Optimizing the Environmental Sustainability of Marketing Efforts Using Distributed Digital Twins

Abstract

This Paper investigates the integration of digital twins (DTs) into marketing, exploring their potential to transform the field by bridging technological innovation with strategic marketing practices. Digital twins, sophisticated virtual models that mirror physical objects or systems, leverage Internet of Things (IoT) technologies, Artificial Intelligence (AI), and data analytics to simulate, analyze, and optimize marketing strategies in real time. The research question centers on how DTs can enhance decision-making, consumer engagement, and sustainability in marketing efforts. Employing a comprehensive methodology that blends theoretical analysis with practical case studies, the paper examines the synergistic effects of IoT, AI, and data analytics in developing and implementing DTs. It highlights the operational benefits, such as improved product sustainability, market adaptation, and personalized marketing campaigns, while also addressing the significant challenges of data complexity, system integration, and real-time data synchronization. Through examples of DT applications, the study showcases the tangible advantages of DTs in marketing, including optimized sustainability practices and enhanced consumer satisfaction. Despite facing technical and interdisciplinary collaboration challenges, the paper concludes that DTs offer a promising future for marketing, marked by advancements in technology and a shift towards more sustainable and consumer-centric strategies. It calls for continued research and collaborative efforts to fully realize the potential of DTs in creating effective, sustainable, and ethically responsible marketing practices.