Title: Practical Text Analytics: Interpreting Text and Unstructured Data for Business Intelligence
Publisher: Kogan Page Ltd
Publication Date: 2016
Language: English
ISBN 10: 074947937X
ISBN 13: 9780749479374
Binding: Hardback
Condition: New
Weight: 565 grams

About this title

Synopsis

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 Author

Dr. Steven Struhl PhD, MBA, MA has more than 25 years' experience in consulting and research, specialising 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, optimising service delivery and product configurations and finding the meaningful differences among products and services.

Steven Struhl 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.

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