Evaluating the Influence of AI-Driven Predictive Analytics on Strategic Marketing Decisions in the Commerce Sector

Abstract

Artificial Intelligence (AI) and predictive analytics have emerged as transformative forces in the field of marketing, radically reshaping how businesses understand customers, forecast demand, design campaigns, and allocate budgets. The commerce sector—comprising retail, e-commerce, FMCG, banking-commerce integrations, and service industries—relies heavily on predictive tools to navigate dynamic markets characterized by rapid digitization and intense competition. This research paper evaluates the influence of AI-driven predictive analytics on strategic marketing decisions using exclusively secondary data from journal articles, consulting reports, business publications, and industry cases. The study reveals that predictive analytics enhances customer segmentation, demand forecasting, pricing optimization, product innovation, and marketing ROI. It enables marketers to shift from intuition-based decisions to scientifically informed strategies backed by real-time insights. However, the adoption of predictive analytics presents challenges such as data privacy concerns, algorithmic bias, technological integration issues, skill shortages, and high implementation costs. The paper concludes with recommendations for ethical, effective, and sustainable use of predictive analytics in marketing.