TY  - BOOK
AU  - Verhoef, Peter C.
AU  - Kooge, Edwin
AU  - Walk, Natasha
TI  - Creating value with data analytics in marketing: : mastering data science
SN  - 9780367819798
U1  - 658.83 
PY  - 2022///
CY  - London
PB  - Routledge
KW  - Marketing--Data processing
KW  - Big data
KW  - Consumer profiling
N1  - Table of Contents
1 Data science and big data

2 Creating value with data science

3 Value objectives and metrics

4 Data assets

5 Data storing and integration

6 Customer privacy and data security

7 Data analytics

8 Data exploration

9 Data modeling

10 Creating impact with storytelling and visualization

11 Creating value with data science

12 Building successful data analytics capabilities
N2  - This book is a refreshingly practical yet theoretically sound roadmap to leveraging data analytics and data science. The vast amount of data generated about us and our world is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organizations to leverage the information to create value in marketing.

Creating Value with Data Analytics in Marketing provides a nuanced view of big data developments and data science, arguing that big data is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. The second edition of this bestselling text has been fully updated in line with developments in the field and includes a selection of new, international cases and examples, exercises, techniques and methodologies.

Tying data and analytics to specific goals and processes for implementation makes this essential reading for advanced undergraduate and postgraduate students and specialists of data analytics, marketing research, marketing management and customer relationship management.

Online resources include chapter-by-chapter lecture slides and data sets and corresponding R code for selected chapters
ER  -