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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…mehr
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.
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Inhaltsangabe
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
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
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