The Role of Big Data Analytics in Improving Competitive Marketing Strategies: A Case Study

Abstract

General Background: Contemporary digital platforms generate vast volumes of structured and unstructured market data. Specific Background: Businesses increasingly seek to transition from broad traditional marketing toward data-driven strategies. Knowledge Gap: However, discrepancies remain regarding how big data analytics explicitly optimizes market segmentation, offering personalization, and marketing campaign efficiency. Aims: This study examines the strategic role of big data analytics in improving competitive marketing performance through a systematic literature review. Results: Synthesizing 50 peer-reviewed studies following PRISMA guidelines reveals that data analytics significantly improves consumer insight generation, targeting accuracy, real-time campaign optimization, and resource allocation, while deployment faces governance, privacy, and skill shortage challenges. Novelty: The findings establish a comprehensive framework mapping multi-source data ingestion to predictive consumer engagement capabilities. Implications: Organizations must invest in digital infrastructure, analytical skill development, and ethical data governance to sustain long-term competitive advantages. Keywords: Big Data Analytics, Competitive Marketing, Customer Segmentation, Offer Personalization, Data-Driven Decision Making Key Findings Highlights Systematic data evaluation transforms broad traditional marketing approaches into highly targeted consumer engagement models. Real-time web and social media tracking significantly optimizes campaign performance and marketing budget allocation. Organizational skill gaps and data privacy governance represent the primary hurdles to successful analytical integration.