We have previously covered the following topics in our Marketing blogs: 3 reasons why your company should start blogging today and Facebook marketing 2019: 5 trends you should embrace'. Today you can learn more about A/B testing! Do you ever apply 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 a 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 component or improving the current component. 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, one serving as the control group. Both groups receive a separate version of the part from 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 parts that you can test are: e-mail campaigns, destination pages and discount offers.
A/B-optimization tests are used to try out 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. A/B-testing is usually used to test how different versions of one online marketing campaign perform. For example, the two groups see two different designs of a website or receive two variants of the same e-mail series.
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In an optimization test you usually compare the results from the number of opened emails, the click rate or conversions, but there are plenty of other metrics that 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 message with an image get more likes than a message without it?“ You can test all of this.
Since the tests measure public involvement or other results based on very small changes with little or no cost to each test, companies can perform many thousands of A/B-tests per year. The data from the tests then form the next campaign or change the current one.
Structuring an A/B-test
As with any good experiment, A/B-testing is rooted in the scientific method. How does this scientific method work again? Ask a question based on observation and research. Make a hypothesis about 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 a hypothesis and have done some background research into the current behavior of your target group using analyzes, it is time to design the test. Some factors to consider:
Changes per variation
How much do the two groups differ from each other? You can make many changes from the A version to B or just one. With some changes it may take longer to see results or results may not stand out as much as with a complete change. It is easier to follow the reactions and causes of the reactions in the case of small changes.
Metric for data
How do you measure the results? For example, if you test the effectiveness of the subject line of an email campaign, it makes sense to use the number of open emails. If you test a change in a campaign, hard sales, sign-ups or other forms of conversion provide the data.
What is the size and duration of the test? When testing something small such as a change in the call-to-action button on websites, the results will become clear very quickly.
Who are the test participants? If you know how the target group is segmented, you can perform A/B-tests on a specific part of the target group or set one part as the A group and one as the B group.
Get started with A/B-testing now!
A/B-testing is a valuable tool to get 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 test with low costs and low risk. For example a minimal change in the e-mail 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 that you are clear about the purpose of the test and how you will measure the results. Use the Google Optimize tool to set up an A/B-test easily and step by step.
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