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Predictive Analytics for Risk Reduction in Vehicle Supply Chain Management

Mohd NavedJaipuria Institute of Management, IndiaS. DhivyaDepartment of Commerce, Faculty of Science and Humanities, SRM Institute of Science and Technology, Chennai, IndiaK. MahajanD.Y. Patil College of Engineering and Technology, IndiaPradeep SharmaNational Institute of Technology, Kurukshetra, IndiaNargiza KuzievaTashkent State University of Economics, UzbekistanMuralimohan Gurusamy
ABI

Аннотация

The use of machine learning for customer profile, predictive analytics, and cluster analysis, AI-powered audience segmentation is revolutionizing campaigns to raise awareness of car safety. By identifying target demographics, driving patterns, and risk variables, this strategy guarantees highly customized marketing campaigns. AI can send customized safety messages by grouping audiences according to safety concerns using behavioral modeling and clustering algorithms. Proactive outreach is made possible by predictive analytics, which forecasts engagement levels and accident risk probability. By improving precision marketing, this technique guarantees that safety awareness messages are seen by the appropriate people at the appropriate moment. Additionally, dynamic content adaption and automatic campaign optimization are made possible by AI-driven segmentation, which maximizes impact. Through the integration of AI-powered data analytics, real-time engagement tracking, and automated outreach, companies can raise public awareness of car safety and drive meaningful behavioral change.

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