Demand Prediction in Retail: A Practical Guide to Leverage Data and Predictive Analytics (1st ed. 2022) (Springer Series in Supply Chain Management #14)

By: Maxime C. Cohen and Paul-Emile Gras and Arthur Pentecoste and Renyu Zhang

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Synopsis: From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture. This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.

Book Quality:: Publisher Quality
ISBN-13:: 9783030858551
Related ISBNs:: 9783030858544
Publisher:: Springer International Publishing
Date of Addition:: 01/14/22
Copyrighted By:: The Editor
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Computers and Internet, Business and Finance, Mathematics and Statistics
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.