Why should you run A/B tests?
A/B testing compares two or more versions to determine not only which version performs better, but also whether a difference between two versions is statistically significant.
Companies today need to take a data-driven approach. They may think they understand the customer, but do they really? In reality, customers behave much differently than you think. Often, customers don't even know or understand why they make the decisions they do. They just do. So it's better to do a test than to rely on your intuition.
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With an experiment like an A/B test, you can compare two landing pages and find out what makes the user click the button or sign up for the newsletter. In version A, the call-to-action button can be green, and in version B, it's red. Or in version A you write PROMOTION and in version B you write FREE. Or you test different photos against each other. Or you change the position of the button. There are really a lot of possibilities. I think you understand what it's all about.
Before you start A/B testing, you need to determine your success criteria. What do you think will happen if you change an element to version B? Will it have an impact on the conversion rate? Will it make more people sign up for a newsletter?
Then divide your traffic into two parts. It doesn't have to be 50% / 50%, but you need to determine the minimum number of people you want to run your A/B test with to get statistically significant results.
Dieses Design Set ist ein Beispiel für eine fast perfekte Landing Page für einen 1-Produkt-Shop.
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Improve your website continuously
If version B performs better, make it your new version A. This way, your landing page will get better and better over time.
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Are A/B tests accurate?
There is still some room for error. For example, something could be broken in the backend and many other reasons. That's why you should always run an A/A test beforehand. If you get the same result, you can start the actual A/B test.
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A landing page should also load fast and have hardly any CLS. Just like the web pages we make.
