Demand Prediction in Retail: A Practical Guide to Leverage Data and Predictive Analytics 2022 Edition Contributor(s): Cohen, Maxime C. (Author), Gras, Paul-Emile (Author), Pentecoste, Arthur (Author) |
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ISBN: 3030858545 ISBN-13: 9783030858544 Publisher: Springer OUR PRICE: $104.49 Product Type: Hardcover Published: December 2021 |
Additional Information |
BISAC Categories: - Business & Economics | Sales & Selling - General - Business & Economics | Production & Operations Management - Mathematics | Probability & Statistics - General |
Physical Information: 0.44" H x 6.14" W x 9.21" (0.94 lbs) 155 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |