Short-form video (SFV) marketing has become a prominent format in digital advertising by combining compressed audiovisual storytelling, feed-based discovery, algorithmic visibility, and rapid audience interaction. This study examines how content- and creator-related factors shape consumers’ value-based responses to short-video marketing and how these responses influence purchase intention. Data were collected through an online survey of 409 respondents in Bulgaria. The analytical design integrates descriptive statistics, clustering, sentiment analysis, partial least squares structural equation modeling (PLS-SEM), and machine learning (ML) prediction to examine both explanatory relationships and predictive performance. From a business intelligence perspective, the proposed workflow transforms structured survey responses and open-ended consumer feedback into actionable insights for audience segmentation, consumer-response prediction, campaign prioritization, and e-commerce decision support. The final structural model treats creating shared values (CSV) as a value-based attitudinal response to SFV marketing. The results show that clarity, willingness to use, similarity, empathy, and likability positively affect CSV, which in turn positively affects purchase intention. The findings indicate that short videos are most persuasive when they communicate clearly, feel relatable, create emotional resonance, and reduce friction in audience engagement. ML models further suggest that the selected perception variables have strong predictive value for consumer responses in this sample. The study contributes to digital persuasion, e-commerce analytics, and business intelligence research by offering an integrated empirical framework for assessing short-video marketing effectiveness.