A/B testing is a way to optimize an interface by analyzing user experience (UX). Most of the assumptions of the adjustment scheme are changes in the content of the page. The following are common test variables for Kentico A/B testing:
A/B testing applications include web pages, application interfaces, and advertisements. Some companies also use A/B testing to analyze the impact of new products on users. The advantage of using A/B testing is that it can be used for small surveys. Companies can use A/B testing to understand user preferences for new services, new ads, and new products, and then make changes to web pages or show ads on a large scale. During testing, you should rely on several conversion metrics for your research:
From the definition of the A/B test, you can see that it focuses on the test of grouping users with the same attributes in one time dimension. The uniformity of time effectively avoids the influence caused by factors such as time and season, and the similarity of attributes. This minimizes the impact of other factors, such as geography, gender, age, and others on performance statistics. According to the test results, it is determined to release a new version, adjust the separation coefficient to continue testing, or continue to optimize the iterative scheme for re-designing the test if the test results are not achieved.
It is difficult to use the A/B test method to find out the effect of each variable on the results and measure the effectiveness of each program. If a page is testing several variables, you need to use multivariate testing, which is a conceptually different testing method, and for greater efficiency, a large amount of traffic is required. Let's find out why it is convenient to conduct such a study with the Kentico App. Improve your operational capabilities through a closed loop of hypotheses, testing, analysis, and improvement. Provide personalized product recommendations based on geography, gender, age, equipment, purchases, and purchase history.
Using the technology of big data mining, statistical analysis of user attributes and behavior characteristics, scientifically and accurately determine the winning version of the AB test and find out the reasons for the differences. Comprehensively and accurately evaluate the effectiveness of advertising channels, creative ideas, and keywords to determine the best advertising solutions.
The most obvious benefit of introducing an experimental culture is the ability to improve your product and increase revenue. But there are indirect advantages of testing, which are manifested when testing becomes rooted in the corporate culture.
For example, you lose HiPPO in experimental culture, and A/B testing – a surefire way to understand the essence of the solution without relying on someone else's instinct.
With such procedures, more of your ideas will see the light of day in the form of tests, and will not be killed on boards and in presentations. When your ideas are easy to try, your team may stop talking abstractly about things that haven't happened yet and instead talk about the results and next steps. Finally, colleagues will be highly motivated because they will see their ideas in the real world. Try and succeed just now!