STRATEGIC ANALYSIS OF DIGITAL MARKETING IN THE ERA OF BIG DATA AND ARTIFICIAL INTELLIGENCE: A SYSTEMATIC LITERATURE REVIEW ON CONSUMER PERSONALISATION, OMNICHANNEL OPTIMISATION, AND MACHINE LEARNING ALGORITHM ADAPTATION TO INCREASE SALES CONVERSIONS

Abstract

The rapid advancement of big data and artificial intelligence (AI) technologies has significantly transformed digital marketing strategies, enabling firms to enhance customer engagement and improve sales conversion performance. This study aims to analyze strategic developments in digital marketing through a systematic literature review focusing on consumer personalization, omnichannel optimization, and the adaptation of machine learning algorithms. Using a qualitative library research approach, relevant academic publications indexed in reputable databases were systematically reviewed to synthesize current knowledge and identify emerging research trends. The findings indicate that AI-driven personalization improves the customer experience and purchase intention, while omnichannel integration enhances consistency in the customer journey across multiple platforms. Additionally, adaptive machine learning algorithms support data-driven marketing decisions that optimize campaign performance and conversion outcomes. However, challenges related to data privacy, technological integration, and strategic alignment remain significant concerns. This study contributes by providing an integrated strategic perspective that consolidates fragmented literature and proposes directions for future research in intelligent digital marketing ecosystems.