Modeling the Impact of Artificial Intelligence on the Effectiveness of Relationship Marketing Strategies in Modern Iranian Banking Services: With an Approach to Improving Customer Experience

Abstract

Following the rapid and extensive developments resulting from the emergence of financial technologies (FinTech) and the era of modern banking, banks are increasingly in need of reviewing their communication and service strategies. This article aims to model the impact of artificial intelligence on the dimensions of relationship marketing (such as personalization and automated interactions) and its ultimate impact on improving customer experience (CX) in modern banking services in Iran. The methodology of the present study is quantitative and to model the structural relationships between variables, the structural equation modeling (SEM) technique with the partial least squares (PLS) approach was used on a sample of 300 active customers of Iranian banks. The results showed that the implementation of artificial intelligence had a positive and significant effect on strengthening the dimensions of relationship marketing (path coefficient 0.55 with T-Value 6.75) and this, in turn, leads to an improvement in the level of customer experience (path coefficient 0.42 with T-Value 4.90). Also, the mediating role of relationship marketing (indirect path coefficient 0.23) was confirmed. This research, with explanatory relationship modeling, provides a practical framework for developing automated and customer-centric marketing strategies to ensure sustainable competitive advantage and ultimately, the growth of the bank's business by utilizing modern AI tricks.