Pricing: Segmentation and Analytics (Marketing Strategy Collection)

Book Discription

Pricing analytics uses historical sales data with mathematical optimization to set and update prices offered through various channels in order to maximize profit. A familiar example is the passenger airline industry, where a carrier may sell seats on the same flight at many different prices. Pricing analytics practices have transformed the transportation and hospitality industries, and are increasingly important in industries as diverse as retail, telecommunications, banking, health care and manufacturing.

With this outstanding contribution to this subject, you will learn just how to identify and exploit pricing opportunities in different business contexts. Each chapter looks at pricing from an economist’s viewpoint beginning with the basic concept of pricing analytics and what type of data are needed to use this powerful science; the common assumptions regarding the customer population’s willingness- to-pay are discussed along with the price-response functions that result from these assumptions; examples from several industries and organizations; dynamic pricing, with a special emphasis on the most common application–markdown pricing; the new field of customized pricing analytics, where a firm responds to a request-for-bids or request-for-proposals with a customized price response; and the relevant aspects of behavioral science to pricing. Additional examples include the asymmetry of joy/pain that customers feel in response to price decreases/increases. Pricing analytics uses historical sales data with mathematical optimization to set and update prices offered through various channels in order to maximize profit.

This book will guide students and professionals on how to identify and exploit pricing opportunities in different business contexts. The first chapter looks at pricing from an economist’s viewpoint, beginning with the basic concept of price elasticity and how it differs at the product, firm, and industry levels as well as the short term versus long term.

The second chapter looks at these same topics, but from a more practical standpoint, with examples provided from several consulting projects. The third chapter is on dynamic pricing, with a special emphasis on the most common application: markdown pricing. The fourth chapter covers the new field of customized pricing analytics, where a firm responds to a request-for-bids or request-for-proposals with a customized price response. In this situation, the firm will only have historical win/loss data and traditional methods involving price elasticity do not apply.

The final chapter covers the relevant aspects of behavioural science to pricing. Examples include the asymmetry of joy/pain that customers feel in response to price decreases/increases. A set of best pricing practices will be presented that are based on these behavioral responses.

Book Information

Print Length

165 Pages

Language

English

Publisher

Business Expert Press

Publication Date

September 30, 2011

Dimensions

6.0 x 0.4 x 9.0 inches

ISBN-10

1606492578

ISBN-13

978-1606492574

About The Author

About Mark Ferguson

Mark Ferguson is the Wilbur S. Smith Professor in the Moore School of Business at the University of South Carolina. Prior to joining the University of South Carolina, he was the Steven A. Denning Professor of Technology and Management at Georgia Tech. He serves as the chair for the Pricing and Revenue Management subdivision of INFORMS, the president

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About Tudor Bodea

Tudor Bodea is an assistant professor in the Operations group at the University of Groningen, Faculty of Economics and Business. Prior to joining the University of Groningen, he was a senior scientist at Predictix and an operations research analyst at InterContinental Hotels Group. He is six sigma certified and a contributor to R, an open source language and

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Table Of Contents

Chapter 1: introduces the ‘pricing analytics’ concept in an accessible fashion. It begins with a concise contextual overview of the various ways in which managers typically arrive at pricing decisions. The chapter proceeds to explore and examine the theoretical underpinnings of the ‘pricing analytics’ phenomenon, beginning with a micro-economic discussion on ‘consumer utility’ in the context of consumer purchase decision making. Following this, the authors describe and model the ‘pricing analytics process’. Through equations and aligned discussion, they reveal how to determine different segments based on price sensitivity, and they expose how to set optimum prices for each segment.

Chapter 2: focuses on the practice of pricing analytics. Accordingly, it is rich in practical examples. The chapter opens with a discussion on the types of data used to make pricing decisions and how to develop pricing capabilities. In this chapter, the authors illustrate that estimating the ‘price elasticity of demand’ is as much an ‘art’ as a ‘science’ in practice. They draw from the several organisations’ practices and those prevalent in certain industries, to support their propositions. The latter part of the chapter contains a particularly good case study on Dominick’s Finer Foods. The case study demonstrates how the theoretical concepts introduced in Chapter 1 play out in practice.

Chapter 3: concentrates on two interrelated phenomena, namely, ‘dynamic pricing’ and ‘markdown optimisation’. The chapter opens with a broad discussion on dynamic pricing, highlighting its historical relevance and evolution in buyer–seller exchanges. This first part of the chapter underlines the reasons why some companies readily embrace and/or fail to capitalise from dynamic pricing. The latter part of the chapter examines markdown optimisation – what the authors regard as the ‘most common dynamic pricing application’. Retailers of ‘seasonal and style goods’ are focused on here due to their interest in generating sales and shifting stock through ‘constant in-season price markdowns’. The chapter ends with two case studies, which illustrate how markdowns are used in practice. The first case study focuses on identifying ‘profitable markdown opportunities’ in a ‘slow-moving item’ context. The second concentrates on using ‘linear programming to solve a simple markdown optimisation problem’.

Chapter 4: specifically focuses on the ‘business-to-business environment’. Overall, it centres on the emergent domain of ‘customised pricing analytics’. The chapter examines business-to-business pricing contexts wherein firms reply to requests for bids/proposals with a ‘customised price response’. In this chapter, emphasis is placed on customised pricing models and on highlighting the ‘technical aspects’ of ‘customised price optimisation’. Towards the end of the chapter, the authors discuss how to implement a ‘customised pricing optimisation package’. Usefully, they describe, as a step-by-step process, the ‘pricing analytics methodology’ relating to an application.

Chapter 5: which is the final chapter, centres on the ‘customer behaviour aspects of pricing’. Generally, the chapter highlights the limitations of the ‘rational’ assumptions of traditional microeconomics, and notes how consumers experience a ‘joy/pain’ dichotomy in response to price fluctuations. This chapter stresses the need to understand the psychology of pricing. The authors reveal how such psychological insights can enable companies to evoke favorable consumer responses to pricing promotions and changes. The chapter proceeds to discuss ‘reference pricing’, ‘prospect theory’ and ‘perceptions of price fairness’.