Springer Demand Prediction in Retail - Practical Data Guide

Master the complexities of retail forecasting with this comprehensive guide from Springer. Part of the Springer Series in Supply Chain Management, this book provides a complete overview of the demand prediction process, covering everything from initial data collection to the evaluation and visualization of results. By using relevant code and implementation details, the text demystifies how to leverage historical data to predict future trends. The methods presented are versatile and can be applied across various retail environments, including online and brick-and-mortar settings such as fashion, electronics, groceries, and furniture. This resource is designed to help data scientists and students in business analytics gain practical expertise in using predictive analytics to drive retail decisions.