Research on Transformation Driven by Machine Learning-Based Dynamic Marketing Strategies
In today's rapidly evolving business environment,companies face highly dynamic and uncertain markets,making the adaptive adjustment of marketing strategies crucial for their survival and development.This paper selects 227 wholesale and retail enterprises from 2009 to 2024,using the CSMAR Guotai An database as the data source.It employs multiple machine learning regression models(XGBoost,LightGBD,SVR,random forest regression,and linear regression)to explore how enterprises can capture new opportunities for market adjustment in dynamic market environments.By thoroughly reviewing relevant theories and combining rigorous empirical analysis,this study aims to reveal the impact mechanism of relevant financial indicators on business performance.It provides a solid theoretical basis and practical guidance for companies to flexibly adjust their marketing strategy portfolios based on their financial conditions,ultimately helping enterprises achieve sustainable development in the face of intense market competition.
万方数据
维普
