Download PDF Practical Text Analytics: Interpreting Text and Unstructured Data for Business Intelligence (Marketing Science), by Steven Struhl
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Practical Text Analytics: Interpreting Text and Unstructured Data for Business Intelligence (Marketing Science), by Steven Struhl
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In an age where customer opinion and feedback can have an immediate, major effect upon the success of a business or organization, marketers must have the ability to analyze unstructured data in everything from social media and internet reviews to customer surveys and phone logs. Practical Text Analytics is an essential daily reference resource, providing real-world guidance on the effective application of text analytics. The book presents the analysis process so that it is immediately understood by the marketing professionals who must use it, so they can apply proven concepts and methods correctly and with confidence.
By decoding industry terminology and demonstrating practical application of data models once reserved for experts, this book shows marketers how to frame the right questions, identify key themes and find hidden meaning from unstructured data. Readers will learn to develop powerful new marketing strategies to elevate customer experience, solidify brand value and elevate reputation.
Online supporting resources include questions and answers for each chapter, figures from Chapter 3 and a brief overview of text sources for text analytics.
About the series: The Marketing Science series makes difficult topics accessible to marketing students and practitioners by grounding them in business reality. Each book is written by an expert in the field and includes case studies and illustrations enabling marketers to gain confidence in applying the tools and techniques and in commissioning external research.
- Sales Rank: #533328 in eBooks
- Published on: 2015-07-03
- Released on: 2015-07-03
- Format: Kindle eBook
Review
"[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." (Darren Ingram Darren Ingram Media)
"Textual analysis has recently become a useful research methodology, of great interest to both academics and practitioners. Dr. Steven Struhl provides relevant and lucid discussion of the topic, highlighting the fundamental issues involved in preparing, analyzing, and presenting textual data for meaningful interpretations. A very interesting and timely contribution that should be of interest to a wide range of audiences." (Dr. Jehoshua Eliashberg Prof of Operations & Info Management, Wharton School, Univ. of Pennsylvania)
"As I’ve been evaluating text analytics materials lately for my data science education engagements, much of what I’ve found published on this subject is written from a very academic and technical perspective that is not very approachable for someone that doesn’t have a fairly deep expertise in statistics, math and programming. This book solves that disconnect...A welcome addition to any data scientist’s library. In addition, the timely nature of the subject should provide much food-for-thought as the rise in interest in unstructured data processing techniques continues to be of interest. Highly recommended." (Daniel D. Gutierrez Inside Big Data)
About the Author
Steven Struhl is Principal at Converge Analytic, a marketing and analytics consulting company based in New Jersey. He has experience in consulting and research, specializing in providing effective, practical solutions based on statistical models of decision-making and behavior. His work addresses how buying decisions are made, understanding consumer groups and their motivations, optimizing service delivery and product configurations, and finding the meaningful differences among products and services.
Most helpful customer reviews
0 of 1 people found the following review helpful.
Good book
By Autamme_dot_com
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.
0 of 0 people found the following review helpful.
Summarizes Text Analytics Well
By William P Ross
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.
0 of 0 people found the following review helpful.
Explains Text Analytics in simple english
By kaus_man
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.
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