Book: Demand Prediction in Retail - A Practical Guide to Leverage Data and Predictive Analytics

Demand Prediction in Retail - A Practical Guide to Leverage Data and Predictive
Analytics 

Demand Prediction in Retail - A Practical Guide to Leverage Data and Predictive Analytics
Including detailed implementations and comprehensive notebooks
Dataset available for download
Authors: Maxime C. Cohen, Paul-Emile Gras, Arthur Pentecoste, Renyu Zhang
Springer Series in Supply Chain Management 14, 2022
ISBN 978-3-030-85855-1
Table of contents
Buy the book: Amazon.com, Amazon.ca, Amazon.fr, Springer, Barnes & Noble, Book Depository, Browns Books

                   

Book Description

This book covers the entire process of using data to predict demand for retailers. We go over all the steps, starting from collecting the data all the way to evaluating and visualizing the prediction results. We present several methods and approaches that are commonly used for demand prediction. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. To assist the learning experience, we share a dataset available for download. The tools and methods covered in this book can be applied to most retail settings (both online and brick-and-mortar) including fashion, electronics, groceries, and furniture. We are confident that after reading this book, readers will be prepared to predict demand in their business setting of interest. See also the table of contents.

About Demand Prediction

Demand prediction is at the forefront of most retailers’ priorities. Being able to accurately predict future demand for each product can be instrumental to guide retailers with their operational decisions and, ultimately, boost profitability.

Audience

This book is targeted to both data scientists and students in business analytics. An additional audience is retailers who want to hire a scientist to leverage historical data for demand prediction.

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