Predictive Marketing: From Data Analytics to Reading Customer Intentions Before They Think - Nehme, Ali Aboudi (Universitas Muhammadiyah Sidoarjo, 2026)
General Background: Modern marketing increasingly depends on data-driven approaches to understand shifting consumer behaviour. Specific Background: As predictive tools become central to customer-focused strategies, challenges remain in achieving accurate intent recognition and ensuring ethical data use. Knowledge Gap: Few empirical studies examine how predictive marketing, intent detection, and satisfaction jointly shape purchase intentions. Aims: This study evaluates how predictive marketing supports intention recognition, enhances satisfaction, and strengthens future purchase intentions in Kkalci Mobile Manufacturing Company. Results: Data from 250 respondents show high levels of predictive marketing use, effective intent reading, strong satisfaction, and high purchase intention, with all variables significantly correlated. Regression analysis indicates that predictive marketing, intent recognition, and satisfaction explain 71% of the variance in purchase intentions. Novelty: The study offers an integrated empirical model linking predictive marketing with behavioural intention pathways in a manufacturing context. Implications: Findings underscore the strategic value of predictive analytics for targeted decisions, personalised marketing, and loyalty building, while emphasising the importance of responsible data governance.Highlight : The results confirm strong links among predictive marketing, intent recognition, satisfaction, and purchase intention. These variables jointly account for most variations in customers’ future purchasing decisions. Predictive marketing supports improved customer experience and repeat buying, while ethical safeguards remain essential. Keywords : Predictive Marketing, Customer Intent Recognition, Customer Satisfaction, Purchase Intention, Marketing Performance