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What Are the Benefits of A/B Testing?
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What Are the Benefits of A/B Testing?

A/B testing is an experiment where two different versions of a web page or app are tested on your audience to see which performs the best.

Ann McArthur
Ann McArthur
December 3, 2021

Understanding Split Testing and Why It’s Effective

What Is A/B Testing?

A/B testing, also known as split testing or bucket testing, is an experiment where two different versions of a piece of content are tested on your audience. You create two versions of a web page or mobile app screen, variant A and variant B. The change can be a small headline, button, or a complete redesign of the page. Then, you randomly show one version to the other.

In a split test, You create two versions of a website or app. The change can be a small headline, button, or a complete redesign of the page. Then, you randomly show one version to half your audience and another to the other half. You can also run multivariate tests, also known as A/B/n test to test more than 1 variation.

It doesn’t matter what kind of company you are or what you’re selling — you can use A/B testing to learn more about your audience and make changes so that you’re reaching them in the best way possible.

With the help of a statistical engine, you can measure and collect visitor engagement with each experience. The results can show whether changing the experience had a positive, negative, or neutral effect on visitor behavior.

When Should You Use It?

Testing your website is key to improving it and finding the best path forward. With data-driven decisions, you can be confident that your changes to your website will result in positive changes. Websites need to be tested so optimization and change conversations become more informed and meaningful.

What Are The Benefits?

There are several benefits of A/B testing. A/B testing lets you increase user engagement, reduce bounce rates, increase conversion rates, minimize risk, and effectively create content. Running an A/B test can have significant positive effects on your site or mobile app. The best part is that they’re easy to implement and provide massive returns and valuable learning for your team.

Better User Engagement

A/B testing is a smart way to improve the content on your site and increase engagement. When you analyze the results of a test and use them to inform your decisions moving forward, A/B testing helps you make improvements to your content that drive engagement. For example, you can test the color of a button on your website or mobile app. You can then see which color leads to more clicks. It’s surprising how a small change can have such a high impact on engagement. Once you run the A/B test you can see which one performs better and keep that variation.

A/B testing can be used in many instances. Product developers and designers can use this tool to enhance user experiences through updating specific elements of a page to create a new design variation. User engagement, onboarding, modals, and in-product experiences are all dependent on A/B testing but are only effective when goals are defined ahead of time and hypotheses are tested.

Reduced Bounce Rates

Analytics can tell you what to optimize. They help you identify high traffic areas of your site or app, and low-converting or high-drop off pages that can be improved so you can test new ideas on how to improve the pages.

You want to keep your visitors on your website for as long as possible. You can do this by changing up the copy, images, and blog post headlines. Testing out what works best can help you reduce bounce rates and keep visitors longer.

Increased Conversion Rates

With AB testing, businesses can learn what kind of content is more likely to lead a website visitor to purchase. It’s a great marketing tactic for figuring out what your audience is like and how they prefer to be communicated with.

Testing out different user experience elements through A/B testing is a powerful way for companies to make changes that lead to positive results and learn what's going to be the most effective. For example, a website might change the wording on a sign-up button from "sign up now" to "sign up now!" and then compare which one gets more clicks to know which one the customer prefers.

Minimized Risks

A/B tests allow you to minimize risks. If you’re not sure how a new feature or element on your site will perform you can conduct an A/B test to see how it will affect your system and how users will react to it. By using a feature flag to conduct your A/B test you can quickly roll back the code if it has a large negative impact.

Effective Content

A/B testing can be used to improve any given experience over time, whether it is trying to improve the conversion rate or answering a single question. A/B testing has become a low-risk and high-reward tool for companies to use. It can help you extract the maximum amount of value from your production tests and increase your return on investment.

How to Implement a Test

Feature flags allow you to run A/B tests on your app or website by turning features on and off. They're simple to create and yet very helpful when running experiments.

Sometimes A/B tests can be tricky. One way to ensure they're successful is to change only one element of each version of the test. You could use a different image but keep the caption and URL the same, or use a different headline but keep the image and body copy the same. To identify which changes will truly improve customer experience, it is important to test one element at a time. This will help pinpoint the changes that actually affect user behavior relative to those that don't. Over time, by combining the effects of different winning changes from experiments, brands can demonstrate how new experiences are measurably better than old ones.

Next, you want to divide traffic evenly and randomly to the 2 different variations. This ensures that there’s no bias on who views each variation. You also want the variations to be tested at the same time. Your test might not produce accurate results if you change the variable you're testing at different points in time. For example, if you run the experiments at different times of the day, you can't trust the results since you're bringing in other external attributes which may sway the results. To keep your test accurate, keep both versions of your A/B test on the same schedule. 

A/B testing is a vital part of any business that wants to grow. A large part of this is setting a timeline for the test that will produce informative results. You want to run your test for 2 weeks to get accurate results.

Next, you want to measure your results. Prior to the test, determine what your KPIs are and see how your test affected those metrics. Finally, you want to learn from your A/B test. This means implementing the winning variation and taking learnings from the test to optimize other areas of your site or mobile app. Don't fret if your experiment doesn't generate a positive or conclusive result. Use the experiment as a way to learn more about what you need to do to get the results you want. From there, you can generate a new hypothesis so you can try running another test.

Try DevCycle Today!

A/B testing and feature flags go hand in hand. Collecting user preferences and responding to user feedback is a breeze with simple, yet powerful feature management tools. You can test any element of your product, website, or mobile app and you won't need a lot of data, but the results you'll receive will be extremely valuable. 

Get started using feature flags to run A/B tests with DevCycle’s 14-day free trial.


Author headshot
written By
Ann McArthur

Ann is a product specialist who helps engineers easily get started using feature flags. She resides in Toronto where you can find her at the AGO, or at home whipping up a delicious meal.

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