EW BOOK: Top thought leaders from academia and industry combine to share a state-of-the-art overview of how the business world is set to transform in The Machine Age of Customer Insight
Why this book matters:
- Clearly demonstrates the growing impact of machine learning and data analytics and how this is transforming customer insights
- Combines an academic overview of machine learning with industry information providing a unique bridge between the two
- Includes practical case studies from well-known companies from a variety of industries such as marketing, IT, banking, and telecommunications
- Reveals the opportunities and challenges of the transformation process for businesses in general and for customer insights in particular
- Gives support for those who consider the machine age of customer insight as a big opportunity and convinces those who are still skeptical by means of practical use cases
- Short, concise chapters written by outstanding thought leaders from renowned universities in Europe & the US and from innovative firms in different industries
- An essential read for professionals, researchers, and students alike
We are now entering a new machine age. Emerging machine learning technologies are reaching the mainstream, transforming the way business value is created, and the race to harness the benefits for better insight-based decision making is on.
Across industries, players are affected by the pace of progress of machine learning tools, developing technologies and the abundance of data, but businesses must master these new capabilities to generate the insights that will enable them to thrive in this new age.
New book, The Machine Age of Customer Insight offers a short pit stop in the race for better, faster customer insights from machine learning tools. It explains the transformation, its growing impact, and the necessary capabilities for organisations to invest in. It provides a comprehensive, practical overview which addresses both academics and practitioners providing a unique bridge between the two.
The Machine Age of Customer Insight illustrates the opportunities and challenges of the transformation process for businesses in general, and specifically for customer insights which has been accelerated by the pandemic, drawing upon case studies of how well-known companies have gained a competitive advantage by transforming customer insights into business value. It also discusses the success factors in using machine learning tools including using data privacy for competitive advantage and data collection and the experience economy.
Written by leading thought leaders from renowned universities in Europe and the United States as well as from innovative firms, this book is divided in three sections which explore key areas:
. How the field of customer insights is being transformed
. Analytical tools which can generate customer insights
. How the management of customer insights can lead to success
Each section includes short, concise chapters written by the different thought leaders on topics of their expertise. It is an essential read for business leaders, students, researchers, and professionals alike.
The Machine Age of Customer Insight by Martin Einhorn, Michael Löffler, Emanuel de Bellis, Andreas Herrmann, and Pia Burghartz, published by Emerald, available on Amazon.
EXCLUSIVE ARTICLES AND INTERVIEWS AVAILABLE:
The authors of The Machine Age of Customer Insight are highly respected thought leaders in their field, and are available for expert comment, guest articles and interviews on a range of customer insight and AI topics including:
. 5 ways AI is transforming customer insights
. How voice and facial coding can be used in market research
. Leveraging customer insights with 5G
. Machine learning tools: a brief overview
. A step-by-step guide for data scraping
. How data privacy will be a drive for competitive advantage
. What is the experience economy and should your company care?
. How to turn business data into business value
. How the pandemic has accelerated AI customer insights
About the authors:
Dr. Martin Einhorn is Director of Customer Evaluation and Analytics at Porsche AG and lecturer at Sigmund Freud University Vienna.
Prof. Dr. Michael Löffler is Vice President for Sales Planning and Strategy at Porsche AG, leading several departments responsible for sales and marketing strategy, worldwide training, organisational 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.
Hernaldo Turrillo is a writer and author specialised in innovation, AI, DLT, SMEs, trading, investing and new trends in technology and business. He has been working for ztudium group since 2017. He is the editor of openbusinesscouncil.org, tradersdna.com, hedgethink.com, and writes regularly for intelligenthq.com, socialmediacouncil.eu. Hernaldo was born in Spain and finally settled in London, United Kingdom, after a few years of personal growth. Hernaldo finished his Journalism bachelor degree in the University of Seville, Spain, and began working as reporter in the newspaper, Europa Sur, writing about Politics and Society. He also worked as community manager and marketing advisor in Los Barrios, Spain. Innovation, technology, politics and economy are his main interests, with special focus on new trends and ethical projects. He enjoys finding himself getting lost in words, explaining what he understands from the world and helping others. Besides a journalist, he is also a thinker and proactive in digital transformation strategies. Knowledge and ideas have no limits.