Optimization of direct response video advertising conversion in marketing strategies of direct-to-consumer brands

Abstract

The relevance of the study is determined by the growing role of video advertising in the digital environment, the intensification of competition in performance-oriented marketing, and the increasing requirements for the validity of managerial decision-making. The increasing complexity of audiovisual content structure and the dependence of its effectiveness on algorithmic content distribution mechanisms necessitate the development of scientifically grounded approaches to optimizing the conversion of direct response video advertising in the marketing strategies of direct-to-consumer brands. Purpose. The purpose of the study is to enhance the effectiveness of conversion of direct response video advertising in the marketing strategies of direct-to-consumer brands through the development and application of scientifically grounded approaches based on multimodal content analysis and data-driven decision-making models. Methods. The study applies methods of analysis and synthesis to generalize theoretical approaches to conversion formation and optimization; systematization to identify key parameters of video content; comparative analysis to assess the influence of various content characteristics on consumer behavioral responses; and logical generalization to develop methodological approaches and practical recommendations. Results. The essence of conversion as a result of the coordinated interaction of semantic, visual, and temporal parameters of video content has been investigated. It has been revealed that the effectiveness of video advertising is determined not by isolated characteristics but by their integrated interaction and alignment with audience expectations and digital environment conditions. It has been proven that the use of multimodal analysis and systematic testing of creative solutions increases the accuracy of content effectiveness evaluation, reduces uncertainty in decision-making, and enables adaptive optimization of advertising campaigns. Conclusions. It has been substantiated that improving the effectiveness of conversion optimization is achieved through the implementation of closed-loop analytical systems, enhancement of performance evaluation frameworks, and integration of analytical and creative processes. It has been established that key limitations include insufficient model interpretability, limited data reliability, and the inadequacy of traditional metrics in reflecting the complexity of conversion processes. Prospects for further research. Further research is associated with the development of quantitative methods for evaluating the effectiveness of multimodal content, improving the transparency of analytical models, and exploring the scalability of optimization systems under conditions of dynamic changes in the digital environment.