Description
Book SynopsisMarketing 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, it’s 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.
Trade Review‘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
Table of ContentsChapter 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
