Customer relationship management: an AI-driven approach

Table of content:
Preface

Acknowledgments

About the Author

List of Case Studies

1. Defining CRM

1.1 Cost of Acquiring Customers

1.2 Driving Customer Loyalty

1.2.1 Why Is Customer Loyalty Critical?

1.2.2 Not All Customers Are the Same

1.2.3 Driving Customer Loyalty

1.2.4 Customer Lifecycle Management

1.3 Traditional Technologies and Customer Information Processing

1.3.1 How Information Processing Gets Different with AI

1.4 Components of CRM Systems

1.4.1 Marketing

1.4.2 Sales Force Automation

1.4.3 Customer Service and Support

1.5 Types of CRM

1.5.1 Operational CRM

1.5.2 Analytical CRM

1.5.3 Collaborative CRM

1.5.4 Social CRM

1.6 CRM Architecture

1.6.1 PACE-layered Architecture of CRM

1.7 Evolution of CRM

1.7.1 CRM 1.0 to CRM 2.0

1.7.2 Integration of AI in CRM Architecture

1.8 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions



2. CRM in Marketing

2.1 Paradigm Shifts in Marketing—Product to Customer

2.1.1 Target Marketing

2.1.2 Relationship Marketing and One-to-One

2.2 Campaign Management

2.2.1 Designing Marketing Campaigns with AI

2.3 CRM Marketing Initiatives

2.3.1 Cross-Selling and Upselling

2.3.2 Customer Segmentation

2.3.3 Behavior Prediction

2.3.4 Customer Profitability and Value Modeling

2.3.5 Channel Optimization

2.3.6 Personalization

2.3.7 Event-Based Marketing

2.4 Secrets of Your Customer Relationships

2.5 Case Study: Fashion Industry

2.6 A Marketing Automation Checklist for Success

2.7 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions

3. Permission Marketing

3.1 Opt-In Policies

3.1.1 Permission Marketing Essential for Marketing

3.1.2 Customer Data Privacy

3.2 Permission Marketing Requirements for E-Commerce

3.2.1 Data Gathering

3.2.2 Data Management

3.2.3 Data Analysis

3.2.4 Data Breach

3.3 Permission Marketing Success Checklist

3.4 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions

4. Sales Force Automation

4.1 Sales Force Automation: The Cradle of CRM

4.2 Sales Force Automation Features

4.2.1 Managing the Sales Cycle, Sales Process, and Activity Management

4.2.2 Sales and Territory Management

4.2.3 Account Management and Contact Management

4.2.4 Lead Management

4.2.5 Configuration Support

4.2.6 Knowledge Management

4.3 SFA and AI-Driven CRM

4.3.1 Predictive Lead Scoring and Nurturing

4.3.2 Real-Time Sales Insights

4.3.3 Monitoring Pipeline Metrics Through a Dashboard

4.3.4 Seamless Integration with Marketing Automation

4.4 Field Force Automation

4.5 SFA Success Checklist

4.6 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions

5. CRM and Customer Service

5.1 The Nuances of Customer Support

5.2 The Evolution of Contact Centers

5.2.1 Call Routing

5.2.2 Web-Based Self-Service

5.2.3 Contact Center Sales Support

5.2.4 Telemarketing and the Outbound Call Center

5.2.5 AI-Based Predictive Dialer and Pacing Ratio

5.2.6 Call Scripting

5.2.7 KPIs to Measure Call Center Effectiveness

5.3 Conversational AI: Chatbots

5.4 Customer Service Success Checklist

5.5 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions



6. Data Management

6.1 Operational CRM and Database Management

6.1.1 The Case for Integrated Data

6.1.2 From Database to Data Warehouse

6.2 Changing Nature of Data

6.3 Big Data for CRM

6.3.1 Non-relational Databases

6.3.2 RDBMS vs. NoSQL

6.4 Data Cleaning and Preprocessing

6.5 Data Governance and Quality

6.6 Data Management Success Checklist

6.7 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions

7. Analytical CRM

7.1 Managing Relationships with Operational and Analytical CRM

7.2 Major Types of Data Analytics

7.2.1 Online Analytical Processing

7.2.2 Data Mining

7.2.3 AI Models

7.3 Applications of AI-Based Analytics for E-Commerce

7.3.1 Clickstream Analysis

7.3.2 Predictive Analytics

7.3.3 Market-Basket Analysis

7.3.4 Sentiment Analysis

7.3.5 Personalization

7.3.6 Dynamic Pricing

7.3.7 A/B Testing

7.4 Analytical CRM Success Checklist

7.5 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions

8. Planning and Implementing the CRM Program

8.1 Preparing the CRM Business Plan

8.1.1 Understanding CRM Requirements

8.2 Understanding Business Process

8.2.1 Redesigning Business Processes to Meet CRM Goals

8.3 Back-end Systems Integration

8.4 Partner Relationship Management

8.5 Requirements-Driven Product Selection

8.5.1 Defining the Role of AI in the Processes

8.5.2 Defining Technical Requirements

8.5.3 Selecting Vendors

8.6 CRM Implementation Roadmap

8.7 Planning and Implementation of CRM Success Checklist

8.8 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions

9. Social CRM Strategy

9.1 Social Media Audit

9.2 Knowing the Audience

9.3 Selecting Relevant Social Media Platform

9.4 Content Strategy

9.4.1 Social Media Promotion Models

9.4.2 Tailoring of Social Media with Customer Journey

9.5 Social Media Analytics

9.5.1 Descriptive Analysis: Decoding the Landscape

9.5.2 Content Analysis: Beyond the Numbers

9.5.3 Network Analysis: Mapping the Connections

9.6 KPIs to Monitor Social Strategy Performance

9.6.1 Audience Insights

9.6.2 Content Performance

9.6.3 Paid Social Media Performance

9.7 Social CRM Implementation

9.8 Social CRM Success Checklist

9.9 Key Implications for Managers

Key Terms

Review Questions

Discussion Questions
[https://www.wileyindia.com/customer-relationship-management-an-ai-driven-approach.html]

In today's fast-evolving business environment, customer relationships are more

important than ever, and Customer Relationship Management—An AI-driven Approach

provides the essential roadmap for navigating this dynamic landscape. This

comprehensive guide bridges traditional CRM methods with AI technologies, showing

how AI technologies like machine learning, predictive analytics, and automation can

transform customer engagement and streamline operations. Through detailed

discussions on CRM fundamentals, the role of AI in driving marketing, sales, and

customer service, and the importance of effective data management, this book offers

practical insights backed by real-world examples and case studies. Special emphasis is

given to the Indian market, exploring how businesses are leveraging AI to meet local

challenges. This is an invaluable resource for professionals and academics looking to

understand and apply AI-driven CRM strategies to stay ahead in today's competitive

market.
(https://www.wileyindia.com/customer-relationship-management-an-ai-driven-approach.html)