Pricing Analytics Models and Advanced Quantitative Techniques for Product Pricing

This updated and expanded second edition has the same theme as the first: the price, the number, someone puts on a product to help consumers decide to buy that product, comes from statistically modeling data.

Five new chapters provide a wider perspective on pricing analytics to more effectively develop elasticities and pricing strategies. This book gives readers the statistical modeling tools needed to get the number to put on a product, based on economic and statistical principles and theory. It covers elasticities, methodologies for analyzing customer choices including conjoint analysis, pricing segmentation, big data and econometric models―now with improved explanations and developments. The second edition adds discussion of three important and advanced topics: simulations for testing strategies under different conditions such as scenario analysis, AI applications for elasticity estimation and dynamic pricing, and the impacts of tariffs.

A comprehensive and essential resource for analysts―economists, statisticians, or market researchers―who must estimate the optimal price for a product or service, this book is also a helpful guide for upper-level students in analytics disciplines.

Walter R. Paczkowski is the founder of Data Analytics Corp., a statistical and data modeling consultancy, and a former lecturer in the Department of Economics at Rutgers University. He holds a Ph.D. in Economics from Texas A&M University, and has published several books on aspects of data science including Pricing Analytics (2018) and Deep Analytics for New Product Development (2020).