The Ultimate Guide To A/B Testing

Marketing decisions cannot be based on intuition. Instead of guessing or assuming what will make people click and convert, run an A/B test also known as a split test. Audiences behave differently and what works for one business differs from what works for another – all of this makes A/B testing valuable. However, the complexity of A/B tests could lead you to make inaccurate assumptions.

Below is the ultimate guide, explaining all about A/B testing and how to do it before, during, and after data collection to help you make the best decisions from your results.

What Is A/B Testing?

You can run an A/B test by first generating two different versions of a single piece of content with alterations to only one variable. Expose these two versions to two equally sized audiences and examine which one did better over a particular time.

The following two kinds of A/B tests can be conducted to grow your website’s conversion rate:

User Experience Test: You might want to see if changing the position of a certain call-to-action (CTA) button from the sidebar to the top of your homepage help to improve its click-through rate. To A/B test this idea, you have to generate an alternative web page that reflected that CTA placement change, and then test these two versions.

Design Test: You might want to know if changing the color of your call-to-action (CTA) button can improve its click-through rate. For this, you have to design an alternative CTA button with a different button color that leads to the same landing page as the control and then analyze both.

The Benefits Of A/B Testing

A/B testing has numerous benefits based on what you decide to test. These tests are inexpensive but effective, hence helpful to a business. Now, if you want a content creator to take two days creating an A/B test on one article, rather than writing two articles during the time frame, you might spend $192 since you’re bringing out one less article. But if A/B test reveals that you can grow each article’s conversion rate from 10 to 20 leads, you just spent $192 to possibly twice the number of customers you get from your blog.

You can lose $192 if the test fails but then you can make your next A/B test even more educated. If your blog’s conversion rate is doubled by that second test succeeds then you eventually spent $284 to possibly double the revenue of your company. The eventual success of your A/B test will nearly always compensate the cost to conduct it even if it fails multiple times.

How to Conduct A/B Testing

Before the A/B Test:

The following steps can be taken before you start your A/B test.

1. Pick one variable to test. There might be numerous variables that you want to test as you optimize your web pages and emails. But take one “independent variable” and calculate its performance to assess the effectiveness of the change and to ensure which one was responsible for changes in performance.
2. Identify your goal. Before running the test, select a basic metric to concentrate on, even before setting up the second variation which will be your “dependent variable.”
3. Create a ‘control’ and a ‘challenger.’ Use your independent variable, your dependent variable, and your desired outcome to set up the unaltered version of whatsoever you’re testing as your “control.”
4. Split your sample groups equally and randomly. You should test with two or more audiences that are equal to have conclusive results for tests in which you can have more control over the audience such as emails.
5. Determine your sample size (if applicable). The way you determine your sample size will also change based on your A/B testing tool, and the type of A/B test you’re running.
6. Decide how significant your results need to be. After picking your goal metric, reflect on how significant your results should be to rationalize selecting one variation over another.
7. Make sure you’re only running one test at a time on any campaign. Don’t complicate your results by testing more than one thing for a single.

During the A/B Test

The following steps are taken during your A/B test.

1. Use an A/B testing tool. Use an A/B testing tool to conduct an A/B test on your website or in an email.
2. Test both variations simultaneously. Timing is important as far as your marketing campaign’s results are concerned.
3. Give the A/B test enough time to produce useful data. Let your test run long enough to get a considerable sample size. Otherwise, it’ll be difficult to know whether there was a statistically significant difference between the two variations.
4. Ask for feedback from real users. Collect qualitative feedback from real users as you’re running your A/B test.

After the A/B Test

The following steps need to be taken after your A/B test.

1. Focus on your goal metric. You’ll be calculating multiple metrics but keep your focus on that primary goal metric while doing your analysis.
2. Measure the significance of your results using our A/B testing calculator. After determining which variation works the best, it’s time to conclude whether your results are statistically significant i.e. sufficient to justify a change?
3. Take action based on your results. If one variation is statistically better than the other, then disable the losing variation in your A/B testing tool. If neither variation is statistically better, then the variable you tested didn’t impact results, which means your test is inconclusive.
4. Plan your next A/B test. The A/B test you just run might help you find how to make your marketing content more effective but don’t stop there. There’s always scope for more optimization. Keep exploring new ways to increase conversion rates and leads.