Data-Driven Marketing in Banks: The Role of Artificial Intelligence in Enhancing Marketing Efficiency and Business Performance

Abstract

The purpose of the study is to examine the role of Artificial Intelligence (AI) in transforming marketing strategies in the banking sector, focusing on its impact on marketing efficiency, customer engagement, and business performance. A mixed-methods research approach was adopted, integrating survey data from 150 marketing professionals with qualitative insights from 40 in-depth interviews. Statistical analyses, including multiple regression and ANOVA, were conducted to assess the relationships between AI adoption and marketing performance indicators. The findings demonstrate a significant positive relationship between AI adoption and marketing efficiency (β = 0.632, p = 0.001), customer engagement (β = 0.588, p = 0.002), and business performance (β = 0.609, p = 0.001). AI-driven customer segmentation, predictive analytics, and marketing automation have significantly improved banks' ability to execute data-driven marketing strategies. The study is limited by its focus on Egyptian banks, which may restrict the generalizability of the findings to other regions. Additionally, the study does not account for long-term AI implementation effects. The findings provide practical recommendations for banking leaders, policymakers, and AI technology providers to enhance AI adoption. Strategies such as AI literacy programs and regulatory frameworks can help overcome implementation challenges. This study contributes to the growing literature on AI in financial marketing by providing empirical evidence on its effectiveness and implementation challenges, offering a roadmap for integrating AI into marketing strategies within the banking industry.