Customer Engagement and Data-Driven Customisation in the Retail Banking Sector in South Africa

Abstract

In a time where South African retail banks significantly invest in AI-driven platforms and multichannel engagement tools, the specific processes through which data-driven customisation cultivates loyalty are vague. This research integrates Artificial Intelligence (AI), the Technology Acceptance Model (TAM), Customer Relationship Management (CRM), and Commitment–Trust theory into a cohesive structural equation model to investigate the influence of personalised banking experiences on engagement, satisfaction, trust, and advocacy among four generational cohorts (Gen Z, Millennials, Gen X, Boomers). Survey data from 190 bank customers who participated in this research indicates that, although the frequency of digital engagement and trust in data security constitute the foundation of the service environment, it is customer satisfaction – driven by genuinely meaningful, tailored interactions – that most significantly predicts Net Promoter Score (NPS) and minimises switching intentions. The direct impact of personalisation and customisation on engagement and of trust on loyalty was not substantial, indicating deficiencies in implementation and monitoring gaps in current banking analytics. Generational analysis reveals significant disparities in AI feature uptake, highlighting the necessity for cohort-specific personalisation tactics and strategies. These findings enhance marketing theory by establishing satisfaction as the crucial mediator in the customisation-loyalty relationship and directing practitioners towards hyper-targeted offers, transparent data governance, and customised engagement approaches to convert each digital encounter into long-term advocacy.