Big Data Analytics
Applications in Business and Marketing
1st Edition
Published on 27. December 2021
275 pages
978-1-000-52355-3 (ISBN)
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.
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.
More details
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Illustrations
31 Line drawings, black and white; 31 Illustrations, black and white
ISBN-13
978-1-000-52355-3 (9781000523553)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
12/2021
1st Edition
Auerbach
€126.60
Shipment within 10-20 days
Book
12/2021
1st Edition
Auerbach
€52.70
Shipment within 10-20 days
Persons
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.
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.
Content
1. Embrace the Data Analytics Chase: A Journey from Basics to Business. 2. Big Data Analytics and Algorithm. 3. Market Basket Analysis: An Effective Data Mining Technique for Anticipating Consumer Purchase Behavior. 4. Customer View--Variation in Shopping Patterns. 5. Big Data Analytics for Market Intelligence. 6. Advancements and Challenges in Business Applications of SAR Images. 7. Exploring Quantum Computing to Revolutionize Big Data Analytics for Various Industrial Sectors. 8. Evaluation of Green Degree of Reverse Logistic of Waste Electrical Appliances. 9. Nonparametric Approach of Comparing Company Performance: A Grey Relational Analysis. 10. Applications of Big Data Analytics in Supply-Chain Management. 11. Evaluation Study of Churn Prediction Models for Business Intelligence. 12. Big Data Analytics for Market Intelligence. 13. Demistifying the Cult of Data Analytics for Consumer Behavior: From Insights to Applications.
