Efektivní A/B a multivariantní testování v prostředí globálního trhu

Thesis is focused on online content testing for the purpose of optimizing the performance of business and information channels in a global environment, i.e. where visitors come from different countries. This diversity causes different behavior of visitors, for example as the American perception of the content is entirely different from the Brazilian and French. Different perceptions and consumer behavior is caused by a different national culture in these countries. Therefore it is necessary or appropriate to test content for the purpose of optimizing on the local level. The simplest option is obviously to run the same test for each country separately. But that is extremely difficult in practice because of the duration of the test and human resources needed for test design, implementation, and evaluation. Therefore the aim of this thesis is to suggest modification of the general method used for testing the online content that will be sufficient for testing on the local level and will take cultural differences of each country into account, but yet also will be effective in terms of time and human resources consumption. Currently there isn't any publicly documented method which would cover this issue. The key of this modification is the segmentation of countries into groups based on similar national culture. Therefore the value of national culture has to be identified in some way and for this purpose it is possible to use model of the Dutch Professor Geert Hofstede, who identified six dimensions of national culture for each country and assigned them values. The benefit of this thesis is described modification of the testing method which is particularly suitable for companies operating on the global market or multiple markets simultaneously. This method, if it's used properly, is able to deliver growth of revenue while simultaneously reducing the consumption of human resources.