Own the Foundation of Customer Health & Risk Monitoring
Define the data signals that predict customer health, engagement, and adoption velocity. Build dashboards that surface at-risk accounts before they churn and identify adoption success patterns so your team can replicate them.
Build Adoption & Engagement Metrics
Track customer behavior over time: time-to-first-use, velocity of engagement, feature adoption, usage patterns by segment. Create cohort analysis to see which customers are accelerating, stalling, or at risk. Translate those insights into metrics that drive action.
Drive Data Consistency Across the Organization
Work with the revenue operations analyst, AI engineer, and customer teams to ensure metrics are defined consistently and reported the same way across human and automated systems. Document calculation logic so the system stays transparent and scalable.
Support Customer Experience Operations
Own the metrics that matter: customer onboarding speed, time to value, implementation health, feature adoption rates. Partner with customer-facing teams to instrument workflows and identify where friction is slowing customers down.
Translate Data Into Insights
Answer hard questions: What correlates with customer success? Which segments are we losing to adoption friction? Where should we focus resources? Pull the data, analyze it, and explain what it means to non-technical stakeholders.