Artificial Intelligence Marketing and Predicting Consumer Choice

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.

Despite being a bit of a specialist read, this book is a fascinating look at how artificial intelligence can aid the marketing process and help forecast or “predict” consumer choice and selection.

The author provides accessible insight into this developing segment, detailing some of the tools and techniques that are current to help try and get into the mind of the consumer. There is no one-size-fits-all best solution and nothing is guaranteed, but after reading this book you will be better informed to understand the subject area and able to make informed deployment and usage decisions. You will end up with a toolbox with more than one hammer! The book’s low price enables even the non-specialist a chance to learn more about this fascinating subject too and maybe even get some knowledge that can be deployed elsewhere.

Now, despite this being quite accessible, there are parts that might make your eyes bleed such as the statistics and mathematics… If that is the case, you can still skip over these bits and yet get a lot of beneficial ground-level knowledge. It naturally focussed towards an academic/professional bias, with lots of references and so forth, but it manages to be a good information source for several disparate audience groups at the same time. Even some humour can emerge from within!

Artificial intelligence and learning is not new – it is a decades-old technique – although clearly the usage cases have been increasing in complexity and the degree of intelligence has been rising. More and more “intelligent donkey work” can be done, and faster too. The author carefully defines matters and helps clear up misunderstandings that may sound on one hand as nit-picking, such as the difference between prediction and forecasting or data and information, but it does make sense when you follow and understand the rationale, even if they can be often interchanged as shorthand. You can be better informed on so many levels; just set your expectations closer to deliverable reality.

One feature that was very useful (unlike in many books) was the chapter round-up, as that gives a great aide-memoire in clear, understandable language about what you (should) have been reading.

All in all, one of those little books that you may have not thought you needed to read, but you could be very glad you did later. If you already know you have a definitive need for it, prepare to receive a little goldmine.

Artificial Intelligence Marketing and Predicting Consumer Choice, written by Steven Struhl and published by Kogan Page. ISBN 9780749479558. YYYYY

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."

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

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