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Gain a thorough grounding in marketing analytics using Python with this practical guide which balances applied analytics tools with marketing theory.
List of contents
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
About the author
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. Gokhan’s 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. Gokhan’s 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 ESSEC’s grande ecole, as well as on the school’s 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. Kübler’s 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.
Summary
Gain a thorough grounding in marketing analytics using Python with this practical guide which balances applied analytics tools with marketing theory.
