Integrated retail ecosystem: The convergence of predictive analytics and omnichannel strategies in modern merchandising

This article explores the convergence of predictive analytics and omnichannel strategies in modern retail merchandising, examining how these integrated approaches transform decision-making and operational efficiency across the retail landscape. Beginning with the theoretical frameworks underpinning predictive modeling in retail contexts, the article progresses through core applications including demand forecasting, price optimization, product assortment planning, and advanced customer segmentation. The article further analyzes the omnichannel paradigm, examining conceptual foundations, integration of physical and digital touchpoints, unified customer experience strategies, and flexible fulfillment models. By investigating the synergies between predictive capabilities and omnichannel operations—specifically in data unification, personalization at scale, inventory optimization, and cross-channel journey mapping—the article identifies significant competitive advantages for retailers implementing integrated approaches. The article concludes by addressing current limitations while highlighting emerging trends and future research opportunities in autonomous retail systems, hybrid intelligence models, edge analytics, computer vision applications, and blockchain technologies.