USING BIG DATA TO DEVELOP DIGITAL MARKETING STRATEGIES: A CASE STUDY

The power of Big Data to deliver tailored, hyper-focused content to audiences, segment audiences into factions, forecast trends, and fine-tune marketing and advertising spending is hard at work in today’s competitive digital landscape – and, for many businesses, challenging to see. So, this study focuses on exploring the role of Big Data in the technique development of digital marketing strategies, with Amazon as a case study over the period 2018–2023. The goal is to study how data-driven strategies influence the most crucial marketing outcome metrics, including customer engagement, conversion rates, return on investment (ROI), and advertising efficiency. The study uses a mixed-method approach to combine Amazon's qualitative content analysis method and quantitative analysis via regression models and Difference-in-Differences (DiD) estimation. Results suggest that personalisation, segmentation, and real-time advertising optimisation significantly improve performance – post-intervention campaigns increase conversion rates by 3.1% and reduce customer acquisition costs by $10. Further, regression analysis reinforces the positive effect of Big Data strategies, and more profoundly, advertising optimisation has the most significant impact on ROI. Based on the findings in this study, the study recommends that policy be based on continuous loops of feedback and predictive analytics to facilitate adaptive, efficient, and targeted marketing efforts. However, it will also be critical to establish clear data governance frameworks and ethical data practices to maintain consumer trust and compliance with privacy regulations.