New Book: A Practical Guide for Demand Prediction in Retail

A Practical Guide for Demand Prediction in Retail 

A Practical Guide for Demand Prediction in Retail
Including detailed implementations and comprehensive notebooks
*Launching Summer 2021*
Authors: Maxime C. Cohen, Paul-Emile Gras, Arthur Pentecoste, Renyu Zhang
Table of contents


Book Description

We cover 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 visualising 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.


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.