‘An excellent all-in-one primer for today’s marketer and researcher. This is clear,
to the point and a comprehensive guide to this complex field.’ Louis A Tucci
PhD, Associate Professor of Marketing, The College of New Jersey
‘Dr Struhl does an excellent job of explaining the strengths and weaknesses
of methods of predicting consumer behaviour. This book is thoughtful,
well-written, and also a practical book for marketers, marketing researchers
and business consultants. If you help organizations make decisions, the
best decision you can make right now is to read this book.’ David F Harris,
author of The Complete Guide to Writing Questionnaires: How to get better
information for better decisions
‘Artificial Intelligence Marketing and Predicting Consumer Choice clearly explains
the tools that drive sophisticated market research. I heartily recommend this
book for anyone looking for greater insight and success with cutting-edge
techniques.’ Robert Kaminsky, President, MedSpan Research
‘For researchers who want to tackle the complex tasks of predicting consumer
choices and creating market simulations, this book is a great one-stop reference.
In easy-to-read style with plenty of useful examples, the author covers
conventional multivariate data analysis techniques (conjoint, discrete choice,
CHAID, regression) as well as the latest ones (Hierarchical Bayesian analysis). The
book also includes many key concepts and definitions useful for any quantitative
researcher, such as statistical significance, sampling, and more.’ Kathryn
Korostoff, Lead Instructor and Founder, Research Rockstar LLC
‘This book covers an extensive set of methods for predicting consumer choices,
including conjoint analysis, discrete choice modelling, neural networks,
classification trees, Bayesian methods, and so much more. Dr Struhl has written
a genuinely practical guide to predictive analytics that is so easy, it reads like a
bedtime reader. Having been a practitioner in this area for over 20 years, I found
this book to not only be informative for a pertinent 21st century topic, but also a
fun read.’ Don Meyer, Client Director, Analytics, AC Nielsen
‘I’ve been working with Dr Struhl for the past two and a half years and am truly
impressed by his expertise. His book covers a truly expansive range of methods
for predicting consumer choices. These include neural networks, ensembles,
Bayesian Networks and classification trees. He also talks about how more
established methods such as conjoint analysis and discrete choice modelling
have benefited from machine learning methods. Here you will find the best
applications of each approach, with plenty of examples from real life, showing
what works and what does not. The online, downloadable simulator programs
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