10 min

What Is A/B Testing and How to Conduct It

A/B Testing can help update your website and tools. Yext explains the steps of A/B testing and how you can implement them in your marketing process.

By Yext

Jan 28, 2022

10 min

Optimizing elements on your website is an essential activity for any business with an online presence.

The internet is constantly expanding and shifting, and on top of that, so is your audience and their expectations.

Keeping up with all of these adjustments can be a little overwhelming if you're just making blind changes hoping that they'll make positive changes in your business success. But there's a better way.

A/B testing, also known as split testing, is a way to experiment with multiple variables by presenting two options to your users and determining which is most successful through data analysis.

While that might sound a little confusing, it's pretty easy to understand when it's broken down. And it's easy for your company to utilize the method for upgrading your online content.

What Is A/B Testing (Split Testing)?

As we mentioned, A/B testing is similar to experimenting with your content, layout, or other elements of your virtual storefront.

Start by presenting your visitors with two versions of a web page, preferably one that's a "control" option that includes the content on your page as it stands, or version A. The other being a new idea, an adjusted version, or version B.

You can accumulate user data regarding bounce rate, conversion success, and other network traffic analyses by presenting these simultaneously.

A/B testing allows you to examine the difference between two ideas and determine which will be more successful with your audience.

What Are the Benefits of A/B Testing?

Obviously, making decisions based on immediate user data is a major benefit of A/B testing, but there are several best practices you should consider when looking to optimize or update your company website.

Traffic data can tell you a lot about what your visitors like and don't like, not to mention it provides insight into where your company should focus when it comes to your future objectives.

Here are a few benefits of A/B testing.

Identify User Experience Issues

Regardless of what type of business or website you're managing, identifying and removing trouble spots that cause a bad user experience is essential.

With A/B testing software, you can see what variation works best for your users, but you also get insight into what's turning them away. This could include pages with confusing layouts, difficult to use navigational tools, long load times, or irrelevant content.

Using A/B testing and user behavior tools to record and analyze their experience will help you shape your website and remove anything that gets in the visitor's way.

Decrease Bounce Rate

Bounce rate is the measurement of how often users visit a single page of your website and then leave. You obviously want this number to be as low as possible.

Because users are all unique, as is your website, there isn't always a simple solution to reducing bounce rate. But being able to test multiple variations and conclude which element option holds on to page visitors the longest or even gets them to continue their exploration of your site is a major step forward.

Develop Reliable Adjustments Based on Data

When talking about using A/B testing to optimize your website, we don't mean to sound like we're pitching a miracle cure for all of your major problems.

At least, not all at once.

A/B is most effective when it comes to incremental changes to your content that, over time will change an unsuccessful website into something your users actually enjoy using.

This is a benefit to your company because, while sweeping major changes might sound nice, smaller changes heavily reduce the amount of risk your business takes by making the adjustment.

While A/B provides data and feedback to guide your choices, making any changes to your page has potential negative side effects. Sticking to small, educated adjustments through A/B lets your company reduce these risks while still moving towards a website your users will love.

Web Page Elements To Test With The A/B Method?

A/B testing allows your company to present variations of elements on your website to users and collect data to determine the most successful option.

The elements you could optimize through A/B testing can include pretty much anything on your pages. There isn't anything that couldn't be made better through the process.

But some aspects of your website are more critical to successful conversion rates and user experience.

Here are some elements you can and should test with the A/B method.

Navigation

The navigation on your website is essential to customer success. Users report turning away from sites with confusing and difficult-to-use layouts, especially when they don't have a convenient system for navigation.

Whether it's an advanced internal search engine or a drop-down menu full of hyperlinks to specific pages, your site needs a high-quality navigation option.

Landing Page

The landing page is a specific and condensed page that doesn't necessarily link back to your website but rather contains everything the user needs to know about a specific focus.

Say, for instance, that as part of your marketing campaign, your company has an ad circulating social media services. One version is a banner. The second version is a simple CTA button (call to action button) at the bottom of a page.

A landing page is what the user would end up on if they were to click on the banner or button. You don't need them to access the whole page, but rather one location with all of the information and products they were interested in. Remember, the placement of your banner and CTA button may affect its effectiveness as well.

When the test is over you can view the A/B test result metrics to see which version performed better.

Page Structure

The amount of content you have on your site, how it's organized and available, and how many pages you spread it out is what we consider page structure.

Each one of these aspects of structure could be tested individually. How the user reacts to the layout on your site is a major part of whether they enjoy their time on your site.

More often than not, users end up on your blog post or page because they're looking for something specific; the aesthetics aren't what immediately concern them.

But the combination of having relevant and easy-to-find content while also organizing everything in a presentable way is important for conversion rate optimization (CRO).

Header (Headline)

The header of your page is what you find at the very top. It's generally a horizontal bar that includes your company logo, perhaps menu links, and an image.

The header follows your user around from page to page, making it even more important that it's as good as it can be. As of today, headers tend to be fairly minimal and to the point. But with A/B testing, you can finagle your header to fit your user expectations perfectly.

Call To Action

The call to action can take a multitude of forms, but its primary goal is always the same: Get the user to engage or convert.

Whether it's a pop-up ad for a sale you're having, an AI Bot asking if there's anything specific they're looking for, or an image the visitor can interact with. The call to action needs to grab the user's attention while not being too distracting or annoying.

Variations of A/B Testing

A/B testing can be done in several unique ways, each with its own pros and cons. It depends on what you're testing which one is right for the situation.

Knowing about the different versions of A/B testing will help you be prepared for whatever subject you're looking to optimize.

Split URL Testing

Split URL testing is what probably comes to mind first when you think of A/B testing. Take two variations of the same web page and offer them simultaneously to your users, recording data on which one is more successful and implementing the "winner."

Split URL testing is great for focusing on specific changes from one page to the other. While the actual growth may be slightly more limited, the data is far more focused and easy to analyze.

Multivariate Testing

Multivariate testing is a more complex form of A/B testing but just as useful for different applications.

This form of testing involves multiple versions of the same page being available but with several different variations that create different combinations on the page.

This lets developers test how users react to different combinations of changes, optimizing the entire page on several different levels at once.

Multivariate testing reduces the amount of time and number of tests required for optimization. While it doesn't offer focused data like split URL testing, Multivariate helps connect interactions between a multitude of focus points.

How To Conduct A/B Testing

A/B testing can be incredibly useful when it comes to shaping your website and making positive changes.

However, it needs to be executed properly to function fully. Like any other experiment, there are steps to follow to ensure your results are as accurate as possible.

Research

Before starting any experiment, collect data and research your website as it is. You should know every detail about your website and traffic data before you try to make adjustments, or else you may miss relevant internal influences.

As well, do research on the element or elements you plan on adjusting. What trends do users respond to positively right now? What could it currently be about your layout that is turning people away?

Being well informed about internal and external sources before you start is imperative to the success of your experiment.

Develop A Hypothesis

After you've done your homework on why your website might be failing and what you could do to optimize, it's time to create a hypothesis.

A hypothesis is simply a statement of belief that your experiment will either prove correct or incorrect. Granted, it should be based on the data that you've collected so far.

Imagine your goal is to decrease your bounce rate, for example, and after researching your site and others, you believe that users jump ship because of your cluttered header.

Your hypothesis would be something along the lines of "Users dislike our header because it has too much going on, so if we create a more minimal yet still convenient header, our bounce rate will decrease."

This allows you to set up and move forward with your A/B testing from a scientific standpoint.

Create Variations

The next step is to create variations that we'll use to test the hypothesis. In this case, you would develop a cleaner header, either a simpler logo, link set up, or font design.

Execute Testing

The time the test will take depends on how many changes you're making and how in-depth you want your results. Depending on the variation in results, you might determine a winning variation pretty quickly, or you might need to watch the race for a little longer to collect more data. Your test should run for a specified time, one day, week, or month, for example.

Analyze Results

Once our test is complete, examine the traffic data from each variation. You might've set out just to determine whether the bounce rate would be affected, but there are always other potential effects that changes you make can have.

Make Adjustments Based on Data

After analyzing the results of the experiment, you should have a clear answer to your hypothesis. In this case, we'll say that yes, having a more minimal header reduces the bounce rate.

The next step would be to implement change based on this data, in our case, making the minimal header a permanent fixture on your website.

In Conclusion

A/B testing, whether split URL or multivariate, can be extremely useful when it comes to making changes to your website. User behavior data is critical when it comes to conversion optimization.

Your target audience will tell you what they do and don't like; you just have to listen. Take your time hypothesis testing with an A/B testing tool and follow the steps to ensure accurate results; rushing through experimentation and disregarding influences that show statistical significance can deliver inaccurate data.

Sources:

14 Reasons Why You Need to Update Your Website | Granite5

What Is Network Analysis? | Cisco

What is a Hypothesis? | Study.com

Share this Article