Customer Experience Operations Analyst II ( Power BI / Microsoft Fabric)

Job Responsibilities

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

Job Qualification

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.