Big data analytics : applications in business and marketing
著者
書誌事項
Big data analytics : applications in business and marketing
（An Auerbach book）
CRC Press, Taylor & Francis Group, 2022
- : hbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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.
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