ON LEVERAGING GENERATIVE ARTIFICIAL INTELLIGENCE (GENAI) FOR BEHAVIOR LEARNING AND PERSONALIZED MARKETING OPTIMIZATION

Abstract

Generative AI (GenAI), especially GPT-3.5-turbo, has transformed the e-commerce marketing process because it offers personalized learning experiences and improves the customer experience. In this paper, we discuss the use of GenAI in consumer behavior analysis and the development of customized marketing strategies. It has been observed that behavioral characteristics, such as purchase frequency and expenditure, are essential for customizing marketing activities, and that there is a strong correlation between these variables and customer satisfaction. The prediction of customer satisfaction was used as a Random Forest classification model and the results have shown that the model can predict customer satisfaction with an accuracy of 97% with the influence of purchase frequency and total spend being the most influential predictors. GenAI is an excellent way to automate content creation, engage more customers, and retain them. Importantly, personalized marketing messages generated by GenAI were more likely to engage consumers, mainly when used to address satisfied customers with upsell suggestions and to incentivize neutral and dissatisfied customers. Nevertheless, challenges remain regarding the authenticity of the content and the privacy of the data. The paper highlights the potential of GenAI to transform the nature of personalized e-commerce marketing by integrating data and real-time content development to increase customer satisfaction and business results.