AI-Driven Marketing Communication and Customer Satisfaction in Jakarta’s Digital Banks

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Authors: Safaruddin Husada, Wulan Yulianti, Ulani Yunus, Tuhu Nugraha
Cited by: 0
References: 24

Abstract

The rapid integration of artificial intelligence (AI) has transformed digital banking practices, particularly through the adoption of hyper-personalised customer experiences. Despite this growth, comparative empirical evidence on how customers perceive AI-driven strategies across competing digital banks remains limited. This study investigates differences in customer perceptions of Integrated Marketing Communication (IMC), AI Personalization, Technology Acceptance Model (TAM) attributes, Kano needs categories, and overall customer satisfaction among users of three digital banks in Jakarta (Bank X, Bank Y, and Bank Z). A comparative quantitative approach was employed, involving 300 respondents selected through purposive and quota sampling. Data were analysed using descriptive statistics, ANOVA, and Tukey HSD tests. The findings indicate that Bank Y consistently achieves the highest mean scores across all constructs, reflecting strong perceptual leadership. Significant differences among the banks were confirmed, with further analysis revealing that TAM-related attributes and performance needs have become parity factors for certain bank pairs. In contrast, AI Personalization and excitement needs emerge as key differentiators. These results suggest that in increasingly mature digital banking markets, competitive advantage is no longer determined by basic functional performance, but by the ability to deliver proactive, contextual, and emotionally engaging AI-based experiences. This study contributes to the IMC, TAM, and Kano literature by highlighting a shift in customer expectations, where AI Personalization plays a central role in generating attractive quality and enhancing customer satisfaction.

Fields of Study & Subjects

Customer Service Quality and Loyalty Technology Adoption and User Behaviour AI in Service Interactions

Publication details

Journal / source
Ilomata International Journal of Social Science
Volume
7
Issue
1
Pages
291–309
Publication date
28 January 2026