Customer Value Management in 2025
Steven Forth is CEO of Ibbaka. Connect on LinkedIn
Customer Value Management: Business Process and B2B Software Category
Customer Value Management (CVM) is both a critical business process and a B2B software category. It is aimed at creating, delivering, and capturing value around the customer lifecycle. In 2025 Customer Value Management will undergo a transformation as it emerges as a critical business process in competitive markets that are being transformed by technology. The B2B software space is an example of this. Massive investments have been made in applying generative AI in this space and the focus is shifting to how AI agents, co-pilots and generators will create value.
Customer Value Management As a Business Process
CVM focuses on aligning an organization's capabilities with customer needs and desired outcomes.
.It involves:
Discovering and communicating value propositions
Modeling and estimating value to customer (V2C)
Delivering value in a sustained way over time
Measuring and documenting that value
Optimizing value creation and capture
Customer Value Management As a B2B Software Category
CVM as a business process is supported and shaped by CVM software platforms. These platforms enable organizations to:
Quantify value using value models like Economic Value Estimation
Communicate that value to customers and support value stories and value communication
Track value realization across the customer journey
Connect value to price
Integrate with CRM and other enterprise tools
The Emergence of Customer Value Management
Several factors have driven the emergence of CVM:
Shift from product-centric to customer-centric approaches
The need for differentiation in competitive markets
The growing importance of long-term customer relationships
Recognition that value to customer drives profitability and growth
Increasing customer expectations for personalized experiences and measurable outcomes
The need to communicate the value of new technologies and products (like generative AI)
Key Characteristics of Customer Value Management
For Ibbaka, customer value management is based on the following principles.
Lifecycle Approach: Manages value across the entire customer journey
Value Quantification: Value management begins with having a model to quantify and understand value, without this there is no customer value management
Value Communication: Value is in the eyes of the customer, if it is not communicated it will not be understood
Value Documentation: Helps quantify and communicate value delivered over time
Cross-Functional Collaboration: Aligns sales, marketing, customer success, and product teams
Evolution of CVM in 2025 and Beyond
2025 is the year of the snake in East Asian cultures. The year of the Wood Snake, 2025, is seen as a time of transformation, wisdom, and renewal. This is what is happening in CVM. There will be …
Increased focus on outcome-based success metrics
Greater integration of AI and automation for predictive analytics
Expansion of digital-first engagement strategies
Tighter feedback loop between customer success and product development
Shift from activity metrics to outcome metrics (e.g., Value to Customer or V2C)
Impact of Generative AI on CVM
Need for CVM
Generative AI increases customer expectations for personalized experiences, making CVM more critical
Best Practices
Leveraging generative AI for hyper-personalization of customer interactions
Using AI-powered analytics for deeper customer insights and predictive modeling
CVM Software Functionality
Automated content generation for personalized marketing and support
AI-driven chatbots and virtual assistants for enhanced customer engagement
Predictive analytics for anticipating customer needs and churn risks
Recommendations for B2B SaaS Executives in 2025
Invest in robust CVM software platforms that integrate AI capabilities
Develop a value realization framework tied to tangible business outcomes
Implement cross-functional collaboration processes centered on customer value
Shift success metrics from product usage to business impact (ROI, cost savings, revenue generation)
Invest in training programs to cultivate a customer value-centric culture
Leverage data analytics for personalized, proactive customer engagement strategies
Establish a dedicated Customer Value Manager role to oversee CVM initiatives
Conclusion
CVM is evolving from a support function to a strategic profit center. It is critical to both the adoption of new products and to their sustained success and Net Revenue Retention (NRR). The integration of AI and data analytics is crucial for future CVM success. Cross-functional collaboration and outcome-based metrics will be at the center of the story. Personalization at scale will be a key differentiator in 2025 and beyond. Value models will become dynamic to reflect changes in the market and adaptations by customers and users. This more dynamic environment will make the use of AI based adaptive models central to the customer value management story.
