Deep Data Analytics for New Product Development

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A01=Walter R. Paczkowski
advanced analytics for product innovation
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ANOVA Table
Author_Walter R. Paczkowski
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Backshift Operator
Big data
Business Case
business programs
Call Center Logs
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Choice Set
Conjoint Analysis
consumer insight analysis
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Correspondence Analysis
Customer Id
customer preference prediction
customers
Data Mart
Data mining
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deep data analytics
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Exponential Smoothing
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Machine learning
market segmentation techniques
Multidimensional scaling
Neural networks
new product development
New product failures
New products
NF2
NPD Process
OLS Regression
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pricing strategy modelling
product lifecycle analytics
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quantitative research methods
Real Gdp
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softlaunch
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Product details

  • ISBN 9780367077761
  • Weight: 444g
  • Dimensions: 156 x 234mm
  • Publication Date: 26 Feb 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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This book presents and develops the deep data analytics for providing the information needed for successful new product development.

Deep Data Analytics for New Product Development has a simple theme: information about what customers need and want must be extracted from data to effectively guide new product decisions regarding concept development, design, pricing, and marketing. The benefits of reading this book are twofold. The first is an understanding of the stages of a new product development process from ideation through launching and tracking, each supported by information about customers. The second benefit is an understanding of the deep data analytics for extracting that information from data. These analytics, drawn from the statistics, econometrics, market research, and machine learning spaces, are developed in detail and illustrated at each stage of the process with simulated data. The stages of new product development and the supporting deep data analytics at each stage are not presented in isolation of each other, but are presented as a synergistic whole.

This book is recommended reading for analysts involved in new product development. Readers with an analytical bent or who want to develop analytical expertise would also greatly benefit from reading this book, as well as students in business programs.

Walter R. Paczkowski worked at AT&T, AT&T Bell Labs, and AT&T Labs. He founded Data Analytics Corp., a statistical consulting company, in 2001. Dr. Paczkowski is also a part-time lecturer of economics at Rutgers University.

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