Improving marketing strategies through data-driven insights and adaptive models: a mobility industry case study

Abstract

This thesis explores the integration of data analytics and artificial intelligence (AI) in the field of marketing. In particular, it focuses on the application of next-best-action (NBA) techniques and the use of adaptive models in a leading Italian company in the mobility sector, which has transformed itself into a digital enterprise in recent years thanks to extensive diversification. The thesis aims to investigate the transformative impact of a data-driven approach and the incorporation of machine learning models on improving the effectiveness of marketing strategies and increasing customer engagement. This exploration involves a detailed comparison of key performance metrics before and after the implementation of these advanced technologies. Furthermore, the research extends to examining how leveraging artificial intelligence and data analytics can lead to deeper customer segmentation, enabling more precise targeting in marketing campaigns. It also explores the role of predictive analytics in predicting customer behaviour and preferences, thus enabling more proactive and personalised marketing efforts. This comprehensive analysis aims to provide a nuanced understanding of how modern technology can revolutionise traditional marketing methodologies in a rapidly evolving digital landscape.