With an A/B test, a website owner can test small changes to their website to see if the changes are more successful than the previous version. This way websites can be optimized step by step.
With an A/B test, webmasters have the opportunity to continuously optimize websites by comparing two website versions (A and B) and making small adjustments each time.
Afterwards, an evaluation is carried out by means of a web analysis, and the more promising version is determined.
Application examples for an A/B test
A/B testing is used to measure the success of two different versions of a website. This can be applied in different areas.
- Test a new web design: When a new template is created, you can find out whether users prefer the new web design or the old design. The two different design versions are put online and tested to see which version users like better.
- Testing the improved functions: If navigation and user guidance are to be improved or new functions (such as filters or search functions) are to be tested, these can be evaluated with the split test.
- Testing the conversion rate of individual pages: If a website owner is not sure whether a page with a different design could not achieve a better conversion rate, they can create a different design, put it online and find out which one works better. The effect of images and videos, the structuring of contact forms, the amount of text or special discounts can be tested with A/B tests.
How an A/B test works
When changes are made to a website, it directly affects traffic. Both the dwell time and the bounce rate may change significantly. Because positive changes in KPIs do not always occur, A/B testing can be used to achieve incremental improvement.
When running A/B tests, incoming traffic is split – hence the other name split test – and half of the visitors are redirected to the new page. This division is done arbitrarily and without the user noticing it. Finally, it can be judged whether version A or version B shows better results.
In this test procedure it is important that both versions are tested simultaneously. Visitors to the website must alternate between version A and version B in the same time period. If the versions are tested at different times, the result would be distorted. How many visitors visit a website and what their user behaviour is depends not only on the website itself, but also on external factors such as the time of day.
For SEO, A/B tests are especially important for OnPage optimizations. They provide empirically provable data on how a website can be improved.
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