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on 17 April 2017
Excelent book.
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on 21 April 2016
Very good for getting new sources of inspiration in the age of Big Data.
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on 6 June 2017
good, easy reading.
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on 10 June 2013

Having no previous knowledge of predictive analytics, I was a little afraid this book might leave me bewildered. How wrong I was! My eyes were opened, my interest caught and held throughout this fascinating book.

There are many questions that come to mind when reading this book, but as you read on they are all very effectively answered by the author.

Predictive analytics are rooted in everyone's daily lives and can have a substantial effect on their future actions. I like the way Eric Siegel explains, giving examples that can be related to, so that even a total novice like myself has some insight into this fascinating subject.

This book is a must for anyone working in marketing. Even if they have previously explored this area, this book will open their eyes to further insight and could prove to be invaluable. It is also a must for anyone wanting to understand how predictive analytics can work.

I particularly liked the chapter on The Data Effect. Predicting the mood of Blog posts was fascinating, as a blogger myself this held my interest. As for the Far Out, Bizarre and Surprising Insights, well you simply have to read it! I devoured every word! Can early retirement really decrease life expectancy? What does your web browsing signify? This book will reveal all and it is written in such a way to hold the readers interest from start to finish.

What effect do predictions have on the business world? What predictions do famous names such as Google, Facebook, Citybank and others make? There is so much to discover in this easy to read and understand book. Anyone interested in the world of analytics will find this fascinating.

I was surprised at how much I enjoyed this book. Very well explained Dr Siegel! I think this deserves five stars.
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on 13 March 2013
I am new to the field of predictive analytics,and so i was expecting this book to somehow 'give me all the answers' regarding 'How' to conduct prediction along with useful nuggets that would have otherwise have taken me a lot of trial and error to figure out.

However, this book is more of a story that shows where the field came from, who are the main players and how it is being used (and will be used) in various sectors and industries. The book is written very well and is successful in engaging the reader and creating 'Interest' in the field. Although there is little detail regarding how to conduct the modelling, the end result of reading this book is increased awareness and interest in this field, the appendix at the end has lots of great references and recommendations for further reading, providing the detail that i was looking for.
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TOP 500 REVIEWERon 8 May 2013
One dimension of the "Information Age" is the extent to which those who offer a product or service know much more now than ever before about those who are most likely to buy or lease it. Meanwhile, prospective buyers know more now than ever before about that product or service as well as others with which it competes. The implications of this information have wide and deep impact on marketing initiatives to create or increase demand for the given offering. The challenge to those in marketing is to obtain the information they need. Moreover, it must be accurate and sufficient as well as current. Only then can sound predictions be made.

According to Eric Siegel, however, "Learning from data to predict is only the first step. To take the next step and [begin italics] act on predictions [end italics] is to fearlessly gamble...Launching predictive analytics means to act on its predictions, applying what's been learned, what's been discovered within data. It's a leap many take - you can't win if you don't play." How then to improve one's odds? Read this book.

These are among the questions to which Siegel responds:

o Why must a computer learn in order to predict?
o How can "lousy" predictions be extremely valuable?
o Why a predictive model into a field operation? What are the potential benefits of doing that?
o To what extent (if any) do predictive mechanisms place civil liberties at risk?
o How does our emotional online (social media) chatter "flip the meaning of fraud on its head"?
o What actually makes data predictive?
o How does prediction transform risk to opportunity?
o Why does machine learning require both art and science?
o What kind of predictive model can be understood by everyone?
o What key innovation in predictive analytics has crowdsourcing helped to develop?
o Why is human language such a challenge for computers?
o Is artificial intelligence really possible?
o What is the scientific key to persuasion?
o Why is trying to predict human behavior a bad idea?
o How is a person like a quantum particle?

Siegel answers these and other questions throughout seven chapters filled with valuable information, insights, and counsel that enable him to explain how and why predictive analytics possesses "the power to predict who will click, buy, lie, or die." In Appendix A, he cross-references "Five Effects of Prediction," then in Appendix B, he cross-references "Twenty-One Applications of Predictive Analytics." These two appendices will facilitate, indeed expedite frequent review of key material later. The best works of non-fiction are research-driven and that is certainly true of this one, as indicated by 61 pages of notes (Pages 228-289). Until reading this book, almost everything I knew about analytics was learned from Tom Davenport, notably in two of his several books, Competing on Analytics (2007) and Analytics at Work (2011). He wrote the Foreword to Eric Siegel and after noting that we live in a predictive society, suggests, "The best way to prosper in it is to understand the objectives, techniques and limits of predictive models. And the best way to do that is simply to keep reading this book." I agree.
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on 6 May 2013
Not often do I read this type of book from start to end without diverting to another. This one I did, great intro and some stuff in there for the more experienced.
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on 4 February 2017
Good story book, not my type of book. I can explain.. in my experience there are books full of rambling stories about how one person did something vaguely related to the title of the book. Then there are books that teach and enlighten. This book suggests it will educate and show me something useful. In fact, it did not. It is nicely written, just not informative.

If you are new to the field.. this will help open your mind as to what people did. I imagine managers and business folks who want to know what Predictive Analytics actually are and how folks used it... Perfect.

As a large scale 360 stack/client developer this book offered nothing.

Summary - if you are reading this and wondering what Predictive Analytics actually is then buy it. If you know what it is already and simply need to fill a short haul flight, buy it. If you have an understanding of this subject already look around a bit more.
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on 12 July 2015
A great narrative into the field of Predictive Analytics, not much maths, perhaps for the first foray into this field.

Correlation is not Causation. The author debunks the use of judgement and intuition in certain decisions and argues the answer is what the data says, not why. Storytelling is in our nature and this is a difficult leap to make.

While Predictive analytics, in one or guise or another, has been continuing for decades, particularly in insurance, the author skilfully shows how today's computing power is the enabler for both simple, complex and multiple models.

And so what? The author continually links the analysis with an action. It is not analysis for analysis's sake, but a driver for change. This a powerful theme throughout the book.

It's a relatively easy read I strongly recommend the book as an introduction for those with some mathematical/computing background.
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on 19 November 2013
This is a great read. The examples are interesting and relevant to a wide range of areas.

I work in online retail analytics and can immediately see how I might even apply some of the electoral analysis techniques to the business in, say, email marketing etc. Most examples in the book have inspired me to look at problems from a new angle and those that aren't applicable to my domain are interesting nonetheless.

The author doesn't display an arrogance in his tone despite clearly being an expert in the field- I say this after reading some similar books that were far too "smug" for my liking!

I'd recommend this to anyone in the analytics field or anyone even remotely interested in understanding how predictive analytics can be applied to their business.

I'm definitely going to read this again very soon.
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