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

Big Data Analytics
Applications in Business and Marketing

  • Available for pre-order. Item will ship after January 19, 2022
ISBN 9781032187662
January 19, 2022 Forthcoming by Auerbach Publications
256 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. Part IV 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

I. Introduction

1. Introduction
Suzanee Malhotra

II. Applications of Business Analytics

2. Big Data Analytics and Algorithm
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, and Neeraj Kumar

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

III. Business Intelligence

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

IV. Analytics for Marketing Decision Making

12. Big Data Analytics for Market Intelligence
Tripti Paul and Sandip Rakshit

13. Data Analytics and Consumer Behaviour
Suzanee Malhotra

14. Marketing Mode and Survival of the Entrepreneurial Activities of Nascent Entrepreneurs
Muhammad Nawaz Tunio

15. The Responsibility of Big Data Analytics in Organization Decision-Making
Ezeifekwuaba Tochukwu Benedict

16. Decision Making Model for Medical Diagnosis Based on Some New Interval Neutrosophic Hamacher Power Choquet Integral Operators
Pankaj Kakati and Saifur Rahman

V. Digital Marketing

17. Prediction of Marketing by the Consumer Analytics
C.C. Jayasundara

18. Web Analytics for Digital Marketing
Srinivas Dinakar Nethi, Venkata Rajasekhar Moturu, and Krishnaveer Abhishek Challa

19. Smart Retailing: A Novel Approach for Retailing Business
Ghanshyam Parmar

20. Leveraging Web Analytics for Optimizing Digital Marketing Strategies
Sapna Sood

21. Smart Retailing in Digital Business
S R Mani Sekhar, Tarun Krishnan Louie Antony, Sandeep B L, and Siddesh G M

22. Business Analytics and Performance Management in India
Pavnesh Kumar, Siddhartha Ghosh, and Kiran Chaudhary

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Dr. Kiran Chaudhary is an Assistant Professor in the Department of Commerce, Shivaji College, University of Delhi. She has Twelve years of Teaching Research experience. She earned Ph.D. in Marketing (Commerce) from Kurukshetra University, Kurukshetra, Haryana. Her areas of research include Marketing, Human resource Management, Organizational Behavior, Business and Corporate law. She has published a book on Probability and Statistics. She has published several research articles in reputed International Journals and Proceedings of reputed International conferences published Dr. Mansaf Alam is an Associate Professor in the Department of Computer Science, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi. He has also been a Young Faculty Research Fellow, DeitY, for the government of India and Editor-in-Chief for the Journal of Applied Information Science. He has published several research articles in reputed International Journals and Proceedings of reputed International conferences published by IEEE, Springer, Elsevier Science, and ACM. His area of research include Big Data Analytics, Machine Learning & Deep Learning, Cloud Computing, Cloud database management system(CDBMS), Object Oriented Database System(OODBMS), Information Retrieval and Data Mining.