Big Data Analytics : Applications in Business and Marketing book cover
1st Edition

Big Data Analytics
Applications in Business and Marketing

ISBN 9781032187662
Published December 28, 2021 by Auerbach Publications
275 Pages 31 B/W Illustrations

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Book Description

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance.

The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including:

  • Big data analytics and algorithm
  • Market basket analysis
  • Anticipating consumer purchase behavior
  • Variation in shopping patterns
  • Big data analytics for market intelligence

The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing.

This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.

Table of Contents

1. Embrace the Data Analytics Chase: A Journey from Basics to Business
Suzanee Malhotra

2. Big Data Analytics and Algorithms
Alok Kumar, Lakshita Bhargava, And Zameer Fatima

3. Market Basket Analysis: An Effective Data-Mining Technique for Anticipating Consumer Purchase Behavior
Samala Nagaraj

4. Customer View—Variation in Shopping Patterns
Ambika N

5. Big Data Analytics for Market Intelligence
Md. Rashid Farooqi, Anushka Tiwari, Sana Siddiqui, Neeraj Kumar, and Naiyar Iqbal

6. Advancements and Challenges in Business Applications of SAR Images
Prachi Kaushik and Suraiya Jabin

7. Exploring Quantum Computing to Revolutionize Big Data Analytics for Various Industrial Sectors
Preeti Agarwal and Mansaf Alam

8. Evaluation of Green Degree of Reverse Logistic of Waste Electrical Appliances
Li Qin Hu, Amit Yadav, Hong Liu, and Rumesh Ranjan

9. Nonparametric Approach of Comparing Company Performance: A Grey Relational Analysis
Tihana Škrinjarić

10. Applications of Big Data Analytics in Supply-Chain Management
Nabeela Hasan and Mansaf Alam

11. Evaluation Study of Churn Prediction Models for Business Intelligence
Shoaib Amin Banday and Samiya Khan

12. Big Data Analytics for Marketing Intelligence
Tripti Paul And Sandip Rakshit

13. Demystifying the Cult of Data Analytics for Consumer Behavior: From Insights to Applications
Suzanee Malhotra

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Dr. Kiran Chaudhary is an Assistant Professor in the Department of Commerce, Shivaji College, University of Delhi and has 12 years of teaching and research experience. She earned a Ph.D. in Marketing from Kurukshetra University, India. Her areas of research include marketing, human resource management, organizational behavior, and business and corporate law. A distinguished student winning various awards of recognition, she is a book author as well as conference and journal paper author.

Dr. Mansaf Alam is an Associate Professor in the Department of Computer Science, Faculty of Natural Sciences, Jamia Millia Islamia University, New Delhi, India. He has also been Young Faculty Research Fellow for the Ministry of Electronics and Information Technology in India and the Editor-in-Chief for Journal of Applied Information Science. A journal and conference paper author, he conducts research in such area as big data analytics, machine learning & deep learning, cloud computing, cloud database management systems, object- oriented database systems, information retrieval, and data mining. His other academic activities include journal reviewer, member of conference program committees, journal editorial board member, and book author.