東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Data-driven retailing = a non-techni...

Kerkhove, Louis-Philippe.

FindBook

Google Book

Amazon

博客來

Data-driven retailing = a non-technical practitioners' guide /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data-driven retailing/ by Louis-Philippe Kerkhove.
其他題名:	a non-technical practitioners' guide /
作者:	Kerkhove, Louis-Philippe.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xv, 257 p. :ill. (some col.), digital ;24 cm.
內容註:	Part I. Pricing -- Chapter 1. The Retailer's Pricing Challenge -- Chapter 2. Understanding Demand and Elasticity -- Chapter 3. Improving the List Price -- Chapter 4. Optimizing Markdowns and Promotions -- Part II. Inventory Management -- Chapter 5. Product (Re-)distribution and Replenishment -- Chapter 6. Managing Product Returns -- Part III. Marketing -- Chapter 7. The Case for Algorithmic Marketing -- Chapter 8. Better Customer Segmentation -- Chapter 9. Anticipate What Customers Will Do -- Chapter 10. Anticipate When Customers Will Do Something -- Part IV. Conclusion -- Chapter 11. Where Retail Is Headed Next.
Contained By:	Springer Nature eBook
標題:	Retail trade - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-031-12962-9
ISBN:	9783031129629

Data-driven retailing = a non-technical practitioners' guide /
Kerkhove, Louis-Philippe.

Data-driven retailinga non-technical practitioners' guide /[electronic resource] :by Louis-Philippe Kerkhove. - Cham :Springer International Publishing :2022. - xv, 257 p. :ill. (some col.), digital ;24 cm. - Management for professionals,2192-810X. - Management for professionals..

Part I. Pricing -- Chapter 1. The Retailer's Pricing Challenge -- Chapter 2. Understanding Demand and Elasticity -- Chapter 3. Improving the List Price -- Chapter 4. Optimizing Markdowns and Promotions -- Part II. Inventory Management -- Chapter 5. Product (Re-)distribution and Replenishment -- Chapter 6. Managing Product Returns -- Part III. Marketing -- Chapter 7. The Case for Algorithmic Marketing -- Chapter 8. Better Customer Segmentation -- Chapter 9. Anticipate What Customers Will Do -- Chapter 10. Anticipate When Customers Will Do Something -- Part IV. Conclusion -- Chapter 11. Where Retail Is Headed Next.

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.

ISBN: 9783031129629

Standard No.: 10.1007/978-3-031-12962-9doiSubjects--Topical Terms:

880324
Retail trade
--Data processing.

LC Class. No.: HF5429.15 / .K47 2022

Dewey Class. No.: 658.87002856312

Data-driven retailing = a non-technical practitioners' guide /
LDR:02376nmm a2200337 a 4500 001 2304638
003 DE-He213
005 20221005130733.0
006 m d
007 cr nn 008maaau
008 230409s2022 sz s 0 eng d
020 $a 9783031129629 $q (electronic bk.)
020 $a 9783031129612 $q (paper)
024 7 $a 10.1007/978-3-031-12962-9 $2 doi
035 $a 978-3-031-12962-9
040 $a GP $c GP
041 0 $a eng
050 4 $a HF5429.15 $b .K47 2022
072 7 $a KNPR $2 bicssc
072 7 $a BUS000000 $2 bisacsh
072 7 $a KNP $2 thema
082 0 4 $a 658.87002856312 $2 23
090 $a HF5429.15 $b .K39 2022
100 1 $a Kerkhove, Louis-Philippe. $3 3607033
245 1 0 $a Data-driven retailing $h [electronic resource] : $b a non-technical practitioners' guide / $c by Louis-Philippe Kerkhove.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xv, 257 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Management for professionals, $x 2192-810X
505 0 $a Part I. Pricing -- Chapter 1. The Retailer's Pricing Challenge -- Chapter 2. Understanding Demand and Elasticity -- Chapter 3. Improving the List Price -- Chapter 4. Optimizing Markdowns and Promotions -- Part II. Inventory Management -- Chapter 5. Product (Re-)distribution and Replenishment -- Chapter 6. Managing Product Returns -- Part III. Marketing -- Chapter 7. The Case for Algorithmic Marketing -- Chapter 8. Better Customer Segmentation -- Chapter 9. Anticipate What Customers Will Do -- Chapter 10. Anticipate When Customers Will Do Something -- Part IV. Conclusion -- Chapter 11. Where Retail Is Headed Next.
520 $a 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.
650 0 $a Retail trade $x Data processing. $3 880324
650 0 $a Retail trade $x Management $x Data processing. $3 3607034
650 1 4 $a Trade and Retail. $3 3594413
650 2 4 $a Innovation and Technology Management. $3 3538485
650 2 4 $a Data Analysis and Big Data. $3 3538537
650 2 4 $a Customer Relationship Management. $3 2186425
650 2 4 $a e-Commerce and e-Business. $3 3591724
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Management for professionals. $3 1565822
856 4 0 $u https://doi.org/10.1007/978-3-031-12962-9
950 $a Business and Management (SpringerNature-41169)