Practical Text Analytics: Interpreting Text and Unstructured Data for Business Intelligence (Marketing Science) 1st Edition

Practical Text Analytics is precisely the book I was looking for to help create my new Text Analytics course at Zicklin School of Business - the timing of the publishing of this book was perfect, as well.Aside from a reviewers copy I bought the Kindle version so I could better annotate as well as read snippets on the go.So much of what has been published on this subject is written from a very academic and technical perspective that it is nearly unusable for someone that doesn't have a fairly deep expertise in statistics, math and programming, that until Practical Text Analytics, there wasn't a book for "the rest of us", better summarized as"your end user".While there are aspects of the book that, perhaps, could have been better, I am pretty happy with it, as it is - and leave it to others to find any holes - which, in any case, I didn't notice.Remember - Text Analytics is a pretty "nerdy subject" and is unlikely ever to be mainstream - we have to take this book as an attempt to take a very "arcane" subject generally out of reach of most people, and turn it into a subject your average reader can understand - a task the book succeeds at doing quite well.

This book explains text analytics from a high level. There are a decent number of techniques explaining ways of looking at text. Throughout the book are mentions of different tools you can use ranging from free to enterprise level tools.There are also a number of graphs in the book showing the output of results from text analytic tools. I would have like to see more "practical" examples though of how a business should be using these tools. I understand from the book the techniques we have now are not sufficient in many cases.Some of the pictures in the book appeared to be totally random and held little relevance to text. I was wondering why the author placed them there.The writing style is pretty informal which works well for this book. Overall this book is a great place to start for learning about text analytics. If your looking for more advanced cases, or business applications you may need to look elsewhere.

Many spelling mistakes. A lot of repeated information. Many charts with simple errors.

As a Voice of customer and Text analytics practitioner I have a little bit of background in this field and I found the book really helpful in explaining the text analytics field from a practical point of view .Most of the concepts which may usually be too math oriented or hard to understand are explained in general English. I specially like the chapter on Bayesian analysis which had eluded me as a tool so far but the book does a good job in explaining the use and power of the algorithm.Text is everywhere and aggregating and analyzing text remains one of the most valuable frontier for Enterprise Software and for general public alike.

I needed a rapid introduction to the field of text analytics. This book did the trick. I found the book very clear and easy to follow. It was not dry or boring. The author provided easy to understand examples, provided recommendations for the most appropriate software, reduced jargon to the absolute minimum, and even spiced things up with humor now and then.

Here is a fascinating, if not rather specialist book, which aims to be an accessible guide to the world of text analytics and data analysis for marketing folk.As an upmarket “how-to guide”, the author has sought to make this a jargon-restricted zone, showing working methodologies and actionable strategies for the use of text analytics without dumbing it down to an absurd, useless level. As the book’s marketing materials note, the book: “…presents the process of analysis in ways that people who use the data need to see them, helping marketers to clarify and organise confidently the confusing array of methods, frame the right questions and apply the results successfully to find meaning in any unstructured data and develop powerful new marketing strategies.”This book may make your head ache at first if this subject is entirely new, yet just think how even more difficult it could be if it did not have the benefit of the author’s simple, sympathetic and at times humorous treatment to make it so reader-friendly! The author aims to get you understanding how text analytics can be used within your organisation, enabling you to perhaps have a go yourself as well as liaising with programmers and external vendors who may use a strange language that vaguely resembles English (or your country’s language) peppered in with a lot of mysterious jargon for good measure.Text that you could, should or may need to analyse can be everywhere and a lot of it, most of it, may be unstructured. Dependent on your needs a lot of this text can yield insights into what people might be thinking, feeling or saying about your company and its products. It might even allow you to guess what they are looking for and not finding. The world can literally at your fingertips, as long as you suck in enough data and manage to sufficiently analyse it.Are you still confused? It does not help that terms such as data and information may be used interchangeably. The author seeks to clarify matters, saying: “Anything that can be collected in any fashion counts as data. Noise from a cell phone tower is data. Mistranslated text is data. Propaganda is data. Data exists, but may not have any purpose. It is not information. The distinction is essential. Information conveys valuable new insights, telling us about something that we did not expect, or allowing us to deal with an unusual contingency. We often encounter the belief that having a great deal of data also means that we must have something interesting. Some writers have even made a point of saying, apparently earnestly, that more data is always better. This is not true. In many cases, this assertion can be completely backward. If the data you have at hand mainly is not useful, more of it makes it harder for you to find what you need, not easier. As valuable items get overrun by useless ones, they become more elusive, and may even vanish from sight entirely. Knowing where to look, as well as how to do the analysis, becomes critical with data that is not structured.”There is a phrase about “not seeing the wood for the trees” in English that can be applied here. The author hopes that you will be able to see right through the forest of text after applying a “filter” with the help of text analytics, making an information pathway through the forest of noise as you go.Certainly this seems to be a valiant, great attempt at demystifying a very complex being. Should you have a need for this book, the author might be your literary knight in shining armour.

Great book that explains the practicals of the methods. Allowed me to find techniques that may help me and go learn the algorithms.

Nice overall about text analysis. Great for someone unknowing.