Machine Learning and Ai in Marketing–Connecting Computing Power to Human Insights - Pooja Nagpal, C. Vinotha, Lucky Gupta, Gunjan Sharma, Khyati Kapil, Vijay Kumar Yadav, Akhil Sankhyan (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Researchers’ interest in artificial intelligence (AI) agents that are driven by machine learning methods has been piqued as a result of the rapid changes that these technologies are creating in the marketing sector. In the framework of this article, we investigate and argue in favour of the use of methods related to machine learning to marketing research. We provide a comprehensive overview of the common aims and methodologies of machine learning and compare them to the traditional statistical and econometric approaches that are employed by marketing professionals. In this research, we claim that machine learning approaches can analyse vast volumes of unstructured data, make accurate predictions, and have model structures that are adaptable. In addition to being difficult to understand, these methodologies are also unclear with reference to the models. We provide scalable and automated decision support capabilities, which are essential for business managers. We investigate the most important business trends and practices that are being driven by AI, as well as academic marketing research that combines machine learning approaches. Most significantly, we provide both a detailed plan for further research as well as an extensive conceptual framework.