Demand Prediction in Retail
A Practical Guide to Leverage Data and Predictive Analytics
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Beschreibung
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.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.
Covers the entire process of demand prediction for any business setting Discusses all the steps required in a real-world implementation Includes additional material to assist the learning experience
Autor*in
Maxime C. Cohen
Themen in »Demand Prediction in Retail«
demand prediction supply chain analytics data-driven forecasting predictive analytics data science and operations data-driven decision tools business analytics predictive modelling
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“To remain competitive in today's economy, it is imperative for retailers to undertake a digital transformation. Having demand prediction capabilities is a crucial building block to optimize omnichannel marketing and operations. This book can serve as an invaluable guide on how to leverage data and AI to predict demand and is a must have on the shelf of practitioners in the retail industry.” (Anindya Ghose – Heinz Riehl Chair Professor at NYU Stern School of Business and author of TAP: Unlocking the Mobile Economy)
“Predicting retail sales does not need to solely rely on experience and intuition anymore. The recent progress in predictive analytics provides great tools to help retailers predict demand. This book is instrumental for retailers who seek to embrace data-driven decision making.” (Georgia Perakis – William F. Pounds Professor at MIT Sloan School of Management)“The key to success for many retailers lies in making sure that the right products areavailable at the right time in the right store. Failing to meet this goal may adversely affect customer loyalty and long-term profits. The only way to systematically succeed in this goal at scale is to rely on data and algorithms. This book is very pragmatic and explains how to leverage past data to predict future demand for retailers.” (Aldo Bensadoun, Founder and Executive Chairman of the Aldo Group)
“End-to-end retail decisions from procurement, capacity/inventory, distribution channel management to pricing and promotions crucially rely on robust demand prediction models, making this book vital for retailers. The content of this book is comprehensive yet remains accessible and actionable. An excellent reference and a must read for data science enthusiasts as well as data science managers who have been changing the retail business as we know it.” (Özalp Özer, Senior Principal Scientist at Amazon, George and Fonsa Brody Professor at UT Dallas, and author of The Oxford Handbook of Pricing Management)
“For business analytics students and practitioners interested in understanding how to implement statistical demand forecasting models using Python, this book provides an invaluable hands-on approach, with detailed programming examples to guide the reader.” (Gerry Feigin, Partner and Associate Director at BCG GAMMA and author of Supply Chain Planning and Analytics and The Art of Computer Modeling for Business Analytics)
“Finally a book that methodically demystifies retail demand prediction has arrived. This is a must read for any aspiring scientists looking to apply statistical and machine learning techniques to real-world demand prediction problems, as well as an excellent refresher for practitioners to stay current.” (Nitin Verma, Vice President, Digital Solutions and Chief Scientist at Staples)
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