A/B testing best practices: Don't make these mistakes

A/B testing is an incredibly useful method for testing your marketing assumptions. A/B tests aim to bring some objectivity to what was once a largely creative domain. Controlled experiments, in which test subjects are split into two variations in order to compare results to prove or disprove a hypothesis are common in many scientific fields.

A/B testing is a powerful tool for CRO (conversion rate optimization) that is used to validate certain decisions made in the process of enhancing marketing content. It can be used to test anything, from copywriting, to images, to call-to-action prompts, etc. From completely different designs to slightly different shades of blues, A/B tests help objectively define whether any given element has an impact.

Of course, it goes without saying that well-planned and executed A/B testing can have a significant positive impact on your marketing numbers. But even if it doesn’t, the biggest benefit of A/B tests is the power to make educated decisions. Determining what works and what doesn’t is important in ensuring that the effort you put into marketing doesn’t go to waste. A/B testing, when used correctly, can be very powerful.

Here, you will find a list of common A/B testing mistakes for you in order to sharpen your testing initiatives:

You might think that you don’t necessarily need to conduct A/B testing because you have a great understanding of what works for you and your target market– but you may be surprised. The reality is, what is true today may not be true tomorrow, due to the market or competitors.

The benefits of A/B testing include, but are not limited to, reduced bounce rates, increased conversion rate, boosted engagement, and clearer analysis. These are things that any business can glean a positive impact from.

Your business may be doing well, but you will never know if you can do better without doing some tests. A/B testing is not only reactive, but it can be used in a proactive approach as well. A/B testing eliminates that degree of subjectivity.

It’s going to be essential before embarking on a test that you ask yourself if you’re testing the right variable. It may seem obvious, but you need a good idea of why you are conducting a test in the first place. Define and make sure you can properly measure your evaluation metric before you start testing. Doing so makes sure you can make a decision without ambiguity once the test is over.

Of course, there are a huge number of potential variables to test. Think about which metrics are most important to your business. Ask yourself which metrics you are unsure about. Which metrics cannot be measured by tools like Google Analytics? It will be important to look at the elements in your marketing toolkit and think of possible alternative ways of doing things; from subject line, to sender’s email, to sender’s name, to images, and so on.

Don’t forget that the end goal of running a test is learning something from them, and tweaking your strategy from there. Sometimes, after a test, the results will be very close. This doesn’t mean that you’ve wasted your time testing. This means you now have a clearer idea of which variables matter and which don’t when considering how to go about your marketing strategy. The variable you have chosen is not an influencing factor. Having the right goal in mind is crucial to avoid wasting your time.

No change in performance means that you will have to work to identify what factors do indeed matter to potential prospects. There are many different elements you can test, so it’s time to pick yourself up by your bootstraps and try something else.

Unfortunately, as markets change, and as your audience’s preferences change, you will need to continue to test your assumptions. Sometimes you’ll need to run the same tests multiple times and change the variables until you have the best one down pat.
In addition, you’ll need your tests to continue to focus on the details of your page, optimizing your conversion rate over time. Often, it’s valuable to throw in a brand new design for a page, to see if it has an impact.

However, don’t run the same test too much. Don’t forget the intention of running these tests– we are checking to see if a change makes any impact. If you test something and you note that the impact had a statistical significance, you can be relatively certain that a change is worthwhile.

So, say you notice that when the tested CTA button is bigger, the conversion is higher. Then, you would go on to make it bigger for all prospects. The next step after that is finding another variable to test, like its color, etc.

Running a test is not a method that is only reserved for seasoned marketing gurus. Everyone that has the resources available should be testing without breaking a sweat. This doesn’t necessarily mean that you should run out and hire someone to do the tests for you. Choosing a software that can take the guesswork out of running these tests will save you a lot of headaches. The VBOUT platform has A/B testing built in, in order to simplify the process. Click here to learn more.

Another common mistake is ending the test too soon. Depending on the tested variable, it is often good to work with the proper resources to determine what a significant sample size is. On the web, it generally means running your test for long enough to capture the right amount of traffic

The key here is to calculate the sample desired sample size before you run the test at all. There are many A/B test sample calculators online. Basically, you need to go in with an idea of your baseline conversion rate, and then the minimum uplift that you wish to detect. These numbers will allow you to calculate your ideal sample size for a test.

However, note that your sample size is essentially predetermined in the process of A/B testing emails, as you are sending an email out to a pre-populated list, of course.

Like with traditionally controlled experimentation, identifying just one variable will help you more clearly understand the results of the testing. For most businesses, it can be more beneficial to successively run several tests as opposed to building the infrastructure to test multiple tests at the same time. You may want to kill two birds with one stone. Unfortunately, this doesn’t work in the world of testing. You would essentially be looking in two totally different directions, shooting to see which bird you hit successfully.

It is also not ideal to run multiple A/B tests if it’s likely that they have an effect on each other. It may be tempting to speed up your testing efforts, but muddling your results is not worth the time saved here.

There are immense benefits to using A/B testing as a way to bolster your marketing strategy with some objective insights. Making room for testing will be an important part of any business’ marketing success. Of course, like anything else, it will take trial and error to make sure that you are going about your testing in the right way.

A/B testing is a huge part of making your marketing strategy more effective, so it’s important not to feel intimidated by it– especially if you have the tools to help you do it (in just a few clicks!). Anyone can make great content with the proper tools. Have any more questions? Reach out to our team here to learn how you can automate your A/B tests.