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| | About this title |
Three factors are fueling the growth of customer experience data: automation in the customer touch points, maturing markets for customer data, and consumer sophistication in sharing customer experience. Today's customers have the ability to use a variety of media to broadcast their good and bad experiences in real time. Successful organizations are responding with an investment in real-time Customer Experience Analytics (CEA) to improve their customer relationships, products, and processes.
This book discusses a series of case studies from a variety of industries to show how CEA is reshaping the way we interact with our customers. It explores a set of technologies available to help us create the capabilities to sense, isolate, and alter the customer experience to competitive advantage—creating a real-time, adaptive relationship with our customers.
With Customer Experience Analytics, you will:
- Gain a keener understanding of what constitutes good customer experience.
- Learn how CEA is enabling organizations to build significant competitiveness and bring disruptive change to the marketplace.
- Understand CEA enablers and the technologies for implementing CEA.
- Read case studies and best practices that take advantage of the business capabilities enabled by CEA.
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| About author |
 Arvind Sathi —
Dr. Arvind Sathi is the Global Communication Sector Lead Architect for the Information Agenda team at IBM. Dr. Sathi received his Ph.D. in Business Administration from Carnegie Mellon University and worked under Nobel Prize winner Dr. Herbert A. Simon. Dr. Sathi is a seasoned professional with more than 20 years of leadership in Information Management architecture and delivery. His primary focus has been in the delivery and architecture oversight of IT projects to communications organizations. He has extensive experience with many domestic as well as international communications service providers, as well as with other services industries.
Prior to joining IBM, Dr. Sathi was the pioneer in developing knowledge-based solutions for CRM at Carnegie Group. At BearingPoint, he led the development of Enterprise Integration, MDM, and Operations Support Systems/Business Support Systems (OSS/BSS) solutions for the communications market and also developed horizontal solutions for communications, financial services, and public services. At IBM, Dr. Sathi has led several Information Management programs in MDM, data security, business intelligence, and related areas and has provided strategic architecture oversight to IBM's strategic accounts. He has also delivered a number of workshops and presentations at industry conferences on technical subjects including MDM and data architecture, and he holds patents in data masking.
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| Contents |
CONTENTS
Introduction
What Is Good Customer Experience?
Analytics to Drive Customer Experience
Sources of Study Material
Book Organization and Intended Audience
PART ONE: The CEA Opportunity
Chapter 1: The Industry View
Customer Experience Analytics Through Examples
Communication Service Providers
Financial Institutions
Public Services
Health Care
Automobiles and Car Insurance
Retail
Information Services
Conclusion
Chapter 2: Instrumentation and Automation Fuels Customer Experience
Data Collection
Sales and Marketing
Operations
Product Engineering
Finance
Across the Customer Life Cycle
Conclusions
Chapter 3: Rise in Customer Sophistication
Evolution of Consumer Decision-Making Process
Use of Social Networks
Role of Leaders in Product Selection and Churn
Chapter 4: Rise of the CEA Marketplace
The Data Bazaar
The Loyalty Marketplace
Auction Marketplace
Social Networking Market
Privacy Concerns: Location
Summary
PART TWO: The Customer Experience Analytics Solution
Chapter 5: Solution Overview
Evolution
Customer Experience Analytics Target Architecture
Enablers
Chapter 6: Data Movement and Master Data Management
Data Movement and MDM Functional Overview and Examples
Key Technical Contributions
Summary
Chapter 7: Stream Computing
Stream Computing Functional Overview and Examples
Key Technical Contributions
Chapter 8: Predictive Modeling
Predictive Modeling Functional Overview and Examples
Predictive Modeling: Selective Deep Dive
Chapter 9: Analytics Engines and Appliances
Analytics Engine: Functional Overview and Examples
Analytics Engine: Selective Deep Dive
Summary
Chapter 10: Privacy Management
Privacy Management: Functional Overview and Examples
Privacy Management: Selective Deep Dive
PART THREE: How to Package a Customer Experience Analytics Program
Chapter 11: Business Case for Customer Experience Analytics
Drivers
Capabilities
Measurements
Business Maturity Levels
Summary
Chapter 12: Conclusions
Market Forces
The CEA Solution
The Power of CEA
List of Abbreviations
Notes |
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