A Systematic Review of Artificial Intelligence-Based Customer Analytics in Personalized Digital Marketing (2019–2026)

Abstract

Artificial intelligence (AI)-driven customer analytics has emerged as a transformative force in personalized marketing within modern digital commerce ecosystems, driven by the rapid growth of big data, real-time consumer interaction platforms, and intelligent recommendation technologies. This systematic review investigates the impact of AI-driven customer analytics on personalized marketing strategies across digital commerce platforms during the period from 2019 to 2026. The study explores how AI technologies, including machine learning, predictive analytics, recommendation systems, natural language processing, sentiment analysis, marketing automation, and AI-enabled customer relationship management systems, affect customer engagement, purchasing behavior, personalization performance, and organizational outcomes in digital environments. The review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to ensure methodological rigor, transparency, and systematic synthesis of existing literature. Relevant academic publications were collected from major scholarly databases, including Scopus, Web of Science, ScienceDirect, IEEE Xplore, SpringerLink, Emerald Insight, Wiley Online Library, and Google Scholar. After applying screening, eligibility, and quality assessment criteria, 126 peer-reviewed studies were selected for qualitative and thematic analysis. The findings indicate that AI-driven customer analytics substantially enhances personalization accuracy, customer segmentation, recommendation quality, and real-time engagement across e-commerce websites, mobile commerce applications, social media platforms, and omnichannel retail environments. The review further reveals that predictive analytics, recommendation engines, conversational AI systems, and automated marketing technologies contribute significantly to customer retention, loyalty, conversion optimization, and overall customer satisfaction. In addition, big data infrastructures and cloud computing technologies were identified as essential enablers of adaptive and real-time personalized marketing strategies. The study also highlights the importance of consumer trust, transparency, privacy protection, and ethical governance in shaping user acceptance of AI-powered personalization technologies. Several studies reported concerns regarding algorithmic bias, behavioral surveillance, cybersecurity vulnerabilities, and regulatory compliance in digital commerce ecosystems. Furthermore, the review emphasizes the increasing influence of social media analytics, AI-powered advertising systems, and influencer engagement technologies on consumer behavior and purchasing decisions. Overall, the study concludes that AI-driven customer analytics has become a strategic foundation for personalized marketing, customer relationship management, and competitive advantage within global digital commerce ecosystems.