In the world of digital marketing, knowing what works and what doesn’t work is the proverbial quintessential to online success.
Oftentimes we as marketers tend to get lost in assuming how we think visitors experience our websites, that we forget that we’re drawing conclusions from our own experiences, backed with a bit of quantitative data spawned by Google Analytics.
To know what truly works and what doesn’t, we need the perfect blend of quantitative and qualitative data. We have the quantitative part sorted, but now we need the qualitative – how can we achieve this?
With a little thing called A/B testing.
What is A/B testing?
A/B testing is a digital marketing experiment where marketers ‘split’ their audience to test a number of variations of a campaign in order to determine which works better. In a nutshell, A/B testing enables marketers to show version A to one half of their audience, and version B to another.
What are the benefits of A/B testing?
Now that we have a bit more of a solid understanding of what A/B testing is, let’s dig a little deeper to uncover some of the most prominent benefits A/B testing has to offer.
One of the biggest advantages of A/B testing is the ability to provide insight on how to improve content. Whether the goal is to answer a single question, or improve conversion rate, A/B testing can help marketers extract the maximum value from their production tests and increase their ROI.
Improved user engagement
So, we know that A/B testing is a smart way of improving the content on your site but improving content unlocks a trove of benefits, one of which is improved user engagement. When you analyse the results of a test and use them to inform your decisions going forward, you can make improvements to your content that drive engagement.
If you’ve been wanting to implement a new feature or element on your website but are skeptical because you’re not sure how users will react to it, that’s where A/B testing comes into the equation; by A/B testing a new feature, you can minimise risks to understand user reaction (be it positive or negative) before implementing it in the flesh.
Increased conversion rates
A/B testing allows marketers to test out different experiences. This is crucial because a website is naturally home to hundreds of different elements; meaning it becomes challenging to determine the best placement of certain elements to promote conversion. A//B testing provides an effective way to determine the best way to convert visitors to purchasers.
How to A/B Test?
If you’ve been wondering how to A/B test but haven’t been quite sure on the process; you’ve come to the right place. Below we’re going to outline how to perform a A/B test in a simple, easy-to-follow format.
Step 1: Decide on an independent variable to test
Before you embark on your test, you need to pick a variable that you’re going to test. As you go deeper into the web optimisation process, you’ll naturally uncover an array of variables you’ll want to test. But for your test to be effective, you need to isolate one independent variable and measure its performance.
Step 2: Identify your dependent variable
You’ll likely have a few metrics during any test, which is fine, but you’ll want to choose one primary metric to focus on. This primary metric will be your dependent variable, which will change based on the manipulation of your independent variable.
Step 3: Create a challenger
So now you have a few of the required ingredients to perform an A/B test, but there’s one crucial ingredient missing – the challenger.
Your challenger is simply the altered version of whatever you’re testing; it could be an altered landing page, website, or email. Step 3 is all about building your challenger.
Step 4: Evenly split your sample groups
The success of an A/B test lays in its equality. What we mean by this is that you need to test with two or more audiences that are equal to generate conclusive results.
Step 5: Use an A/B testing tool
To effectively conduct an A/B test, you need to use a tool that can provide you with the software you need to successfully run these tests. One of the best [free] tools out there for A/B testing is Google Optimize.
Step 6: Test both versions simultaneously
Timing plays a crucial role in the results of an A/B test. You need to ensure that you run both versions of your test congruently. There is little to no point running variant A at one point and running variant B a month later.
Step 7: Give it time
You need to give your test sufficient time to obtain a substantial sample size. If you don’t, you could risk not being able to tell whether there was a significant difference between the two tested variations. There is no hard and fast rule on how long an A/B test should run for, but just make sure that you express some patience and give the test time to do its thing.
Step 8: Measure your results
Once the test has drawn to a close, you need to measure your results. One of the best ways to do so is by using an A/B testing calculator. HubSpot has a great [free] A/B testing calculator that can help you determine whether the results of your test were statistically significant to justify a change.
Step 9: Take action
The last and final step in the A/B testing process is to turn insights into action. If one variation of your test performed better than the other, then alas – you have a winner! If neither of your variations performed better then you can rule out that the variable you tested didn’t impact results, making the test inconclusive.