How to Run A/B Tests with Next.js

Running a successful marketing campaign is a challenge, and finding the most effective approach takes time. After all, a marketing project rarely hits every goal on the first try. That’s why several techniques have been developed to test different ideas and approaches at the same time, collecting data to determine which solution works best. This process is called “A/B testing”.

An A/B test, also known as a split-run test or bucket test, is a method of comparing two or more versions of a web page, app or user interface to find out which one delivers better results.

In other words, A/B tests are randomized experiments in which two or more variants of a page are shown to different visitors at the same time to collect data. This data is then analyzed with a statistical approach to determine which version performs better against a given marketing goal or specific business metrics.

A/B tests can be applied to any page of a website and play a key role in increasing conversion rates. Optimizing a marketing campaign through A/B testing lets you get the most out of your website. The elements you can vary in an A/B test include anything that can influence visitor behavior and lead visitors to your marketing goals: headlines, site design or layout, colors, images and copy, for example.

Don’t overdo it with A/B tests. Keep them simple and change only a few variables at a time. And remember that you can always run multiple A/B tests at the same time, especially if your website has many pages.

Now let’s see how A/B tests work in practice.

An A/B test is simple. Say you want to apply one to a landing page. All you need to do is take your current landing page and modify it to create a second version. The change in the new landing page could involve the layout, the order of components, colors, a button, some headlines or other elements. The key is to avoid changing too many things at once, especially if the landing page already performs well. The more you change, the harder it becomes to interpret the results of the experiment.

Next, a share of your site traffic is shown the original version of the landing page, while the rest sees the modified version. How you set these percentages can depend on several factors, but you can also go with a simple 50%/50% split.

As users visit the two or more variants of your landing page included in the experiment, data is collected behind the scenes. This data is then used to produce metrics that can be measured and analyzed statistically to determine whether the change had a positive, negative or neutral effect on your marketing goals.

There are several reasons to run A/B tests, but let’s focus on the three most important.

• It helps you improve conversion rates: driving traffic to a website isn’t easy, which is why you should use techniques that get you the highest possible conversion rate. That’s exactly what A/B tests are for.
• It gives you scientific results: an A/B test involves collecting, analyzing and studying a lot of data and metrics. A/B tests therefore produce results backed by statistical analysis, not guesswork.
• It removes the fear of making changes: people are often afraid to change a website because of the possible consequences, especially when it has been online in the same form for years. A/B tests let you study the effect of changes and help you make low-risk updates.

In this previous article, you saw how to build a landing page in Next.js. Now you’ll learn how to extend that demo app to add A/B testing logic.

You can implement an A/B test in Next.js without any extra dependencies. This means the list of prerequisites is the same as for the landing page demo app:

• Node.js 12+ and npm 8.0+
• Next.js >= 12.x
• React >= 18.x

Clone the GitHub repo that accompanies this article and try the A/B test locally by running the following commands:

Then visit "http://localhost:3000" in your browser to see the A/B testing logic in action on the landing page.

Otherwise, follow this tutorial and learn how to implement A/B tests in Next.js.

The landing page template you’ll find here consists of a header, a hero section, a CTA, an “about us” section and a footer. To run an A/B test, you need at least one new version of the landing page. So the first step is to define the following two new components:

• "LandingPage1"

• "LandingPage2"

These two components correspond to the two versions of the landing page. As you can see, the main difference is that "LandingPage2" has a custom "className" attribute. It is used to style the landing page differently from "LandingPage1", the original landing page. The two landing pages also use two different components for the hero section. Here is how these two components are defined:

• "Hero1"

• "Hero2"

The main difference between these two components is the image and the headline text. You now have two landing pages to alternate in an A/B test. Let’s see how.

The new "index.js" file, which represents the home page of the demo website, is now defined as follows:

In the "getStaticProps()" function, "Math.random()" is used to randomly generate the number 1 or 2. This number then determines which landing page is shown to the end user. Likewise, the data for the services shown on the landing page is fetched differently depending on the number drawn. Note that you can make the selection logic much more sophisticated, for example by using weights to get different selection percentages.

Start the demo app built to run an A/B test with the following command:

Open "http://localhost:3000" in your browser and click the "Reload page" button at the top of the page. You should randomly get one of the two landing pages, depending on whether 1 or 2 is drawn in "getStaticProps()".

At this point, you can use Google Analytics, adding UTM (Urchin Tracking Module) parameters to CTA links or following similar approaches, to start collecting data from the landing pages and determine which one performs best. Learn more about the legality of Google Analytics in Italy here.

Et voilà! You’ve just implemented an A/B test in Next.js!

At Cantiere Creativo, we rely on DatoCMS to optimize and plan marketing campaigns. If you’re not familiar with it, DatoCMS is a headless CMS, a content management application without a front end. DatoCMS lets you store, manage and deliver content from a single place through APIs. That makes it the perfect headless CMS for managing content in an omnichannel strategy.

When it comes to A/B testing, a headless CMS like DatoCMS can support your marketing strategy in several ways. First, DatoCMS lets you build modular web pages quickly and easily. Defining the variants for your A/B test takes just a few minutes, and anyone can do it. Second, DatoCMS content is fetched through APIs.

So if you want to change the content shown on a page at random, you simply randomize the API call. Third, all content is managed in one place. As a result, analyzing A/B test results becomes easier, especially when tests run across multiple pages or websites.

In this article, you learned what an A/B test is, how to run A/B tests and why you should consider A/B testing to optimize a website, an app or a marketing campaign. You also learned how to implement an A/B test involving landing pages in Next.js. As shown here, it isn’t hard and takes only a few lines of code. However, if you want to take your A/B tests to the next level, you may need the support of a digital partner that uses advanced tools like DatoCMS. Thanks for following the tutorial! We hope you found this article useful. Feel free to contact us here with any questions, comments or suggestions.