Source: SBI Growth Advisory (2026), The Great Unbundling: Why Your NRR Is Declining Even as Customers Extract More Value
The decline in Net Revenue Retention (NRR) from 110.5% in 2023 to 107.1% in 2025 signals a permanent fracture in the SaaS business model known as "The Great Unbundling." 58% of companies report lower net revenue retention (NRR) because artificial intelligence (AI) productivity enables customers to achieve the same output with fewer people. This dynamic creates a trap where increased customer success reduces vendor revenue under traditional seat-based pricing. Future growth requires a strategic shift from monetizing human capacity to capturing value through agentic workflows and application programming interface (API) consumption.
Companies relying on seat-based pricing are 1.6 times more likely to miss growth targets
80% of SaaS companies rely on seat-based pricing models. These organizations are 1.6 times more likely to miss growth targets than competitors using consumption models. This underperformance stems from the "Productivity Trap" where AI tools increase output while reducing the need for human operators. Customers achieve higher productivity with smaller teams. This dynamic directly erodes revenue for vendors dependent on headcount growth.
Solution usage explains 80% of renewal decisions. This predictive power far exceeds firmographics or historical revenue data. Pricing models based solely on login frequency or seat utilization systematically misclassify churn risk in an era where fewer humans generate more value.
The era of distinct user interfaces driving premium pricing has ended. Buyers prioritize API completeness and data portability over interface design because autonomous agents handle workflows via code rather than human interaction. "UI Obsolescence" occurs when the ease of use that once justified high fees no longer matters to a machine.
Future success depends on "Agentic" readiness. Buyers demand low response latency for agents and require that every user interface (UI) function has an API equivalent. The new competitive moat is the technical infrastructure that supports these autonomous interactions.
Traditional health scores fail because login frequency provides a false signal of retention. Behavioral cohorts offer a superior alternative by mapping accounts based on usage level and consistency. This approach predicts commercial outcomes with 90% accuracy up to 12 months in advance.
The model identifies six distinct groups ranging from "Power Users" driving expansion to "Disconnected" accounts that signal immediate risk. "Enthusiastic Adopters" represent high but unstable usage, while "Converts" form the core of reliable renewals. Understanding these patterns allows for precise intervention strategies. The new competitive moat is understanding exactly which customers will succeed and pricing accordingly.
The separation of value from human capacity represents a permanent structural shift. SaaS leaders must transition from seat-based dependency to hybrid models that capture the value of automation. A leading developer tool provider recently faced a 30% seat contraction due to AI coding assistants, but successfully reversed the trend. Implementing a hybrid model to capture storage overages turned a potential revenue loss into a net Annual Recurring Revenue (ARR) uplift.
Organizations that fail to adapt will see their NRR continue to slide. The winners in the agentic era will be those who monetize the machine's output rather than the human's time.