Applied marketing analytics using R

By:

Yildirim, Gokhan

Contributor(s):

Kubler, Raoul

Material type: Text

TextPublication details: Sage Publication Pvt Ltd. London 2023Description: xiv, 369 pISBN:

9781529768725

Subject(s):

DDC classification:

658.8342 YIL

Summary: 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, 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 (https://us.sagepub.com/en-us/nam/applied-marketing-analytics-using-r/book277514)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Marketing	658.8342 YIL (Browse shelf(Opens below))	1	Available		006817

Table of content:
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
[https://us.sagepub.com/en-us/nam/applied-marketing-analytics-using-r/book277514#contents]

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, 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
(https://us.sagepub.com/en-us/nam/applied-marketing-analytics-using-r/book277514)

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