Gokhan Yildirim, Raoul V. Kübler

Applied Marketing Analytics Using Python (eBook, ePUB)

• Format: ePub

Produktbeschreibung

It is 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 Python, 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.

Supporting online resources include datasets and software codes and solutions as well as PowerPoint slides, a teaching guide and a testbank. This book is essential reading for advanced level marketing students and 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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Produktdetails

• Verlag: SAGE Publications
• Seitenzahl: 384
• Erscheinungstermin: 21. März 2025
• Englisch
• ISBN-13: 9781036201937
• Artikelnr.: 72258561

Autorenporträt

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.

Inhaltsangabe

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