Want to know if this job is worth applying to?
Hyderabad, Telangana, India
Hybrid
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
• 5–7 years of experience in Support Operations, Business Analytics, or similar roles in a B2B environment
• Strong experience with BI tools within the Microsoft Fabric ecosystem (Power BI, etc.)
• Experience working with Salesforce Service Cloud data models
• Demonstrated ability to work with ambiguous or incomplete datasets
• Experience partnering with Product, Engineering, or Customer Success teams
• Familiarity with Gainsight or similar CS platforms preferred
• Exposure to AI-enabled support tools (e.g., Forethought, Agentforce) is a strong plus
• Strong analytical and storytelling skills—ability to turn data into decisions
What Success Looks Like
• Clear, trusted visibility into support trends and performance
• Support data is actively used to inform product and customer decisions
• Improved alignment between Support, Product, and Customer Success
• Meaningful metrics that reflect real customer experience, not just operational proxies
• High confidence in data quality and reporting consistency
• Clear Metrics for measuring AI effectiveness, and drive for improving those outcomes.