Unlock the power of generative AI to transform your enterprise B2B sales and marketing strategies
In AI-Driven Value Management: How AI Can Help Bridge the Gap Across the Enterprise to Achieve Customer Success, authors Craig LeGrande and Venky Lakshminarayanan reveal how artificial intelligence can revolutionize B2B value management. This book lays out a first-ever strategic blueprint for cost-effectively scaling value management programs. Value management is the art and science of orchestrating all the business functions in your company to envision and create exceptional value for your customers - and in the process enhance your pipeline, revenue and renewals. It's designed for business leaders who are looking to harness AI to gain a competitive edge and boost pipeline, revenue and expansions, effectively solving the problem of expensive scaling in business-to-business sales and marketing.
Dive into the core of AI-empowered Value Management (AI-VM) through a detailed exploration of a comprehensive AI-driven value management blueprint. This guide uses real-world success stories and cutting edge AI technology solutions to illustrate how businesses can combine people, processes, and technology to execute value management at scale, enhancing efficiency and effectiveness.
In this book, you'll:
- Learn from the successes and strategies of leading companies like Salesforce, ServiceNow, and Amazon Web Services
- Discover the AI-VM Blueprint, an integrated framework that lays out strategic, operational, and technological guidelines for deploying AI-driven value management
- Equip your team with actionable insights and tools to innovate and implement AI in your sales, marketing and customer success strategies effectively
AI-Driven Value Management is essential reading for B2B professionals eager to leverage AI for business growth. If you are a business leader, manager, or professional aiming to integrate AI into your value management practices, this book will provide you with the knowledge and tools you need.
Table of Contents
Foreword xiii
Introduction xv
Chapter 1 Introduction to AI-Driven Value Management 1
A Brief History of Value Management 2
The Evolution of AI 3
Modern Corporate Governance - Raising the Bar on Capital Investments 5
Rethinking Customer Relationships 6
The Road to Customer First 7
Resource Barriers 9
Scaling Out Value Management 10
Introducing the Value Management Life Cycle 10
Your Guide to Achieving 8X Company Revenue Outcomes 11
Chapter 2 The Current State of Value Management 13
Understanding the Fundamentals of Business Value 13
Product Features vs. Value Messaging 14
How Value Beats Features: An Industry Success Story 15
The Modern Corporate Buying Process 16
The Rise of PMOs 18
Building a Value-Based Narrative: The Business Case 20
Three Phases in Building a Business Case 20
A Simple Home Purchase Example: Solar Panels 26
Beyond Case Studies 27
Understanding the Customer Life Cycle 28
Go-to-Market Collaboration: The Key to Value Management Success 28
Solution Value Messaging 30
Value Models 31
The Value Opportunity Stage (Awareness + Interest) 31
The Value Target Stage (Interest + Purchase) 33
The Value Realization Stage (Adoption) 34
The Value Expansion Stage (Renewal) 36
Chapter 3 Building the Future Value Management Program 39
The Game Changer: Artificial Intelligence 39
AI: Past, Present, and Future 40
AI-VM: Competitive Advantage at Scale 41
Introducing a Blueprint for AI-Value Management 42
Chapter 4 AI-Driven Value Management for Marketing 47
Empowering B2B Marketing with AI-Enabled Value Management 48
The Current State of B2B Marketing 49
Product Marketing: Account-Based Marketing Barriers to Scale 50
Revenue Marketing: Large Nets and High Costs 53
Digital Marketing Challenges 54
Event Marketing Challenges 55
Corporate Marketing: Siloed Function, Limited ROI Visibility 56
The Current State of Value Management in Marketing 59
What’s Next: Value Management Marketing Powered by AI 61
The New Product Marketer: Enhancing Solution Positioning with Value Intelligence 62
The New Revenue Marketer: Automating and Scaling ABM with Value Intelligence 66
Improving Digital Demand-Gen “Targeting” Using Value Intelligence 69
Using Value Intelligence to Create a Demand-Gen “Hook” 71
Boosting the ROI of Corporate Events and Trade Shows 73
Leveraging AI-Driven Value Intelligence Content 74
Individualized Participant Experiences 75
Interactive Booth Experiences 76
The New Corporate Marketer: Creating a Value Intelligence ABM Approach to Sponsorships 76
Smarter marketing investments 78
Chapter 5 AI-Driven Value Management for Sales 81
Getting Started with Value Management for Sales in Start-ups and Small Companies 83
Building VM Capabilities with People: Small, High-Powered Team Focused on Top Deals 84
Building VM Capabilities with Process: Manual Value Management Programs 84
Building VM Capabilities with Technology: Value Automation Platforms Can Increase Business Case Productivity 86
Building Deal Coverage and Customer Outcomes 87
From Art to Craft to Practice: How Value Management Programs Support Mature Sales Organizations 88
Building VM Capabilities with People: Creating an Independent Function for Value Management 88
Building VM Capabilities with Technology: Enabling VM at Scale 92
Building VM Capabilities with Process: Organization, Governance, and Operating Models Struggle Under Their Own Weight 92
Value Model Development 93
Engagement Planning 94
Administration and Reporting 94
Training and Content Development 94
Organization 95
Operating Model and Demand Management 95
Improving Deal Coverage and Customer Outcomes 96
What’s Next: AI-Driven Value Management for Sales 97
Introducing the AI-Powered Value Consultant 98
AI Technology: Powering Up Value Management Platforms 99
AI-Enhanced Processes: Exponentially Scaling Value Management Programs 100
Business Case Creation 100
Training and Content Development: Autogenerating Content for Value Management Programs 103
A Quantum Leap in Coverage and Customer Outcomes Using AI 103
Chapter 6 AI for Sales Operations 105
Understanding the Responsibilities of the Sales Operations Team 106
Adding AI to Sales Operations to Quickly Scale Value Management Programs 109
Making the Business Case for Value Engineering Programs: The ROI of ROI Programs 112
Key Outcomes of Value Programs 113
Optimizing the ROI from ROI Programs 113
Chapter 7 Empowering Your Sales Partners with AI-Driven Value Management 115
The Risk of a Poor Partner Experience 116
De-risking Partner Relationships 117
Partner Ecosystems Tiers 118
AI-Enabled Partner-Based Value Management (AI-PBVM) 120
Top Tier - AI-PBVM Unifies Go-to-Market Activities 122
Middle Tier - AI-PBVM Automates Value Management Go-to-Market Messaging and Assets 124
Lower Tier - AI-PBVM Provides Virtual CMO and Value Engineering Resources 126
Value Management for Three Types of Ecosystem Partners 127
System Integrators: An Indispensable Partner 128
Automating Strategy-to-Planning Efforts with AI 130
Accelerating Proofs-of-Concept for Faster Customer Buy-in 132
Providing Accurate Implementation Recommendations 133
Value-Added Resellers - A Critical Link in the Value Chain 137
AI-Powered Co-marketing Assistant 138
Digital Sales Consultant for VARs 138
Technology Alliance Partners 139
AI-Enabled Alliance Assistants 140
AI Sales Consultant 140
AI Value Assistants for Renewals 141
Conclusion 142
Chapter 8 AI-Driven Value Management for Customer Success 145
What Is Customer Success and Why You Should Care? 146
Understanding the Customer Success Workflow 149
Better Together: Combining Customer Success and Value Management 152
The Challenge of Integrating Value Management and Customer Success 153
Pressures Mount for Customer Success Teams 154
The CSM’s Toughest Challenge: Measuring and Communicating Value 155
Touchpoints: Where Value Management Meets Customer Success 157
AI: Changing the Customer Success Game 158
Automating Customer Success 158
Harnessing Data 160
Driving Sales and Loyalty 160
Capturing Greater Value 160
Raising the Performance Bar with AI 161
The Future of AI-Powered Customer Success 164
Chapter 9 One Value Motion: The Power of Unified Value Management 167
The Journey to a Unified Enterprise 168
Sloppy Handoffs and Broken Workflows 171
Differences in Taxonomy 172
Prioritization Conflicts 172
Success Measures 173
Governance Gaps 173
Functional vs. Enterprisewide AI Approaches 174
Solving the Puzzle of an Enterprisewide Value Management Program 175
Creating One Value Motion: A Unified Value Management Framework 175
The One Value Motion Playbook 176
Step 1: Define Your One Value Motion Mission 177
Step 2: Set the One Value Motion Strategy and Leadership Alignment 177
Step 3: Define Success Measures and Business Outcomes 178
Step 4: Establish a Companywide Value Lexicon 178
Step 5: Create a One Value Motion Team 180
Step 6: Secure the Budget 181
Step 7: Implement Operational Governance 182
Step 8: Define One Value Motion Workflows 183
Awareness Phase 183
Interest Phase 184
Purchase Phase 184
Adoption and Renewal Phase 185
Step 9: Design, Develop, and Deploy the AI Value Assistant 185
The AI Value Assistant: Customer Insights at Your Fingertips 186
The Autonomous Worker: Powered by Agentic AI 187
The AI Value Coach: Navigating Conversations in Real Time 188
Building Your AI Value Assistant 189
Targeted Workflow AI Assistant Approach 191
Phase 1: Discovery and Planning 192
Engage Stakeholders 192
Identify and Prioritize Use Cases 193
Gather Requirements 196
Conduct Feasibility Analysis 196
Design a Technical Solution Architecture 197
Phase 2: Design and Development 197
Data Strategy and Integration 197
AI Model Design and Training 198
User Interface and Experience (UI/UX) Design 198
Development of the AI Toolset 198
Phase 3: Testing and Validation 199
Unit and Integration Testing 199
User Acceptance Testing 199
Performance and Security Testing 200
Phase 4: Deployment and Adoption 200
Deployment Planning 200
Pilot Deployment 200
Full-Scale Deployment 201
Phase 5: Post-Deployment Support and Continuous Improvement 201
Continuous Improvement 201
Reporting and Value Realization 201
Reaping the Rewards of One Value Motion 202
Chapter 10 Delivering Business Outcomes with AI-Powered Value Management 203
Boosting Revenue Throughout the Customer Life Cycle 204
How AI-VM Can Drive Revenue: A 10-Year Forecast 206
Capturing More Value from Your Partner Ecosystem 208
Driving Cost and Time Savings 209
Chapter 11 A Final Note to the Reader 213
Glossary 215
Acknowledgments 221
About the Authors 223
Index 225
