Core Technological Breakthroughs and Applications in Brand Marketing Information Systems

Abstract

Addressing the industry pain points of “difficult multi-platform data integration, low marketing prediction accuracy, and high technological access costs” in the brand marketing information systems of small and medium-sized enterprises (SMEs), this paper develops two core technologies. First, a multi-source data automatic adaptation middleware is proposed, which, through a “preset template library + dynamic field mapping + incremental synchronization” design, enables one-click access to data from over 10 mainstream marketing platforms. The adaptation efficiency is improved by 14 times compared to traditional solutions, with a synchronization error rate of less than 0.5%. Second, an improved LSTM marketing prediction model is introduced, which incorporates entropy weight method to calculate industry feature weights, addressing the poor cross-industry adaptability of traditional models. This model achieves a prediction accuracy of 92% in the fast-moving consumer goods, catering, and retail industries.