The product lifecycle model and its managerial counterpart, product lifecycle management (PLM), are frameworks that describe how products evolve and should be managed over time. While widely used for understanding and managing products, they face limitations that hinder their applications beyond the design and introduction stages. The digital twin (DT) paradigm addresses some of these challenges by creating real-time virtual representations of physical objects. This paper expands on this concept by introducing cognitive digital twins (CDTs), which incorporate human-in-the-loop (HITL) support, to enhance lifecycle management. To address a noted gap in marketing and lifecycle performance research, the study uses automobiles as a case study to demonstrate how CDTs can simulate vehicle behavior, predict and optimize performance, and improve reliability, sustainability, and customer satisfaction. Additionally, the integration of enabling technologies such as fog computing and blockchain is highlighted as a significant advancement for scalability, security, and real-time data processing. Ultimately, CDTs promise to drive greater innovation and efficiency across the automotive industry.