A/B testing

Optimize conversion rates with precision A/B testing

Test and compare different web elements to optimize user experience, drive conversions and find out what works best with your audience. No guessing, all tests are supported by statistical data.
No flickering: No flickering that can mess up your website's UX.
Performance: Test without impacting your website's performance.
Audience segmentation: Location, screen size, OS and browser.
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A/B testing

What is A/B testing?

A/B testing by definition is comparing two different versions (A vs. B) to see which one works better. In an A/B test, you change just one small detail on your website. This can be a different copy or an element, like a headline, a button, an image or a video. When people visit your site, they randomly see one of these variants. 

The important part is that version A is not the same as version B, so you can determine which works best for your audience based on A/B testing statistics. It's a simple way to figure out what makes people click or engage more on your website. The A/B test results are supported by real data, which lets you optimize your site and increase conversions easily. 

The ultimate guide to A/B testing in Webflow

Follow this guide and test different versions of your site and discover the best performing ones to improve conversions.

What are the A/B testing benefits?

When it comes to businesses wanting to optimize their website and staying competitive, there are many advantages of A/B testing that you can leverage.

Increased conversions

The cost of getting quality traffic on your website is huge. A/B testing helps you make the most of your existing traffic so you don't have to break the bank. Sometimes even the smallest changes, like a different CTA button, can give you high ROI.

Visitor pain points

Visitors end up on your website to achieve a specific goal. But they might face some common pain points while doing that, leading to bad user experience and low conversion rates. If you run an A/B test, you can quickly fix their pain points.

Reduce bounce rate

The bounce rate can be a result of different things, like too many options to choose from, confusing navigation or complex copy. There's no ultimate solution, but with A/B testing software you can easily find the best combination possible.

Low-risk changes

By A/B testing in Webflow, you can make minor changes instead of redesigning the entire page. A lot of changes at once can be unpredictable, but smaller changes backed by real statistical data will reduce the risk of jeopardizing current conversions.

Data-driven decisions

Since A/B testing is completely data-driven with no room for guessing or gut feelings, you can quickly determine a winner or a loser based on your statistics. By relying on this data, you reduce all risk factors connected to your subjective assessment.

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How to

How to A/B test in Webflow?

The A/B testing framework consists of six crucial steps for a successful A/B test on your website or your app. If you fail to consider them, your A/B test results will not be as accurate.


Before drafting your A/B testing plan, research the performance of your website first. Take a look at the data from analytics tools and determine which pages you’re going to be testing. Check which pages drive the most traffic and where most conversions happen. Prioritize pages with the highest potential or the highest daily traffic, so your A/B tests will be more efficient.


If you don’t clearly specify your goals, you won’t know if your A/B tests are actually working. The hypothesis can be more complex and longer, or a simple one like “Changing the color of my CTA button will increase landing page conversion rate by 2%”. This step also helps in the future when you look back to check what was working better and where you could improve. 

Install Optibase

Since you will be A/B testing in Webflow, there are a lot of options, but only one fully integrates with Webflow. Optibase is a Webflow app that offers a native way to set up A/B tests and split tests in minutes without impacting your website loading performance. Find it on the Webflow Apps marketplace and install it in your Webflow Designer.

Add variants

When you have the A/B testing software installed, it’s time to create a variant based on your hypothesis and A/B test it against the existing version. In Optibase, go to the “Tests” page and create a new variant. You should then connect it to your element in Webflow. This way Optibase will know which HTML element belongs to which variant. 

Run your test

Now that you have your variants set up, you're ready to start A/B testing. But before you do that, consider a few factors for more accurate results. Make sure to run your test for enough time to get accurate data. The average testing time is at least 2 weeks, but you should always adapt it to your goals. Consider using the A/B test duration calculator to plan your experiments.

Analyze results

This is the last step in your A/B testing marketing campaign, but also the most important. A/B testing is designed for continuous iterations based on data to improve your conversion rates. Once your test is finished after a given time, analyze the metrics like percentage increase, confidence level, direct and indirect impact on other metrics and P2BB value.  

Optibase A/B testing features

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Probability to Be Best

With the P2BB metric, you can make better data-driven decisions by identifying the variant most likely to bring optimal results. It's calculated using Bayesian statistics, which considers the observed results and the uncertainty inherent in A/B testing.

Export data

Optibase lets you seamlessly export comprehensive A/B testing data for further in-depth analysis. This feature allows you to import your exported data in other marketing and analytics tools to make informed business decisions together with the team.

Segment audiences

The robust segmentation capabilities, including geolocation, screen size, device type and operating system, let you tailor tests to specific groups of people. It allows you to optimize user experience and conversions based on demographics and behavior.

No flickering

Optibase testing platform ensures a consistent user experience by eliminating flickering, weird redirects and confusion during A/B tests. Seamless performance enhances the reliability of test results and maintains the integrity of your testing environment.

Cross-page testing

For your A/B test results to be as accurate as possible, Optibase tracks tested users across different pages and domains. It ensures that your experimentation data in Webflow is reliable and that nothing is lost, letting you understand user behavior much better.

Integration with Webflow

Optibase is a specialized A/B testing app for Webflow which is uniquely tailored to the needs and requirements of Webflow users. It lets designers and marketing teams with no coding background set up A/B tests in minutes without bothering engineers.
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Frequently asked questions

What is A/B testing?
A/B testing means comparing two different variants (A and B) to see which one performs better. Usually, it means changing one small detail on your website, for example testing a different copy or an element, like a headline, a button, an image or a video. When people visit your website, they randomly see one of these variants.
What is the goal of A/B testing?
The goal of A/B testing is to figure out which version of your website or app performs better based on metrics like user engagement, conversion rates, time spent on site, scroll depth, etc. so you can optimize based on real data.
How to do A/B testing on a website?
To start A/B testing your website, you need to research your site performance and come up with hypotheses, then install the Optibase app, create a variant to test, connect it to a HTML element in Webflow and run your test. Once the test is completed after enough time, analyze the results and iterate as data suggests.
What is a typical use of A/B testing?
A/B testing is commonly used by businesses to optimize their websites or platforms by testing variations of different elements to figure out which one performs better. Some typical scenarios where A/B testing is used are headlines and copy, call-to-action buttons, images and graphics, layout and design, pricing and product features, forms and navigation flows.