Improve Your Bottom Line with Successful A/B Testing

Successful online marketing requires experimentation. You’ll need to get a pulse from your audience and figure out what type of content they’ll be more receptive to. 

And that’s where A/B testing, otherwise known as split testing, comes in. 

So what is A/B testing?

At its core, A/B testing involves pitting two different versions of an ad, email, or website to identify which one performs best. This type of test can measure different factors, from the text and color scheme of a CTA button to your site’s landing page.

A/B testing is so important because it has the capacity to exponentially improve your bottom line. But only if the split test is done correctly.

But now that we know the importance of A/B testing, how is it done? Let’s take a closer look. 

How to Conduct a Successful A/B Test

When performing A/B testing, you’re not always going to get it right the first time. But keep in mind that even if the test doesn’t deliver your desired results, the data you’ve collected can still inform your next test. 

That means you aren’t shooting in the dark anymore because your decisions have been shaped by insights you’ve obtained before.

1. Identify Test Variables

Start by deciding what factor you want to test. Is it an on-site or off-site variable?

On-site variables, as the name suggests, are found on the website itself. These include website copy, headlines, calls to action, and the like. Meanwhile, off-site tests measure variables such as social media ads or email copies. 

Make sure you establish your current baselines such as your webpage traffic or your email open rates. Then you can proceed to step two. 

2. Create a Challenger

When performing A/B testing, you’re comparing two versions of the same content. However, a single variable needs to be altered.

Here’s an example. Let’s say you’re testing out your website’s CTA button. Option A, or the control variable, will be the current CTA you’re using on your site. Meanwhile, option B is the altered version, or the “challenger,” with a different variable. These changes could be:

• The color scheme
• The typeface 
• The size of the button
• The position of the CTA on your website

Both versions of your CTA will be shown to users at random. You can conduct statistical analysis to see which one performs better.

3. Run the A/B Test

Then comes the A/B test itself. The duration of the test will usually run anywhere between a few days to two weeks. That’ll give you enough time to gather enough data and results.

The important thing is that you don’t rush the A/B test. Conducting tests over a short period could skew the results because you haven’t had enough time to pinpoint the exact changes the CTA had on visitor behavior. 

4. Focus on a Single Variable

If you’re testing the effectiveness of your website’s CTA button, focus only on one variable at a time. If you’re testing the color scheme, stick to that. Don’t make any changes to the size or the typeface at the same time.

Focusing on a single variable makes it easier for you to identify what specific change led to the desired outcome. 

It’s possible to test multiple variables at the same time, however. This type of test is called multivariate testing, and its goal is to identify which combination of variables performs the best. The different versions are tested concurrently to determine the winning variation. 

Multivariate tests can end up saving you more time in the long run but they’re also more complicated to run. The more factors you need to test, the longer it’ll take to gather insights. 

5. Test the Control & Challenger Variables Simultaneously

Your A/B test should focus on a single variable. But make sure that when you test these single variables for the control and challenger groups, you’re testing them simultaneously. 

Let’s say you carried out the A/B test for the control group in November and the challenger group for December. It wouldn’t paint an accurate picture of which one performs best because one variable could receive a higher engagement than the other. After all, the influx of sales due to seasonal differences could end up skewing the results.

However, if you’re specifically testing for the best time to send a message — like when measuring email engagement to improve open rates — it’s perfectly OK to space out the A/B test. 

6. Determine the Statistical Significance

Statistical significance plays a crucial role in the data provided by an A/B test because it measures the difference between your existing variable and the challenger.

For example, if you ran a test and received a 96% confidence level, it means that you can be 96% confident that the differences are real. In turn, it will ultimately decide which variable will come out on top after the A/B test. 

7. Use the Right Tools

There are various tools available to help you measure statistical significance. You can use the free statistical significance calculator from Neil Patel or HubSpot, for example.

If you’re looking for free A/B tools, on the other hand, Google Optimize is your best bet. It might be easier for you to use, especially if you’re already familiar with other tools like Google Ads and Google Analytics.

8. Implement the Changes

After you’ve conducted your A/B test and identified which variable performs better, you can replace the previous version. But if the challenger failed to outperform your control, that means the alterations you’ve made are ineffective.

And that means you need to continue testing. But don’t feel discouraged, though — you can still use the data you’ve collected to help guide your next A/B testing. This way, you’re moving forward and gaining valuable insights for your future marketing campaigns.

9. Plan Your Next A/B Test

Regardless of whether your A/B test yielded positive or negative results, it helps to plan ahead for your next analysis. As mentioned earlier, constantly evaluating your site and testing out different variables gives you the opportunity to optimize it for higher engagement and conversions.

It’ll also help you keep up with the ever-changing nature of the marketing world. What works today isn’t always a guaranteed success tomorrow. So conduct A/B tests regularly to understand your audience better, make more informed marketing decisions, and ultimately increase your bottom line.

If you need more help identifying what works best for your digital marketing campaigns, Growth Rocket can help. Get in touch with us today.