Metrics & Reporting
- Define, refine, and operationalize a set of support metrics that reflect both operational health and customer impact (not just volume and SLA)
- Build and maintain dashboards across the Microsoft Fabric ecosystem to provide visibility into:
o Support demand and trends
o Backlog health and case lifecycle
o Escalations and recurring issue patterns
- Evaluate the effectiveness of AI-enabled support capabilities, identifying where outputs are inaccurate, misleading, or fail to support complex support scenarios.
Insights & Analysis
- Analyze support data to identify systemic product issues, friction points, and emerging risks
- Translate complex support activity into clear narratives and recommendations for Product and Engineering
- Partner with Customer Success (Gainsight) to ensure support data contributes meaningfully to:
o Health scores
o CSAT analysis
o Customer risk identification
Data Quality & Structure
- Partner with Support Ops and System Admin to improve:
o Case taxonomy
o Categorization accuracy
o Data completeness and usability
- Identify gaps in data capture and propose pragmatic improvements
Cross-Functional Enablement
- Act as a key partner to Support, Product, and CS teams in understanding support trends
- Support regular business reviews (weekly/monthly) with clear, insight-driven reporting
- Help establish feedback loops between support insights and product improvements
AI & Emerging Capabilities
- Evaluate outputs from AI-enabled tools (e.g., Forethought, Agentforce) to:
o Assess accuracy and usefulness
o Identify opportunities to improve knowledge capture and insights
- Partner with Ops and Systems to ensure AI-generated data is measurable and trustworthy
