Essentials of Pricing Analytics Tools and Implementation with Excel 1st Edition by Erik Haugom ISBN 9781000228083 1000228088

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Product details:

ISBN 10: 1000228088
ISBN 13: 9781000228083
Author:  Erik Haugom

Table of contents:

Chapter 1 Introduction

1.1 The purpose of the book

1.2 The impact of price management on profit

1.3 Pricing analytics

1.4 Who can use pricing analytics?

1.5 Alternative approaches to pricing

1.6 Summary

1.7 Problems

Chapter 2 Fundamentals of price theory

2.1 Consumer preferences and price–response functions

2.2 Costs that matter in pricing decisions

2.3 Deciding optimal price and quantity – an example

2.4 The role of pricing under various market structures

2.5 Summary

2.6 Problems

Chapter 3 Segmentation and price differentiation

3.1 Price differentiation defined

3.2 The economics theory behind price differentiation

3.3 Ways to segment and price differentiate in practice

3.5 Summary

3.6 Problems

Chapter 4 Break-even analysis

4.1 Break-even analysis defined

4.2 Break-even analysis of price changes

4.3 Break-even with cost changes

4.4 Break-even sales curves

4.5 Summary

4.6 Problems

Chapter 5 Price sensitivity and willingness to pay

5.1 Price sensitivity

5.2 Willingness to pay

5.3 Functional forms of price–response functions

5.4 Summary

5.5 Problems

Chapter 6 Empirical estimations of price–response functions

6.1 Sources for price and demand data

6.2 Preliminaries to data collection

6.3 Measuring price–demand relationships in a direct survey

6.4 Addressing hypothetical bias using experiments

6.5 Empirical estimation of price–response functions

6.6 Summary

6.7 Problems

6.8 Appendix

Chapter 7 Price optimization

7.1 Basic price optimization

7.2 Price optimization with capacity constraints

7.3 Optimal price differentiation with capacity constraints

7.4 Optimal time-based price differentiation

7.5 Elasticity and optimization

7.6 Pricing with competition

7.7 Summary

7.8 Problems

Chapter 8 Case study Optimal prices of movie theater tickets

8.1 Step 1: Develop a questionnaire

8.2 Step 2: Data collection and punching

8.3 Step 3: Data preparation

8.4 Step 4: Preliminary analysis

8.5 Step 5: Estimation of price–response functions

8.6 Step 6: Optimize prices

8.7 Step 7: Implementation

8.8 Limitations and final notes

8.9 Problems

Chapter 9 Markdown optimization

9.1 What is markdown optimization?

9.2 Formulating the markdown optimization problem

9.3 Implementation of markdown optimization in Excel

9.4 Summary

9.5 Problems

Chapter 10 The hedonic pricing model

10.1 What is price hedonism?

10.2 The model specification

10.3 Empirical applications of hedonic pricing

10.4 Implementation of hedonic pricing

10.5 Summary

10.6 Problems

Chapter 11 Revenue management

11.1 History and applicability of revenue management

11.2 Implementing revenue management

11.3 Optimal protection levels in a single period model

11.4 Summary

11.5 Problems

Chapter 12 Big Data and pricing analytics

12.1 What is Big Data?

12.2 The business value of Big Data in pricing analytics

12.3 Big Data analytics techniques for pricing decisions

12.4 Implementation in Excel

12.5 Excel’s role in big data pricing analytics

12.6 Summary

12.7 Problems

Chapter 13 Monte Carlo simulation for pricing decisions

13.1 What is Monte Carlo simulation?

13.2 How can simulation be used for pricing decisions?

13.3 The basics of Monte Carlo simulation in Excel

13.4 Example of simulation models for pricing problems

13.5 Summary

13.6 Problems

Chapter 14 Conjoint analysis for pricing decisions

14.1 Conjoint analysis

14.2 Estimate price–response functions with conjoint data

14.3 Implementation in Excel

14.4 Summary

14.5 Problems

Chapter 15 Acceptance, ethics, and the law

15.1 Customer acceptance

15.2 Ethical constraints

15.3 Legal issues

15.4 Summary

15.5 Problems

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