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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…mehr
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.
Louis-Philippe Kerkhove is co-founder and CTO at the retail analytics agency Crunch (founded in 2017) in Belgium. He is also academically connected to Ghent University (Belgium).
Inhaltsangabe
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.
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.
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.
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.
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