Data-driven Retailing: A Non-technical Practitioners' Guide
Data-driven Retailing: A Non-technical Practitioners' Guide
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Retail managers will learn how data analysis can be used to optimize pricing, customer loyalty and logistics without complex algorithms.
The goal of the book is to help managers ask the right questions during a project, which will put them on the path to making the right decisions.
Format: Hardback
Length: 257 pages
Publication date: 06 October 2022
Publisher: Springer International Publishing AG
This comprehensive book is a valuable resource for retail managers seeking to leverage data for innovative strategies in three critical areas: algorithmic marketing, logistics, and pricing. It delves into practical applications and case studies, empowering managers to optimize pricing, customer loyalty, and logistics without the need for complex algorithms. The book's primary objective is to guide managers in asking the right questions throughout a project, ensuring they make informed decisions that drive their retail organization's success. With a focus on practitioners who aspire to employ advanced techniques to enhance their retail operations, this text offers valuable insights and techniques for achieving competitive advantage in the ever-evolving retail landscape.
Introduction:
In today's fast-paced retail environment, where customer expectations are constantly evolving, data-driven decision-making has become an essential tool for retail managers. This book aims to provide a practical guide for retail managers to effectively use data to optimize their operations and achieve sustainable growth.
Chapter 1: Algorithmic Marketing:
The first chapter explores the role of algorithmic marketing in retail. It discusses how retailers can leverage data analytics to gain insights into customer behavior, preferences, and purchasing patterns. It also highlights the importance of personalization in marketing strategies and how algorithms can help retailers create targeted campaigns that resonate with their customers.
Chapter 2: Logistics:
The second chapter focuses on logistics and supply chain management. It discusses how retailers can optimize their inventory management, delivery processes, and warehouse operations using data analytics. It also explores the use of technology, such as RFID and automation, to improve efficiency and reduce costs.
Chapter 3: Pricing:
The third chapter examines pricing strategies in retail. It discusses how retailers can use data analytics to optimize their pricing models, including dynamic pricing, price discrimination, and bundle pricing. It also highlights the importance of understanding customer willingness to pay and how pricing can influence customer loyalty and purchasing behavior.
Conclusion:
In conclusion, this book provides retail managers with a comprehensive guide to using data for innovative strategies in algorithmic marketing, logistics, and pricing. By leveraging data analytics, retailers can gain a competitive advantage, improve customer satisfaction, and drive sustainable growth. As the retail industry continues to evolve, this book will remain a valuable resource for managers who want to stay ahead of the curve.
Weight: 582g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031129612
Edition number: 1st ed. 2022
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