This study delves into how big data analytics can be used to predict consumer behavior and optimize marketing strategies. Our approach combines sequence pattern mining and time series analysis to reveal consumer purchasing patterns and trends on e-commerce platforms. By examining a user's browsing history, purchase history, and feedback, we can identify preferences and predict future behavior. Experimental results show that recommendation accuracy and customer satisfaction are significantly improved. In addition, real-time big data analysis helps dynamically adjust marketing strategies and improve resource allocation efficiency and advertising effectiveness. This study provides a powerful framework for leveraging e-commerce big data to drive intelligent decision-making and improve market competitiveness.