Integrasi Big Data Analytics dan Artificial Intelligence dalam Meningkatkan Kinerja Digital Marketing

Sebuah Systematic Literature Review

Abstract

This study aims to analyse the synergistic integration between Big Data Analytics (BDA) and Artificial Intelligence (AI) in enhancing digital marketing performance through a Systematic Literature Review (SLR) approach. The study synthesises 26 reputable Scopus-indexed articles selected systematically using the PRISMA protocol. The analysis combines bibliometric and thematic approaches to identify research trends, relationship patterns among variables, and literature gaps. The results indicate that BDA and AI are complementary strategic capabilities that generate a super-additive synergistic effect, significantly improving engagement, conversion, and operational efficiency. This strategic value is realised through enhanced customer insight, hyper-personalisation, and predictive capability in marketing decision-making. The effect is not direct but mediated by customer-based constructs such as customer engagement and perceived value, and is contingent on organisational capabilities, particularly organisational agility and data governance. Theoretically, this study extends the Resource-Based View (RBV) and Dynamic Capabilities Theory by positioning BDA-AI integration as an advanced capability that becomes a source of competitive advantage within the digital ecosystem. Unlike prior studies that tend to be partial, this research offers a more holistic conceptual synthesis integrating technological, organisational, and behavioural dimensions. Nevertheless, the literature remains dominated by cross-sectional approaches, with limited attention to small and medium enterprises (SMEs), cross-industry contexts, and data ethics and privacy issues. Future research is therefore encouraged to adopt longitudinal designs, leverage real-time data, and explore human-AI collaboration in greater depth.