Augmenting Customer Retention Through Big Data Analytics
eBook - ePub

Augmenting Customer Retention Through Big Data Analytics

  1. 350 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Augmenting Customer Retention Through Big Data Analytics

About this book

Most businesses today are embracing digital transformation and automation, deploying the processes of data analytics in combination with advanced technologies for customer retention using such techniques as marketing automation, digital marketing, machine learning (ML), blockchain, generative AI, and robotics. This new book discusses a wide range of topics related to big data customer analytics and its application for customer retention.

It covers important topics on the use of big data in business, including personalization and customization of products and services, segmentation, digital marketing, customer relationship management, loyalty programs, and customer loyalty and retention and more. The book provides examples and case studies that demonstrate how big data is changing the customer loyalty scenario in a highly digitalized world. The book also addresses using big data analytics in areas such as metaverse, government bodies, and fashion retail.

Key features:

  • Provides valuable insights on formulating customer retention strategies using big data analytics
  • Discusses the application of big data for reducing churn rate
  • Demonstrates strategies for using big data analytics to improve efficiency and customer service

With its diverse and comprehensive coverage, this book offers academics, marketers, human resource managers, students, as well as industrial practitioners a guide to using the exciting technology of big data for customer retention.

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Yes, you can access Augmenting Customer Retention Through Big Data Analytics by Reena Malik,Ambuj Sharma,Prashant Chaudhary in PDF and/or ePUB format, as well as other popular books in Business & Data Mining. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Apple Academic Press
Year
2024
eBook ISBN
9781040166390
Edition
0
Topic
Business
Subtopic
Data Mining
Index
Business

Table of contents

  1. Cover Page
  2. Half Title Page
  3. Title Page
  4. Copyright Page
  5. About the Editors
  6. Contents
  7. Contributors
  8. Acknowledgments
  9. Preface
  10. Chapter 1 Personalization and Customization of Products and Services in E-Commerce Through Big Data
  11. Chapter 2 Unleashing Big Data and Its Role in Retaining Customers
  12. Chapter 3 The Role of Big Data in Modern Markets for Personalizing and Tailoring Products and Services
  13. Chapter 4 Segmentation and Customer Satisfaction: A Study of Insurance Sector
  14. Chapter 5 The Underlying Foundation for the E-Commerce Customer Shopping Experience Edge with Big Data Analytics
  15. Chapter 6 Marketing and Retaining Customers in the World of Brazen Bullshit: Analyzing the Post-Truth Scenario Effect on Strategic Communication
  16. Chapter 7 Big Data as a Tool for Digital Marketers
  17. Chapter 8 Big Data and Customer Retention with Real-life Examples of Companies
  18. Chapter 9 Impact of Big Data Analytics on Customer Relationship Management
  19. Chapter 10 Influence of Big Data on Customer Relationship Management in Real Estate
  20. Chapter 11 New Age Communication: Social Media Marketing and Big Data
  21. Chapter 12 Innovating Products and Services Using Big Data
  22. Chapter 13 Revamping Internal Customer Experience (ICX) with AI
  23. Chapter 14 Big Data: The Covert Artillery Backing Customer Loyalty Programs
  24. Chapter 15 Role of Big Data Analytics in Enhancing Customer Experience
  25. Chapter 16 Role of Big Data in Customer Acquisition and Retention
  26. Chapter 17 Personalization and Customization of Governance Products and Services for Citizens Using Big Data Analytics and Artificial Intelligence
  27. Chapter 18 Retention in the Metaverse: Customer Engagement Using Big Data
  28. Chapter 19 What Lies in Big Data for Customer Retention? Analyzing the Past, Present, and Future
  29. Index