Research on Cigarette Consumption Demand Mining and Product Iterative Innovation from the Perspective of Big Data

Against the backdrop of accelerated digital transformation, big data technology has provided a new path for the tobacco industry to accurately grasp consumer demand and optimize product iteration. Based on the perspective of big data, this paper analyzes the core dimensions and implementation paths of cigarette consumption demand mining, explores the strategic directions of data-driven product iterative innovation, and demonstrates the application value of big data combined with industry practice cases. The research shows that by integrating multi-source consumption data and mining scenario-based demands, the adaptability between cigarette products and market demands can be effectively improved; product form, taste, harm reduction technology and packaging innovation oriented by demand insight can help tobacco enterprises break through development bottlenecks and achieve high-quality development.