Web Advertising Content Personalization Using Artificial Intelligence

User experience is the most important part of any website. In the past, users of multimedia content were saturated with a generic offer, and today they expect customized content. Artificial intelligence (AI) provides opportunities to serve up the right advertising content at the right time for individual website users. But even though AI can enable dynamic optimization and personalization it has limited creating capacity. Creating capacity depends on past experiences, observations, and behaviour on one hand, and limitations and restrictions posed by AI algorithms on the other hand. Therefore, a space has opened up to generate a model that is capable of copying the logic of individual user steps to create intelligent advertising content in real time that reaches the user through multimedia channels. To achieve this, it is necessary to integrate personalization technologies that operate on the principle of ontology and semantically based information. The sequence diagram will connect the user, multimedia advertising content and database through modelling, filtering, and content customization. A study of the parameters of personalization of multimedia content was conducted in order to improve the user experience through multiple simulation modelling. A series of smaller reversible experiments were started within one criterion, i.e., the simulation model was changed by one parameter. A font was singled out as a key structural element, and a prototype of a variable font was tested in a responsive web environment, using CSS technology. The data was analysed to work out exactly which combination of these different variables produces the best result by A/B test. The results represent the score of particular observations and demonstrate the possibility to perform the optimal visual elements combination as important part of advertising content.