Big Data Analytics

Applications in Business and Marketing

• Author(s): Kiran Chaudhary, Mansaf Alam,
• Publisher: CRC Press
• Pages: 275
• ISBN_10: 1000523578
  ISBN_13: 9781000523577
  
• Language: en
• Categories: Business & Economics / Marketing / General , Computers / Data Science / Data Visualization , Computers / Data Science / Data Analytics , Computers / Information Technology , Computers / Computer Science , Business & Economics / Economics / General , Computers / Database Administration & Management , Business & Economics / General ,

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.