lot. Depending on the functional scope, number of users and test volume, prices are between around 50 and more than 1,000 euros.

Open source A/B testing software usually has a much lower price (if any). In fact, it is sometimes possible to conduct A/B tests free of charge. Such an A/B testing tool often does not offer the same type of reports, finely tuned features or additional services as a proprietary solution. However, users are flexible in reshaping and using such programs. But: Programming knowledge and other deep technical know-how are often required for the efficient operation of such a solution.