Previously, we have discussed 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?'. Today you can read 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 perform 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 most small experiments can tell a lot about what works and what doesn't.
What is A/B testing?
But what is A/B testing? When you run an A/B test, you divide the target audience or customer base into two groups, with one acting as the control group. Both groups receive a separate version of the part from your marketing strategy, the performance of each version is carefully tracked. By looking at the results, you can adjust your strategy if necessary and then test another element. Examples of parts you can test include: email campaigns, landing 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 business. Typically, A/B tests are 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 email series.
Usually, with 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 that you can test and compare. 'Does a long subject line of your email or a short subject line lead to more results?' 'Will 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 minor 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? Scount a question based on observation and research. Draw up 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've come up with a question and a hypothesis and did some background research on your target group's current behavior using analyses, it's time to design the test. Some factors to consider:
- Changes by variation
How much are the two groups different? 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 with a complete change. It is easier to follow the reactions and causes of the responses in case of small changes.
- Metric for data
How do you measure the results? For example, if you test the effectiveness of an email campaign's subject line, it makes sense to use the number of emails opened. If you test a change in a campaign, offer hard sales, sign-ups, or other forms of conversion 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 clear very quickly.
Who are the participants of the test? If you know how the audience is segmented, you can run A/B tests on a specific part of the audience or set one part as the A group and one as the B group.
Now A/B testing!
A/B testing is a valuable tool to get the most out of your marketing strategy, whether it's 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 and 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 result. Furthermore, it is important that you need to be clear about the purpose of the test and how you will measure the results. Use the Google Optimize tool to easily and step by step set up an A/B test.
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