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The Machine Age of Customer Insight

Martin Einhorn
Porsche, Germany

Michael Löffler
Porsche, Germany

Emanuel de Bellis
University of Lausanne, Switzerland

Andreas Herrmann
University of St. Gallen, Switzerland

Pia Burghartz
University of St. Gallen, Switzerland


Product Details
Format:
Paperback
ISBN:
9781839096976
Published:
15 Mar 2021
Publisher:
Emerald Publishing Limited
Dimensions:
256 pages - 171 x 248mm
We are living in a new machine age offering unique opportunities, particularly for generating customer insights, which is radically transforming the way business value is created. Across industries, players are affected by the pace of progress of machine learning tools, novel technologies, and the abundance of data. These developments require mastering new capabilities.

The Machine Age of Customer Insight explains the transformation of customer insights and demonstrates the growing impact of machine learning. Thought leaders from renowned universities in the US and Europe as well as from different industries provide a comprehensive overview. Addressing both academics and practitioners, they discuss the transformation, cutting edge tools, and success factors to thrive in the new age.

The book shows how machine learning helps to understand customers better and faster. It supports everyone who considers the machine age a great opportunity to gain a competitive advantage by transforming customer insights into business value.
Introduction; Martin Einhorn, Michael Löffler, Emanuel de Bellis, Andreas Herrmann, and Pia Burghartz
Chapter 1. Transformation of Customer Insights; Martin Einhorn and Michael Löffler
Chapter 2. Intelligent Applications in the Modern Sales Organization; Gilberto Picareta, Martin Kloehn, and Eugenie Weissheim
Chapter 3. Voice and Facial Coding in Market Research; Niels Neudecker, Deepak Varma, David Wright, and Robert Powell
Chapter 4. Machine-Driven Content Marketing; Javiera M. Guedes, Akinbami Akinwale, and María Requemán Fontecha 
Chapter 5. Leveraging Customer Insights with 5G; Marco Ottawa
Chapter 6. Overview of Machine Learning Tools; Brett Lantz
Chapter 7. Neural Networks and Deep Learning; Hongming Wang, Ryszard Czerminski, and Andrew C. Jamieson
Chapter 8. Classification Using Decision Tree Ensembles; Jochen Hartmann
Chapter 9. Text Analytics and Natural Language Processing; Ted Kwartler
Chapter 10. A Step-By-Step Guide for Data Scraping; Reto Hofstetter
Chapter 11. Data Privacy: A Driver for a Competitive Advantage; Timo Jakobi, Max von Grafenstein, and Thomas Schildhauer
Chapter 12. Data Growth: Generating Business Value with Cloud Services; David Mingle
Chapter 13. Data Technology: Turning Business Data Into Business Value; Gerrit Kazmaier
Chapter 14. Data Competitions: Crowdsourcing With Data Science Platforms; Jenny Lena Zimmermann
Chapter 15. Data Processing: Kontosensor as an Application of Predictive Analytics; Raimund Blache, Lars Fetzer, René Michel, and Tobias von Martens
Chapter 16. Data Visualization: The Power of Storytelling; Ted Frank
Dr. Martin Einhorn is Director of Customer Evaluation and Analytics at Porsche and lecturer at Sigmund Freud University Vienna.

Dr. Michael Löffler is Vice President for Sales Planning and Strategy at Porsche, leading several departments responsible for sales and marketing strategy, worldwide training, organizational development, and innovation.

Prof. Dr. Emanuel de Bellis is Assistant Professor of Marketing at the University of Lausanne. His research explores how consumers perceive and use autonomous products and other AI-based technologies.

Prof. Dr. Andreas Herrmann is Director for Marketing and Research Methods at the Institute for Customer Insight at the University of St. Gallen and Visiting Professor at the London School of Political Science.

Pia Burghartz is a PhD candidate and research associate at the Institute for Customer Insight at the University of St. Gallen. Her research deals with consumers' acceptance of autonomous driving and shared mobility.

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