Marketing has become increasingly data-driven in recent years as a result of new emerging technologies such as AI, granular data availability and ever-growing analytics tools. With this trend only set to continue, its vital for marketers today to be comfortable in their use of data and quantitative approaches and have a thorough grounding in understanding and using marketing analytics in order to gain insights, support strategic decision-making, solve marketing problems, maximise value and achieve success.
Taking a very hands-on approach with the use of real-world datasets, case studies and R (a free statistical package), this book supports students and practitioners to explore a range of marketing phenomena using various applied analytics tools, with a balanced mix of technical coverage alongside marketing theory and frameworks. Chapters include learning objectives, figures, tables and questions to help facilitate learning.
Supporting online resources are available to instructors to support teaching, including datasets and software codes and solutions (R Markdowns, HTML files) as well as PowerPoint slides, a teaching guide and a testbank.
This book is essential reading for advanced level marketing students and marketing practitioners who want to become cutting-edge marketers.
Dr. Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, London.
Dr. Raoul V. Kübler is an Associate Professor of Marketing at ESSEC Business School, Paris.
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There are good books on marketing principles, on analytical models and on statistical software, but not on the combination of these three areas. This is where Applied Marketing Analytics Using R breaks new ground and offers exceptional value to the practice of marketing model building. The marketing decision areas are carefully selected, the modeling principles are well explained, and the case studies offer relevant applications of the R software modules. I recommend this book with enthusiasm! -- Dominique M. Hanssens Kubler and Yildirim manage to mix tried-and-true marketing models with recent advances in machine learning to offer a coherent, practical, and down-to-earth toolbox for data-driven marketers. A must-have for modern marketing managers. -- Arnaud De Bruyn This book brings a much-needed practical perspective to scientifically sophisticated marketing analytics. The authors Gokhan and Raoul truly represent the best of both worlds, being both accomplished marketing academics and practical data scientists. They start each chapter with a case study ranging from US banks to EU skincare, and UK airlines to Turkish kitchens and Finnish game developers. I love the natural flow of the book chapters, following the market orientation structure of segmentation, targeting, positioning and marketing mix modeling. At the same time, the authors demonstrate the value of adding the latest tools in attribution, online chatter and image mining. They explain every step both in the marketing strategy process and in the software installation and implementation. As to the latter, the R exercises give you hands-on experience in the latest in marketing analytics, which helps you optimize your decisions and shine in the marketplace. -- Koen Pauwels Applied Marketing Analytics using R is an exceptional resource for individuals eager to achieve business success and students seeking an extensive exploration of marketing analytics and R. Unlike many purely academic books, Yildirim from Imperial College and Kubler from ESSEC seamlessly blend a rigorous academic perspective with a practical approach to solving real-world marketing problems. This comprehensive guide takes you through the entire A to Z process of marketing analytics, covering everything from fundamental data sets and visualization techniques to advanced statistical modeling and its business implications. The inclusion of insightful case studies further enhances the practicality of the book, offering valuable applications of marketing analytics. By delving into this book, marketing researchers can elevate their skills and expertise, making it an indispensable resource for anyone serious about pursuing analytics in the field of marketing. Overall, this book makes a significant contribution to the field and is highly recommended! -- Shuba Srinivasan
Chapter 1: Introduction
Chapter 2: Customer Segmentation
Chapter 3: Marketing Mix Modelling
Chapter 4: Attribution Modelling
Chapter 5: User Generated Data Analytics
Chapter 6: Customer Mindset Metrics
Chapter 7: Text Mining
Chapter 8: Churn Prediction and Marketing Classification Models With Supervised Learning
Chapter 9: Demand Forecasting
Chapter 10: Image Analytics
Chapter 11: Data Project Management and General Recommendations
Dr. Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School where he teaches on the full-time MBA, executive MBA and MSc Business Analytics programs. Gokhans research is at the intersection of marketing effectiveness, metrics and models. He quantifies how marketing actions impact offline and online consumer behaviour, and how changes in consumer attitudes in turn drive company performance. Specifically, his research concerns short vs. long-term effectiveness of digital and non-digital marketing activities, cross-channel marketing resource allocation, and consumer attitudinal metrics for guiding marketing decisions. He uses applied time-series econometrics and machine learning tools to offer managerial insights in these areas. Gokhans academic work appeared in leading journals of the field such as Journal of Marketing, Marketing Science and International Journal of Research in Marketing. He is one of the recipients of the prestigious ISMS-MSI Gary Lilien Practice Prize award. Dr. Raoul Kübler is an Associate Professor of Marketing at ESSEC Business School in Cergy/Paris where he teaches on the FT Top10 ranked Master in Management program of ESSECs grande ecole, as well as on the schools Global MBA and the executive MBA. Before joining ESSEC he was from 2018 until 2022 a Junior Professor at the University of Münster, and worked from 2012 until 2018 as an Assistant Professor of Marketing at Özyegin University in Istanbul, Turkey. In his research, he examines how marketers can leverage user generated content and social media data in combination with machine learning and artificial intelligence to derive better marketing decisions. His research focus is largely guided by his close collaboration with marketing professionals. He consulted leading international companies such as TetraPak, Rausch AG Switzerland, Dr. Wolff Group, PepsiCo Turkey, Sisecam Turkey, Garanti Bank, GfK, and OD Yachting in digital marketing issues. Dr. Küblers research is frequently published in leading international marketing and business journals such as the Journal of Marketing, the Journal of the Academy of Marketing Science, the Journal of Interactive Marketing and the Journal of Cultural Economics. Furthermore, Raoul has been ranked since 2018 within the top 10% of most successful business scholars in Germany, Switzerland, and Austria according to A+ publications, of which some have been awarded by institutions such as MSI, Marketing EDGE, and EMAC.
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