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A/B testing can also be used by product developers and designers to demonstrate the impact of new features or changes to a user experience. Product onboarding, user engagement, modals and in-product experiences can all be optimized with A/B testing, as long as goals are clearly defined and you have a clear hypothesis.
What are the limitations of a B testing?
Another limitation of A/B testing is that it requires the tester to extend the results indefinitely into the future. Traditional A/B tests assume an unchanging world view and don't take into account changes in trends and consumer behavior and the impact of seasonal events, for example.
Which variable can be tested using the A B testing tool?
Essentially, A/B testing eliminates all the guesswork out of website optimization and enables experience optimizers to make data-backed decisions. In A/B testing, A refers to 'control' or the original testing variable. Whereas B refers to 'variation' or a new version of the original testing variable.
