Predicting future brand value: The role of machine learning monitoring

Data-driven strategies have become essential for brand valuation optimization in today’s rapidly evolving virtual economy, where organizations face increasing pressure to gain real-time, accurate insights to maintain a competitive edge. The purpose of the study examine the impact of machine learning in monitoring key market factors to predict future brand value, addressing the growing need among industry professionals for tools that enhance strategic decision-making. From April to September 2024, a purposive sample of 350 upper-level brand managers and sales marketing directors from various Jordanian companies targeted due to their direct involvement in brand evaluation and marketing strategy. 229 completed and valid responses were collected through a self-administered questionnaire. The data analyzed using AMOS software and Structural Equation Modeling (SEM) to test the research hypotheses. Results indicated that all proposed factors significantly influenced the prediction of future brand value, with purchase frequency (β = 2.681), industry trend monitoring (β = 2.228), consumer behavior (β = 0.353), and social media metrics (β = 0.345) showing statistically significant effects (p