- Provides real-world guidance on the application of text analytics for marketing professionals
- Bridges the gap between marketers and data analysis experts by cutting through jargon
- Helps marketers to frame the right questions and apply the results successfully
- Online resources: Self-test questions, chapter review Q&A and an Instructor's Manual with text sources and instructions
Practical Text Analytics
Interpreting Text and Unstructured Data for Business Intelligence
Apply the tools and techniques of text analytics with ease and add value to your company by understanding its key approaches and the business reality behind them.
Key features at a glance
EAN: 9780749474010
Edition: 1
Published:
Format: 233x156
272 pages
About the book
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, Practical Text Analytics 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 resources include self-test questions, chapter review Q&A and an Instructor's Manual with text sources and instructions.
About the authors
Steven Struhl PhD, MBA, MA has more than 25 years' experience in consulting and research, specializing in practical solutions based on statistical models of decision-making and behaviour. In addition to text analytics and data mining, his work addresses how buying decisions are made, optimizing service delivery and product configurations and finding the meaningful differences among products and services. Steven also has taught graduate courses on statistical methods and data analysis. He speaks at conferences and has given numerous seminars on pricing, choice modelling, market segmentation and presenting data.
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.
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