Abstract
This article presents a systematic literature review of data-driven marketing analytics, examining its theoretical foundations, principal applications, strategic value, and implementation challenges. Publications from 2013 to 2024 indexed in Scopus, Web of Science, and marketing-specialist databases were analysed. The review covers the conceptual architecture of marketing analytics, customer analytics applications including segmentation, lifetime value modelling and churn prediction, attribution modelling, and the integration of AI and machine learning in marketing decision support. The analysis demonstrates that organisations with mature marketing analytics capabilities achieve customer acquisition costs 30–50% lower than industry averages, retention rates 15–25% higher, and marketing return on investment improvements of 15–20%. Implementation challenges including data quality, talent scarcity, privacy regulation compliance, and organisational resistance are identified. Implications for marketing practice in Uzbekistan's rapidly digitalising business environment are discussed.
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