AB Test Evaluation & Documentation

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After the test is performed and sufficient data is available, the chi-square test is applied.
The tests carried out should always be properly documented . This can prevent tests from being carried out multiple times, thus tying up valuable resources. The following content should be documented at a minimum:



test name
test period
hypothesis
used variant
Results and Conclusions
potential for financial gains per year
To evaluate the test results, you can use the tools that often offer a type of reporting and clearly show you whether the selected KPIs have improved in the test. To do this, you must refer back to the goals you anhui mobile numbers list defined at the beginning. Enter the results into the roadmap you created at the beginning .
6. Apply theory on the page

If the test was successful and can be applied to the population, the results should be put into practice . If the test is not significant, another test with a larger sample may be helpful.
7. Continue testing
Setting up and running AB tests - Further testing
You should n't stop after a successful test or even after a test with unhelpful findings and implementation . AB testing is a cycle in which you revise existing hypotheses and test new approaches or then approach a different hypothesis with a new focus.
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Tools for AB Tests
As in other application areas, there are a variety of different tools for AB testing for a wide range of budget sizes. In my experience, AB testing can be carried out quickly and easily using the following three tools.
Google Optimize is particularly suitable for getting started with the topic , as the tool is part of the Analytics360 suite and is integrated into Google Analytics. A Chrome plugin helps you create new tests. There are also different targeting options to choose from.
Another large and recommended provider is Optimizely. Various tests can be created here using a user-friendly interface. If your requirements go beyond the given functions, you can use the "Professional" offer. The price depends on the monthly traffic of the website.
AB Tasty is the third recommendation for a complete solution in the area of ​​conversion rate optimization . In addition to setting up tests, it can be used to define different user segments on the website or try out different banner formats. The tool also offers the option of conducting tests on mobile devices.