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Recommendation Engine Book Review – Highly Recommended

by Mark P. McDonald  |  September 8, 2020  |  3 Comments

Recommendations implicitly and explicitly drive eCommerce and the digital world.  Recommendations are so ubiquitous that it is easy to lose sight of them or their influence.  From what you see in search, to articles on web content, to products appearing on websites, recommendations sit at the core of our world.

Michael Schrage at MIT’s Sloan School of Management’s Initiative on the Digital Economy has written a definitive book about recommendation engines, entitled Recommendation Engines.  This is a highly recommended and unique book that is readily accessible to technologists, business leaders and the general public.  The book is part of MIT’s essential knowledge series which seeks to provide “foundational knowledge that informs a principles understanding of the world.”  That sounds a little academic, but Schrage’s interpretation is an informative and thoughtful approach to a topic that can easily seem arcane or too technical.

Overall, highly recommended book about recommendations.  Here is why:

  • The topic is more important than you think.  Recommendations are calls to actions emerging from artificial intelligence, machine learning and process automation.  They are the part that you see and feel. Understanding them is important as they create bias, limits etc. to who you are and how you can use the internet and digital world.
  • Schrage’s treatment of the topic is comprehensive and logically structured.  The opening chapters talk about the role of recommendations in general, then the later chapters move to discuss how digital recommendations work and finally their long-term implications on us personally and as a society.  The progressions are clear, build on one another and never overwhelm the reader.  Schrage makes both a great argument and exposition of complicated topic.
  • The book is balanced supporting the reader making up their own mind.  Too many books about technology exist at the extremes: machine dystopia or digital euphoria.  Schrage presents observations, cites a range of high-quality research studies, etc. to present the issue.  This is an essential knowledge book not an opinion or angle pressed by the author.
  • The book includes a wide range of examples and illustrations.  These go well beyond the usual suspects of Netflix, Amazon, Google etc. This gives the book depth and the examples that illustrate the pervasive nature of recommendations.
  • The book is clearly written and accessible to readers with different levels of technical or business knowledge.  This is a real trick that Schrage pulls off and it makes for good and thoughtful reading.
  • The one drawback that I found is the books size.  It is part of MIT’s’ move to ‘pocket-sized’ sides books. It is small, but that makes it thick and not the most comfortable to hold in your hand.  Suggestion is to think about purchasing a digital version.
  • Selected Quotes

Here are some statements from the book that I found particularly informative and valuable.  They should give you an idea of the tone and treatment of recommendation engines:

Recommenders prioritize the world’s most relevant options and choices for your consideration; those recommendations ostensibly reflect one’s tacit and explicit desires: that slice of the world that matters most to you.

The future of choice may well be found in the future of recommenders.

The absence of recommenders virtually guarantees commercial underperformance.

Truly successful recommender transcend commercial exchange; they promote personal curiosity and discovery.

Three overarching design themes predominate; content-based systems that rely on the properties and characteristics of items; collective filtering systems that recommend items based on similarity measures computed between users; and hybrid systems that ensemble the best aspects and element of content and collaboration filtering systems to produce commendations that are superior to either alone.

Recommendation, suggestion and advice cannot be meaningfully divorced from how they are framed.

The real future if AI behind the recommender future isn’t artificial intelligence but augmented introspection.


  1. What recommenders are/Why recommenders Matter – discusses the role of recommendation and its centrality in a world where there are more choices than anyone can manage on their own.
  2. On the Origins of Recommendation – a look at the purpose and role that recommendation has had on individuals and society. This chapter was enlightening for the realization that we have always lived with and been shaped by recommendations.
  3. A Brief History of Recommendation Engines – covers the nature of recommendations with a focus on how they work in the digital age. Very informative.
  4. How Recommenders Work – perhaps the most difficult chapter to write, Schrage walks people through the recommender math and technology without requiring a Ph.D.
  5. Experiencing Recommendations – points the centrality of user design and customer experience in creating recommendation, shaping choices etc. This chapter includes a strong discussion of behavioral economics, choice framing and other factors driving recommendations.
  6. Recommendation Innovators – features deep dives into Spotify, Byte Dance and Stitch Fix who have all innovated in this area.
  7. The Recommender Future – reviews the different ways people look at recommendations and technology.

Final Impressions

If anyone would have told me that I would put down reading a summer thriller to read about recommendation engines, I would have said yeah right.  But that is exactly what happened.  The book draws you in, not like a thriller, but with the realization that recommendations are everywhere and shaping view on everything.

This is one of the few books that makes you better informed, aware and conscious of things – a book well worth your time if you are interested.


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Category: analytics  analytics-and-bi-solutions  analytics-and-bi-solutions  book-review  digital-marketing  digital-society  human-ability  management  marketing  technology  

Mark McDonald
VP Analyst
12 years at Gartner
33 years IT Industry

Mark McDonald, Ph.D., is a Vice President and Fellow Emeritus in Gartner for General Managers Program. Read Full Bio

Thoughts on Recommendation Engine Book Review – Highly Recommended

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