The following three conditions must occur:

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The main A/B testing platforms on the market present this data automatically during the experiment. The data must be consolidated , that is, there must be no fluctuations in the graph in the last time period. If the data is, in fact, statistically significant, but there are continuous variations, the winner cannot be defined mathematically.


Finally, the result must be significant : if the variation is less than 2% of the results, there is no point in determining a winner. Defining the Winner in the A/B Testing Process May he be a winner forever To verify that the test has determined an actual winner, the A/B test should be repeated and reiterated over time , possibly on smaller audience segments (10% of visitors).


In this way, you will have the almost chinese overseas british phone number list mathematical certainty (we speak of “almost” because we are still in the realm of statistical estimates and not absolute truths) of having chosen the winning variation. In any case, a winner is not always determined by an experiment on a website.


In some cases, the hypothesis may be incorrect; in others, the variation insignificant. In these cases, it is necessary to start from the beginning, defining a new element to vary and repeating the process. Every mistake, after all, is just “one more step towards the truth”.


A/B testing isn’t the only type of experiment you can run on a website. There are several more advanced tests you can implement that fall into two main categories: A/N tests , where there are more than two variations of the element (there are therefore more than one “experimental group”).