Pricing Analytics

Models and Advanced Quantitative Techniques for Product Pricing

Walter R. Paczkowski

• Publisher: Routledge
• Year: 2018
• Print ISBN: 9781138036758
• eBook ISBN: 9781351713085
• Topic: Business
• Subtopic: Business General
• Index: Business

The theme of this book is simple. The price – the number someone puts on a product to help consumers decide to buy that product – comes from data. Specifically, itcomes from statistically modeling the data.

This book gives the reader the statistical modeling tools needed to get the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory conjointly provide the background and framework for the models. Therefore, this book emphasizes two interlocking components of modeling: economic theory and statistical principles.

The economic theory component is sufficient to provide understanding of the basic principles for pricing, especially about elasticities, which measure the effects of pricing on key business metrics. Elasticity estimation is the goal of statistical modeling, so attention is paid to the concept and implications of elasticities.

The statistical modeling component is advanced and detailed covering choice (conjoint, discrete choice, MaxDiff) and sales data modeling. Experimental design principles, model estimation approaches, and analysis methods are discussed and developed for choice models. Regression fundamentals have been developed for sales model specification and estimation and expanded for latent class analysis.

Part I

Background

There is an old Chinese proverb most are familiar with: “A journey of a thousand miles begins with a single step.”¹ This first part is that first step. It sets the stage for the remainder of the book by discussing the importance of pricing and getting the “right” price. There are many ways to set the price of a product or service. In fact, there is probably an infinite number of ways, one for each marketing or pricing manager who has to wrestle with the issue of what to charge. Each manager brings his or her own biases and experiences to the pricing table. That does not mean that the methods are correct or good. Often, pure judgement is used, summarized in the pithy statement: “I know what the price should be.” This reflects the art of pricing.

Getting the price right is also a science just as much as it is an art. There are statistical and econometric tools – well-developed and sophisticated quantitative tools – that complement and support the art side of pricing. These tools cannot be overlooked or ignored solely in favor of the art. That would court business disaster.

What exactly do the tools do? Most of them, but not all, provide elasticities, an economic concept that is at the heart of pricing. An elasticity tells you quantitatively how much sales will change (in percentage terms) when you change the price (also in percentage terms). This is vital to know because, while you may believe that lowering price will stimulate sales, the amount of stimulation could be insufficient to offset the revenue loss of the lower price, resulting in a decrease in revenue. The art side of pricing will not tell you this, but the science side, summarized by the elasticities, will.

This first part of the book is divided into three chapters. The first gives an overall perspective of pricing and the importance of a quantitative approach, one that actually produces a number to go on the product’s price tag. This chapter highlights the art side of pricing, but then makes the case for the science or quantitative side.

The second chapter reviews and develops the elasticity concept. Thi...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Contents
• List of figures
• List of tables
• Preface
• Acknowledgements
• Part I Background
• Part II Stated preference models
• Part III Price segmentation
• Part IV Big Data and econometric models
• Bibliography
• Index