What is A/B testing and how does it work?

Give the test sufficient time and receive meaningful results

Data is a huge deal in online business. No self-respecting marketer, manager, or leader makes decisions without analyzing the data. Why? Because data is evidence that ensures that the decision won’t be made on instincts.

If you’re wondering what it is, read below.

What is A/B Testing?

A/B testing is defined as a method of measuring two versions of something to see which one performs better. In online settings, one can compare two or more versions of an app, a website, or another user-oriented digital product.

Google approves and even encourages this method.

A/B testing is essentially an experiment where multiple versions of a website or an app are provided to users at random. To determine which version works better, statistical analysis is used.

A/B Testing

As the result of the analysis, the developer of the tested product may identify specific areas of improvement by collecting and analyzing the impact of the difference between the compared versions.

How A/B Testing Works

To start testing, you need to decide what it is you want to compare. For example, you can compare two different website designs, sizes of the subscribe button, colors of CTA buttons, etc.

The second step is to determine how you want to analyze the performance of the solutions. For example, if you’ve decided to test the effectiveness of two colors of the CTA button on the landing page, you can assign two different versions of the pages to be visited by users.

Then, you compare the performance of the two versions and determine which color received more clicks, and therefore, more customers.

Given that the color of CTA buttons may affect their performance (for example, it is typically recommended to make them stand out on a page by using orange, green, or red colors), it is a great idea to randomize and determine the best-performing option.

How to maximize the Effectiveness of A/B Testing?

“To get the most out of the testing, it needs a clearly defined hypothesis,” says Jim Bosh, an online marketer. “After testing various aspects of our professional essay writing service website I can say that A/B testing is a basic type of randomized controlled experiment. It requires testing a conditional statement about the relationship between two or more variables.”

To continue with the example of CTA buttons, we can develop a hypothesis that a red-colored button will attract more clicks than a green-colored one. If the results support the hypothesis, the version with the red-colored CTA button will be employed by the site.

Call to Action Buttons

Remember: every A/B testing you perform should have a hypothesis behind it.

A Straightforward A/B Testing Process

To start running tests for your needs, you can follow the simple testing framework below.

  • Gather Data. As it was mentioned in the introduction to this article, it’s all about data these days, and no one makes decisions unless they are backed by substantial evidence in the form of data. By collecting the data from your Google Analytics, you can determine areas that need improvement. For example, these could be low conversion rates on landing pages.
  • Determine Goals. Supposing that you want to increase a conversion rate, the conversion goal will be the metrics that you will utilize to identify whether one version of a landing page performs better than another. For example, a specific number of email signups or CTA button clicks could be good, measurable goal.
  • Create Hypothesis. We’ve already established you need hypotheses to generate meaningful results and get the most of testing.
  • Define Variations. They are the change that ensures better performance of a website, an app, or another digital product (color of a CTA button, etc.). A/B testing software helps to make these changes quickly and efficiently.
  • Conduct the First A/B Testing. Run the experiment by randomly assigning your site’s visitors to either the control version or the experiment version of the element you want to test. Measure the experience of the users for future comparison.
  • Analyze the Findings. At this point, you have all the data you need to know whether your hypothesis is correct. The A/B software will present the results so you know if you should apply the change.

Time to Test

A/B testing is an effective and informative method that can be useful for your online business. It also requires your patience because the process is not going to produce meaningful results overnight.

In fact, depending on the volume of the traffic you receive, the test may take from a few days to a few weeks. Be sure to give the test sufficient time and receive meaningful results that will help you to advance your online business.

Happy testing!

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Published on May 30, 2018 by Tom Jager; modified on May 29, 2018. Filed under: , , .

Tom Jager is a professional blogger. He works at A-writer. He has a degree in Law and English literature. Tom has written numerous articles/online journals. You can reach him at G+ or Facebook.

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