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Pricing Analytics : Models and Advanced Quantitative Techniques for Product Pricing

By: (Author) Walter R. Paczkowski

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Ksh 7,450.00

Format: Paperback / Softback

ISBN-10: 1138623938

ISBN-13: 9781138623934

Publisher: Taylor & Francis Ltd

Imprint: Routledge

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jun 26th, 2018

Print length: 318 Pages

Weight: 548 grams

Dimensions (height x width x thickness): 15.60 x 23.10 x 2.60 cms

Product Classification: Finance
Sales & marketing

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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, it comes 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 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.


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