In our last post we talked about Experimentation Teams, which one is best for your company? Today, within the special series at the end of optimize, we are going to leave the organizational layer and go down to a more technical subject, but no less important: Test Types. The most common type of test is the so-called A/B Test, which for many professionals has become a metonym. However, experimentation tools offer other types of testing that can go beyond the A/B view and bring much more insights to your business. In this post we will discuss the different types of tests and what are the advantages and disadvantages of each.Testes A/B/n As mentioned at the beginning of the post, this format is the simplest and the most used when we talk about experimentation.
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Its popularity can be associated with the easy interpretation and design of the experiment. In the case of A/B testing, the tool simply redirects the user. Between the original page, which you want to test, and its variants created according to a pre-established objective. It’s an excellent method to introduce the concept of experimentation Chinese Malaysia Cell Phone Number List culture within. A company that in a simple way can quantify the impact of Web Environment.Because it has few page variations, the A/B test result will always. bring statistical Greater number of variatiA/B tests are recommended for few page variations, they bring a view of the performance of the pages as a whole but do not make tangible the impact of the elements of the pages tested.
Multivariate Tests The logic
A simple element can be the reason for a variant to become a winner and this, depending on the test we Recommend multivariate testing. of multivariate tests is the same. As but in this case the experiment compares a larger volume of changes on the same page and reveals. More details of how each element performs together with the others EK Leads The multivariate test. The central objective of measuring the effectiveness of each design combination. According to a mapped business objective . As soon as the test has received enough traffic for a decision. The experiment reveals the most effective design combination for the Important for identifying elements and designs that optimize the .
