We previously covered the following topics in our Growth Hacking blogs: 'What is Growth Hacking and how do you use it?' and 'What is Hotjar and what do you use it for?'. Read more about A / B testing today! Do you ever use this test?


Almost every part of your marketing strategy can be seen as an experiment where the results determine the next move. When you implement part of your marketing strategy you can test what works and what doesn't. These findings can be taken into account when setting up the next part or improving the current part. Even the smallest experiments can tell a lot about what works and what doesn't.

What is A / B Testing?

But what is A / B testing then? When you perform an A / B test, you divide the target group or customer base into two groups, with one acting as the control group. Both groups receive a separate version of the part of your marketing strategy, you carefully monitor the performance of each version. By looking at the results, you can adjust your strategy if necessary and then test another element. Examples of items you can test include: email campaigns, landing pages, and discount offers.

Test optimization

A / B optimization tests are used to test how changes to a small part of an existing process affect customer engagement. The goal is to optimize the impact of that process and to achieve the best results with the lowest costs for your company. Typically, A / B testing is used to test how different versions of a single online marketing campaign are performing. For example, the two groups see two different designs of a website or receive two variations of the same email sequence.

Usually, in an optimization test, you compare the results from the number of emails opened, the click rate or conversions, but there are plenty of other metrics you can test and compare. 'Does a long subject line of your e-mail or a short subject line lead to more results?' "Does a green button or a red button get more clicks?" "Does a Facebook post with an image get more likes than a post without?" You can test all of this.


Since the tests measure public engagement or other results based on very small changes with little or no cost to each test, companies can run many thousands of A / B tests per year. The data from the tests then forms the next campaign or changes the current one.

Structure an A / B test

As with any good experiment, A / B testing is rooted in the scientific method. How does that scientific method work again? S.count a question based on observation and research. Hypothesise the answer to this question. Then formulate testable predictions, collect data, and use the data to measure the accuracy of your hypothesis. A Growth Hacker has an extra step here: adjust your test precisely based on the results achieved. Then test again, again and again ...

Once you have come up with a question and hypothesis and have done some background research on the current behavior of your target audience using analytics, it is time to design the test. Some factors to consider:

  • Changes per variation

How much are the two groups different from each other? You can make many changes from A version to B or just one. With some changes, it may take longer to see results or results may not be as noticeable as with a complete change. It is easier to follow the reactions and causes of the reactions with small changes.

  • Metric for data

How do you measure the results? For example, if you're testing the effectiveness of an email campaign's subject line, it makes sense to use the number of emails opened. When you test a change in a campaign, hard sales, signups, or other forms of conversion provide the data.

  • Test range

What is the size and duration of the test? When testing something small like a change in the call-to-action button on websites, the results will become apparent very quickly.

  • Segmentation

Who are the test participants? If you know how the audience is segmented, you can perform A / B tests on a specific part of the audience or set one part as the A group and one as the B group.


A / B testing now!

A / B testing is a valuable tool for getting the most out of your marketing strategy, whether on a small scale to optimize an email campaign or on a large one. Ready to try it?

Start small. For your first A / B test, choose a low cost, low risk test. For example, a minimal change in the email series, posts on social media or a button on the website. Starting with a small change has the advantage that you can quickly see the cause-effect result. It is also important to be clear about the purpose of the test and how you will measure the results. Use the tool Google Optimize to set up an A / B test simply and step by step.


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