What is A/B testing: definition, examples, and tips

A/B testing is a method used to compare two versions (of website landing pages, email copies, ads, product features, etc.) to find out which one is received better by consumers. It takes the guesswork out of deciding what will work best: instead of hoping what you choose is the best version, you have exact data to confirm which option performs better.

A versus B

So, what exactly does A/B testing entail? 

At its core, it is sending or sharing two versions of the same copy/website/advertisement with just one difference between versions A and B, and comparing the results depending on the goals of the experiment. Usually, open rate, click-through rate, and conversions are compared.

An A/B test can be as simple as making one call-to-action button orange and the other one blue. Everything else in these two versions is identical. If more people click on the orange button than the blue, you will know that an orange CTA button will bring you a higher click-through rate among this audience. 

email a/b test example
A classic example of email CTA A/B test

A/B testing takes assumption out of the equation and gives you an objective answer on how you can change your copy to get better results. A/B testing can also be applied to product features to determine possible improvements. Different audiences respond to different things, and guesswork is not a risk you should take. 

Why you should A/B test

First of all, A/B testing is an affordable way to figure out how to improve your copy or product to achieve the best possible results. Anyone can A/B test their email, ad, UI, etc., with little extra effort.

Secondly, while it may take a few trials, in the end, you will find the most effective variation of your copy or product and get valuable insight into what your audience prefers, giving you an advantage in the future. 

How to do A/B testing

To do A/B testing correctly, you should only ever test one variable (change) at a time. Testing more than one variable at a time won’t show you which change is responsible for the achieved result. 

The variables you can test are limitless. Colors, headlines, words, phrases, images, copywriting formulas, videos, icon placements, and a million other things can be changed and tested to see what leads to higher conversion rates and better CTR. 

Here’s how to start:

  • Figure out your goal
    Do you want a higher open rate? More conversions? Lower bounce rate? Defining your goal means knowing what needs testing, as well as the improvement you’re looking for.

  • Pick what element you want to test
    There’s little point in testing something that doesn’t affect your main goal. Make sure you’re testing elements and comparing metrics that actually lead to your final goal. For example, comparing your open rate when your main goal is growing conversions won’t necessarily lead to accurate results. In this case, comparing the click-through rate would be more accurate, especially if you’re using UTM tracking. Another example of incorrect test element choice would be testing website footer design to lower bounce rate. Instead, test your website content and overall design.

  • Remember to only A/B test one thing at a time
    As we’ve mentioned before, if you are changing multiple variables at once, you will not be able to determine which variable is making the difference, which defeats the purpose of an A/B test.

  • Analyze current performance
    If you do not know your baseline, you cannot see or compare the changes. Know where you stand so you can see where you are going. Better yet, leave a small control group out of your A/B testing.

  • Design the test
    Define how long it will run, what data it will gather, the sample size, etc. Set the metrics for your A/B test before releasing it out into the wild. Always split the two groups equally and randomly, and perform the tests simultaneously to get accurate results. Of course, you can perform A/B testing within a specific group or demographic too, but still make sure the split is equal and random.

  • Make the change
    If you see a clear positive difference between the A and the B (and, of course, the control group, if you’re using it), make the change and reap the benefits. You will find the smallest tweaks can make a big difference, so do not pass up the chance to improve your asset.

  • Rinse and repeat
    More A/B testing is normally the next step. You want your assets to be as lucrative as possible, so making sure everything is at its best for the consumer is a no-brainer. There is always room for improvement. 

It’s easy as ABC

As you have read, there are several steps to successfully running an A/B test, but none of them are particularly hard, or at least not hard enough to abandon the method – and it is certainly better than blindly making changes and just hoping they work. 

A/B testing a very effective tool in many aspects of consumer interaction and will help you understand better what works and what doesn’t, which is extremely important in making future decisions.

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