Even the most talented UX designers, web developers, and content creators cannot make a perfect website on their first effort.

Creating the perfect website or landing page takes effort and iteration. It involves testing variations, getting feedback, and incremental improvement.

Fortunately, there is a method to scientifically achieve this – A/B testing.

What is A/B testing for landing pages and how can it benefit your website? We explain the answers in this guide to website A/B testing.

What is Website A/B Testing

The concept of website A/B testing arises from statistics, where A/B testing allows researchers to compare two versions of a single variable.

Website A/B testing involves changing a single element of a webpage, such as its headline, button design, or logo.

Then, you simultaneously show these two versions to two similarly sized audiences and analyze which webpage performs better according to a predetermined metric or set of metrics.

In short, A/B testing is a statistical experiment with straightforward steps.

1. Incrementally Change Single Elements of Your Webpage

A/B testing changes a single variable of a landing page.

In some cases, early in the design process, you might choose to show two significantly different landing pages.

When you compare landing pages that are different in many regards, this is called split testing.

In some cases, it is best to begin with split testing. After one of the two different designs proves best, you would move on to A/B testing to optimize your webpage.

For A/B testing, you then change single elements to refine your webpage to an optimized ideal.

You want to isolate one change, or “independent variable”, and measure the performance between two variants of this element. Otherwise, if you have several elements you are testing at once, you cannot determine which change is having a real impact on the outcome.

2. Simultaneously Show the Different Pages to Users of Similar Size

A/B testing involves showing your two landing pages to your users at once.

Some of your webpage visitors will see the “control” landing page, which is the landing page you consider your primary design, while some will see the “challenger” design.

The “challenger” variant of your website contains the single change you wish to test. In statistical research, the visitors who see the challenger page are called the control group.

 3. Collect Interaction Data According to Predetermined Metrics

You will likely measure a number of metrics for each A/B test.

But you should choose a primary metric to focus on before you run the test. The primary metric you choose depends on what you are looking to optimize.

Are you looking to improve clicks, bounce rate, conversation rate, or another metric?

Decide which of these metrics you intend to optimize, and which one is most important before you begin A/B testing.

 4. Use Simple Statistical Analysis to Understand

Once you have selected the metrics you want to optimize, think about how significant your results need to be to justify choosing one variation over another.

If the challenger’s metrics are only slightly better than the control page, or your primary landing page, do you want to make the change?

The process of making this decision is called statistical significance.

Why Use A/B Testing

A/B testing takes the guesswork out of designing web pages and increasing user engagement.

Undoubtedly, website design and content creation is a creative, subjective tasks.

A/B testing does not detract from this creative process, but it allows you to scientifically evaluate what website design most efficiently achieves your business objective.

Get Started with A/B Testing

At its core, website A/B testing is simple. But in practice, how do you go about running such an experimental test?

How do you drive some users to one page and others to another? How do you collect your decided metrics and analyze them using robust statistical measures?

Contact Marketing Magnitude to find out more about A/B testing. We have the tools and experience to make A/B testing simple and efficient.