The role of motion analysis in enhancing personalized marketing experiences in e-commerce platforms: A biomechanics and biology-integrated perspective
Abstract
This paper explores the role of motion analysis in enhancing personalized marketing experiences within e-commerce platforms. Personalized marketing has become a vital strategy in e-commerce, allowing businesses to tailor content and recommendations to individual users based on data such as browsing history, purchase patterns, and customer preferences. Motion analysis, which tracks and interprets physical interactions such as mouse movements, scroll patterns, and gestures, offers an additional layer of real-time behavioral insights. This paper examines how motion data can lead to more accurate product recommendations, adaptive user interfaces, and dynamic marketing strategies. Furthermore, it highlights the key benefits, including improved customer engagement, conversion rates, and satisfaction. This study also explores the biological mechanisms underlying motion analysis. It investigates how motion analysis reflects users’ physiological responses and psychological states, integrating these insights with personalized marketing strategies. Additionally, the paper examines how motion analysis data can enhance the understanding of users’ biological characteristics, such as fatigue and attention, and how these insights can be applied to create more effective personalized marketing approaches. Moreover, the paper identifies the challenges associated with implementing motion analysis, such as the complexity of integrating real-time tracking tools, data processing limitations, and privacy concerns. The integration of motion analysis with AI and machine learning is explored as a promising avenue for the future, offering predictive and adaptive personalization techniques that can revolutionize the user experience in e-commerce.
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Copyright (c) 2025 Liming Liu, Mi Zhang, Xingchang Fan, Hui Cui, Chengnan Li
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