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, it is important to note the intention behind the repetition throughout, as described here: “This book was designed to give as much help as possible to the reader who could not read it in its entirety. Summaries at the end of each chapter are for readers pressed for time or for a quick refresher on the content. This content is compressed from the main chapter materials. Chapters can be read alone, so they at times need to restate pertinent materials from other sections of the book to give complete explanations without the reader turning back.” Dr. Steven Struhl, author of this book.
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.”
From the back cover:
The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field.
Thank you to Netgalley and Kogan Page Ltd for this advance copy.