6 A/B Testing Tips for More Success in Experimenting

1. What is A/B testing?
2. What types of A/B tests are there?
3. What can be achieved with A/B testing?
4. 6 Tips for Successful A/B Testing
5. Best Practices of Successful A/B Tests: How You Should Proceed
6. Which tools can be used to apply the tips for successful A/B testing?
7. Conclusion

The theory of A/B testing sounds simple: You compare two variants of a content and the better one is kept for the future. What you should definitely consider when planning A/B testing and how you can catapult your conversion rate upwards with targeted experiments, you will learn in this article.

What is A/B testing?

A/B testing refers to the comparison of two variants of a system (for example, a website). By randomly playing variant A and B, it is determined which version performs better.

With the help of a statistical analysis, you determine which one better achieves your previously defined goal after reaching a certain sample size. A/B testing is an integral part of optimizing the conversion rate.

In this article, you will learn more about the basics, how to implement your A/B testing correctly

What types of A/B tests are there?

A/B tests are carried out in online marketing not only on websites, but are also used in advertisements, app content or emails as a tried and tested means of boosting the conversion rate. This article focuses primarily on optimizing websites, the tips and principles can also be easily transferred to other areas.

In addition, A/B tests can be divided into three categories.

Classical A/B test

In a classic A/B test, two (or more) variants of a page are tested under the same URL. Visitors are randomly directed to a version. It is important to test only individual elements such as headings or buttons in order to gain reliable insights and determine precise effects of individual changes.

Redirect test

The redirect test redirects part of the traffic to one or more other contents (for example, another URL) and thus compares whole contents (such as landing pages or entire websites) with each other. Often, the redirect test is also called Split Test, but in some providers the term Split Test also refers to the standard A/B test.

Multivariate Test (MVT)

While the A/B test tests the changes to exactly one element, multivariate testing allows for simultaneous testing of multiple changes, such as headlines, images, and buttons.

What can be achieved with A/B testing?

With the help of A/B testing, you can test and optimize almost all content on your website. Typical examples are:

• Titles and headings

• Formulation of the call-to-action

• Buttons

• Pictures

• Prices

• Forms

• Navigation and menus

• Page structure

But change for the sake of change should not be the motivation behind your A/B tests. Instead, the overriding goal should always be the Conversion Optimization. Because what is the use of the most beautiful or innovative website, if it does not fulfill its main task, namely the conversion of visitors into customers? In the following, we will discuss the central goals of Conversion Optimization and show how A/B testing can play a key role in this.

More direct sales

You run an A/B test in your online store and find out that a product video instead of a product image leads to 20 percent more purchases. The conversion rate thus has a direct influence on your sales and ensures that you get more out of your website visits.

Many site operators focus heavily on increasing spending on paid advertisements to generate more traffic, while simple changes on the website can have a much stronger effect on sales.

More leads

Your newsletter is one of the most important sales channels? Then you are understandably interested in having as many subscribers as possible. By optimizing the Subscription form for your email newsletter regularly through A/B testing, you can increase your email reach without increasing traffic.

More efficient advertisements

By A/B testing your online ads, you can find out which messages, images or call-to-actions are most appealing to your target group. Imagine investing in two different ad versions and discovering that one test variant has a 30 percent higher click rate. This means not only that you get more traffic for every euro invested, but also that the marketing budget is used more purposefully and efficiently.

Improving User Experience

A/B tests can not only have a hard conversion goal, such as fewer shopping cart abandonments, but can also be used to improve user friendliness. Through various experiments, you can find out whether a redesigned menu or a simpler structure increases the duration of stay on your site.

As a complement to qualitative A/B tests, where it is always about confirming a hypothesis after a sufficient level of confidence, you can also integrate user experience studies such as the analysis of mouse movements or the user journey into your marketing.

6 Tips for Successful A/B Testing

To ensure that your conversion testing (or also your customer experience testing) runs optimally, we here provide 6 tips for planning and conducting successful A/B tests.

1. Prioritize the tests correctly

The possibilities for A/B testing are huge. Buttons, headlines, images, menus, or colors - with the multitude, you can quickly lose track. As tempting as it may be to quickly set up a simple test for the background color of your homepage: Does this test really help you achieve your goals? Or should you rather focus first on formulating a sharp and convincing call-to-action?

Not all changes have the same impact on the Conversion Rate. Before you start testing, you should think about which changes are likely to have the greatest impact on your visitors and their behavior. So set clear priorities and focus on the tests that offer the most added value.

2. Test only one change at a time

In A/B testing, you should also resist another urge: Testing several changes at the same time to see results faster. However, testing multiple elements at once can skew the results. Is the increased average shopping cart value per visitor due to the more prominently placed product descriptions or to the newly introduced chatbot for answering questions?

Yes, more complex scenarios such as multivariate tests or multi-page experiments are valid, but especially when you're just starting optimization, try to limit yourself to one tested change.

A carefully conducted test with clear results is much more valuable than several simultaneous experiments with results that are difficult to interpret.

3. Set up the tests statistically correctly

The centerpiece of successful A/B tests is a clear goal setting and a clean statistical preparation. Consider what you want to achieve, and on this basis formulate a hypothesis. Then you implement the changes in your A/B testing tool and test until the sample size is large enough and statistical significance is achieved. Most tools help you set up and notify you when meaningful results are available.

4. Use segmentation

Website visitors can show strong differences in their user behavior. For this reason, it can be useful to limit your tests to individual user groups (for example, smartphone users, women, or visitors who came to the page via the Google search).

By directing tests towards specific segments, you can gain much deeper and nuanced insights and provide tailored experiences for different groups.

Again, don't complicate the testing! Does it bring you closer to your revenue goals by testing how female visitors over 45 with an Apple smartphone from Lower Saxony react to an alternative headline? Not to mention that such tests probably need to run for a very long time to reach a sufficiently large case number.

5. Consider external factors

For all the advantages that data-driven marketing with effective A/B testing has: Sometimes external factors can distort results and lead to wrong conclusions.

Holidays, seasons, current events, or even other marketing campaigns of yours can change the behavior of your users and thus distort the result. A typical example: At the beginning of the month, many online shops can record a dramatically increased conversion rate. However, this is usually not due to the grand new shop design, but simply the fact that it is easier to shop with a freshly replenished bank account after salary payment.

Therefore, when evaluating your tests, always check whether there were external influences during the test period and whether these may have influenced the results. If necessary, you can then repeat the test later to make sure that the results are actually due to the changes and not to external influences.

6. Do not neglect evaluation and documentation

For many marketers, the A/B test is over as soon as the tool switches to "green" and the changes are confirmed. After that, these are implemented and the next experiment is rolled out. However, a thorough evaluation and documentation of the test results are crucial in order for you to benefit from your gained insights in the long term.

A detailed analysis may not only show which changes were successful, but also the reason for it. Be sure to share the results with the other teams so that these things are taken into account when creating future content.

Often, A/B tests can also be avoided if a comparable experiment has already been carried out in the past and has already been forgotten. Clean documentation ensures much more efficient use of your test resources.

Best Practices of Successful A/B Tests: How You Should Proceed

The following procedure has proven effective for conducting successful A/B tests.

1. Consider what you want to test

In the first step, consider which element you want to test and improve. Should it be about the subject lines of your next newsletter? Or do you want to adjust your contact form? You should also have in mind what goal you want to achieve (for example, a better opening rate or a higher conversion rate for contact requests).

2. Hypothesis

Then you formulate a clean hypothesis. For example, it might look like this:

"If I insert an emoji in the subject of the newsletter email, then the opening rate increases, because users better perceive the message due to its more conspicuous representation."

3. Correctly set up the test technically

In your A/B testing tool, set up the test, create Variant B, and double check that you have correctly adjusted parameters such as runtime, confidence level. For a test on the website, it is best to ensure in a private browser window once more that both variants are played.

4. Evaluate result

Once the test is completed, you should not rush to implement the more successful variant. Think again whether the results are really meaningful and due to the changes.

Which tools can be used to apply the tips for successful A/B testing?

We recommend that you definitely carry out A/B tests with a professional tool. These tools help you in the creation, execution, and evaluation of experiments. In most tools, you don't even need programming knowledge, nevertheless it is enormously advantageous if you can develop yourself or have a developer in the team who can do this for you.

Here is a small selection of tools for your A/B testing:

ABlyft

Kameleoon

Varify.io

trbo

EASY2

Dynamic Yield

NOSTO

A complete overview of our A/B Testing category can be found at OMR Reviews.

Conclusion

A/B testing is a great way to learn more about your customers and improve your conversion rate. If you implement the mentioned tips, nothing stands in the way of successful A/B testing.