The Blurb On The Back:
AI For Marketing And Product Innovation offers product innovators, creative talent and marketing professionals a hands-on and highly accessible guide to artificial intelligence (AI) and machine learning (ML). The authors (a team of experts at the intersection of neuroscience, technology, insights, and marketing) reveal how to harness AI and ML to accelerate product innovation and marketing. These two powerful new tools stand poised to revolutionize the way we sell products and make innovative breakthroughs.
This vital resource explores a wide range of business-related topics, from innovation, branding, pricing and promotions, creative storytelling to the future of market research and advertising agencies. All the techniques presented in the book have become algorithms and serve as real-life examples of AI and ML at work. In addition, the authors outline the resources, the skills, best practices, terminology, and metrics required to harness the unparalleled and rapidly expanding power of these twin technologies. AI For Marketing And Product Innovation provides an in-depth look at what AI is, what it can – and cannot – do, and contains practical ideas and insights on ways in which to apply that knowledge to your business and career development.
Throughout the book, the authors neither resort to mathematical mumbo-jumbo nor do they present an endless array of irrelevant case studies. Instead, they challenge us to “Think Different”. AI For Marketing And Product Innovation is filled with the information needed to understand the practical business implications of Artificial Intelligence and Machine Learning. In clear terms, the book shows how to put them to work to gain a competitive advantage in today’s increasingly digitally-driven economy.
You can order AI For Marketing And Product Innovation by A K Pradeep, Andrew Appel and Stan Sthanunathan from Amazon USA, Amazon UK, Waterstone’s or Bookshop.org UK. I earn commission on any purchases made through these links.
The Review (Cut For Spoilers):
Dr A. K. Pradeep is the CEO of machineVantage, a start-up applying artificial intelligence (AI) and machine learning (ML) to marketing problems. Andrew Appel is CEO of IRI, a technology solutions company for the consumer, retail and media sector. Stan Sthanunathan is Global EVP of Consumer and Market Insights for Unilever.
Although Pradeep, Appel and Sthanunathan’s all have strong credentials in AI, ML and marketing and product innovation, I found this a really difficult book to follow because the early sections concentrate on the maths underpinning what AI and ML can do and it doesn’t really show you how AI and ML can make a difference to marketing and product strategy. If you’re already proficient in the subject, it may offer you more than it does to a beginner.
The first 6 chapters in the book focus on explaining what AI and ML is and how they can be used to analyse data and make predictions. There is a lot of maths and statistics in these chapters, which – having not progressed beyond maths GCSE – I found incredibly difficult to follow. Pradeep, Appel and Sthanunathan use a conversational style to take the reader through concepts like neural networks, deep learning algorithms, clustering and classification algorithms, principled component analysis, supervised, unsupervised and reinforced learning but they constantly disappear down rabbit holes of mathematical theorems (e.g. two-dimensional Voronoi cells, which I read and re-read several times and still didn’t understand at the end). I guess that if you’re already familiar with using maths to work on product and market segmentation and innovation, then you would find these useful but for newcomers they are really alienating, and I say that as someone who has read a number of books on AI and ML and so is not a complete newbie to the subject.
There is more utility in the remaining chapters, which take the reader through the applications to which AI and ML can be put, focusing on product innovation, pricing dynamics, promotions and offers, customer segmentation, brand development, tracking, and naming, and creative storytelling and advertising. For example, I was interested in the creative storytelling chapter, which sets out how AI and ML can help identify emotional connectors and compelling story arcs for an advertising campaign, but there’s no real analysis of what the down side of all that analysis is and how users can avoid AI/ML assisting in the creation of campaigns that rapidly get ‘samey’. Nor are there any real examples of where AI/ML get things wrong – this is very much one of those books that spin you on the positives and the labour saving elements rather than in the ‘here be dragons’ dangers to be aware of. Given Pradeep and Appel’s day jobs, this is perhaps to be expected, but it would have been good to get Sthanunathan’s perspective on that from the business consumer side. Also, it’s worth pointing out that the marketing/product innovation chapters are all rich in their own industry jargon which I found easer to follow but still almost as alienating as the reliance on maths in the opening chapters.
All in all, this clearly isn’t a book for absolute beginners in the subject, but I have to question how much even experts would get from this given that it seems more orientated at explaining how AI and ML can help professionals to do what they already do better, than how they can take their sector forward in terms of innovation. This is especially disappointing given that the blurb emphasises the practical ideas and insights on offer here and I just didn’t see it. I would also say that there’s a lot of reliance on quotes and extracts from films and books, which I don’t think brought anything to the table and just became an irritating ‘word salad’ that I flicked past to get to the more substantial stuff.
Thanks to the Amazon Vine Programme for the review copy of this book.