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Titlebook: Data-driven Retailing; A Non-technical Prac Louis-Philippe Kerkhove Book 2022 The Editor(s) (if applicable) and The Author(s), under exclus

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发表于 2025-3-21 18:57:24 | 显示全部楼层 |阅读模式
书目名称Data-driven Retailing
副标题A Non-technical Prac
编辑Louis-Philippe Kerkhove
视频video
概述Offers tools to manage data-centric projects and ask the right questions.Provides user-friendly practical knowledge on data management.Covers theory and practice of data analysis and management
丛书名称Management for Professionals
图书封面Titlebook: Data-driven Retailing; A Non-technical Prac Louis-Philippe Kerkhove Book 2022 The Editor(s) (if applicable) and The Author(s), under exclus
描述This book provides retail managers with a practical guide to using data. It covers three topics that are key areas of innovation for retailers: Algorithmic Marketing, Logistics, and Pricing. Use cases from these areas are presented and discussed in a conceptual and comprehensive manner. 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. It is thus aimed at practitioners who want to use advanced techniques to optimize their retail organization..
出版日期Book 2022
关键词Retail; Data analytics; Machine learning; Customer relationship management; Data warehousing; Pricing; Mar
版次1
doihttps://doi.org/10.1007/978-3-031-12962-9
isbn_softcover978-3-031-12964-3
isbn_ebook978-3-031-12962-9Series ISSN 2192-8096 Series E-ISSN 2192-810X
issn_series 2192-8096
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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发表于 2025-3-21 20:27:48 | 显示全部楼层
Improving the List Priceng to change. Prices change over time, depending on circumstances and perhaps also depending on who is making the purchase. This chapter provides an introduction on how data-driven decision-making can be used to improve prices and consequently retailer profits.
发表于 2025-3-22 02:20:21 | 显示全部楼层
Optimizing Markdowns and Promotionse improved using data-driven decision-making. Both permanent price reductions (markdowns) and temporary promotional discounts are discussed. The main focus is the former, as the markdown decision is often influenced less by the marketing objectives and can more easily be delegated to a data-driven a
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发表于 2025-3-22 12:02:52 | 显示全部楼层
Anticipate What Customers Will Dots outs the broad lines, these models are the precision instruments that allow for the identification of specific individuals. The focus of the chapter is on what a retailer can do with these models, rather than on the technical workings of such models.
发表于 2025-3-22 16:10:36 | 显示全部楼层
Anticipate When Customers Will Do Somethinga medical context to model patient survival. These models can be perfectly repurposed to optimize the timing of a retailers messaging, to coincide with moment when this messaging has the greatest impact.
发表于 2025-3-22 17:53:12 | 显示全部楼层
The Retailer’s Pricing Challengemain where most data-driven solutions operate is discussed. Next, the major pricing challenges are introduced by discussing the goals that are pursued by a retailer under specific conditions. Later chapters go into more depth as to how these goals can be achieved in practice.
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发表于 2025-3-23 06:05:57 | 显示全部楼层
Anticipate What Customers Will Dots outs the broad lines, these models are the precision instruments that allow for the identification of specific individuals. The focus of the chapter is on what a retailer can do with these models, rather than on the technical workings of such models.
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