Not an easy book to read, but for the AI practitioner a source of ideas and important recipes to implement.

Great tool to develop marketing strategies.
The author's experience and work is extensive, well grounded and has real applications that have been tested for many years. The content of the book is of first quality, very informative and with well explained examples, focused on educating practitioners, students, marketers, in the analysis of the prediction of consumer choices. Understanding how consumers make their choices for different situations involves the use of different methods and strategies that are appropriate for each circumstance.
The value of this book is that it allows an expanded view of the different perspectives, so that a correct planning can be carried out according to each project, applying the appropriate methods for each situation, constructing the models that best fit the target consumer, counting with tools to process and understand the results, apply the results to use them in the best way, for example to choose the best features and setting the best price. All explained in a clear and comprehensive way so that the student understands what works best.
My gratitude to the Publisher and NetGalley for allowing me to review the book

This is a challenging book to review. The information covered reminded me of key research principles and their importance as well as highlighted advances in the field. However, the pacing of the book is pedestrian and the repetition throughout, tiresome. When considering the question "Would I recommend it?" I realised I have several to whom I will recommend this book! One is a friend in need of a grounding in research, as she has no experience. Another is a friend who is completing a doctorate and is reviewing research options. It is well compiled, extensive, easy to understand and interesting. If you pick it up intending to read only those aspects relevant to you, you will thoroughly enjoy the experience.

My favourite quotes include:

"More data of the wrong type actually is bad for you. If you are looking for a needle in a haystack it does not help to have a larger haystack. While it is a worthwhile goal to collect as much data as possible, data quality, and knowing which data will address your needs, remain paramount."

"So why focus groups? Aside from detecting disasters, these groups have several valuable applications. You learn about the language that people use in discussing the product, and in particular the terminology that they can understand."

"Experience shows that, for a reasonably sized experiment, 125 per group you want to measure separately is safe and reliable."

Very heavy in Statistics. Artificial Intelligence Marketing and predicting consumer Choice by Steven Struhl has academic tendency. It will make a great book for students and learners.