A novel approach to target audience analysis: synthetic recipients

the purpose of this study was to describe a methodology for analyzing the characteristics of the target audience of advertising messages using synthetic recipients powered by artificial intelligence technologies. It includes the collection and analysis of primary data about the target audience, the creation of synthetic recipients for both broad and narrow segmentation, the development of a questionnaire to refine audience preferences, and conducting surveys with synthetic recipients. The practical application of this methodology is relevant for testing advertising hypotheses, selecting communication channels, forming personalized messages, and improving the effectiveness of advertising campaigns. The study concludes that the advantages of applying this methodology include high implementation speed and economic efficiency. Synthetic recipients can partially compensate for the lack of data about the target audience of advertising messages. However, their use has certain limitations, such as strong dependence on the quality of input data, the absence of psychological and emotional factors, the potential for algorithmic errors in creating synthetic recipients, and a lack of contextual flexibility. Nevertheless, the results of the conducted research demonstrate that under conditions of limited access to target audience data, as well as the inability to implement large-scale advertising studies, the application of a methodology for analyzing target audience characteristics using AI-powered synthetic recipients opens up new opportunities for gaining a competitive advantage.

advertising, advertising research, artificial intelligence, target audience analysis, personalization of advertising messages, contextual advertising