INTEGRATION OF BIG DATA INNOVATION AND TRADITIONAL MARKETING THEORY: AN ECONOMIC ANALYSIS OF ENHANCING MARKET COMPETITIVENESS IN THE FOOD AND BEVERAGE INDUSTRY

Abstract

The rapid advancement of big data technology has significantly transformed the traditional marketing paradigm. Leveraging this technology to gain precise insights into consumer demand, enhance product positioning accuracy, and optimize communication efficiency between enterprises and consumers has become a focal point of interest. This paper constructs a big data marketing model by integrating big data technology with the theoretical frameworks of traditional marketing: the 4Ps (product, price, place, promotion), 4Cs (consumer, cost, convenience, communication), and 4Rs (relevance, response, relationship, return). The model is applied within the food and beverage industry from three key perspectives: analysis of consumer behavior, development of personalized marketing strategies, and fostering product innovation. To validate its effectiveness, the leisure food industry is chosen as a case study. The findings demonstrate significant impacts of big data marketing in enhancing the precision of enterprise marketing efforts, driving innovation in product development, and strengthening the alignment between enterprises and consumers. Consequently, the theoretical framework of big data marketing holds promising prospects for market promotion and broader adoption.