Sr. Product Analyst

Role Summary

The Senior Product Analyst is responsible for measuring and analyzing how effectively customer service tools and AI-driven automation features support both agents and customers. This role combines analytical rigor with a product mindset. The scope includes evaluating the productivity impact of existing systems, quantifying the value of new features, and identifying opportunities to enhance speed, quality, and automation through data-driven insights.

You'll work cross-functionally with Product, BPR and technical teams (AI / LLM & dev teams) to translate raw data into clear business recommendations that improve customer experiences and reduce handling effort across human and automated interactions.

Partner with Product Managers to scope solutions, refine backlogs, and align dependencies across Contact Center and digital platforms.

Key Responsibilities

Measure the efficiency and effectiveness of customer and internal facing enterprise tools (Chat, telephony, workflow and AI / LLM systems).

Develop and maintain dashboards and performance models tracking key metrics targeted for improvement such as handle time, automation rate, accuracy, and customer satisfaction.

Evaluate the ROI and adoption of new features, quantifying value through productivity improvements, cost savings, or customer impact.

Influence the product roadmap through data driven insights

Partner with engineering and AI teams to analyze LLM bot interactions , comparing outcomes against human agent performance (speed, resolution quality, escalation rates).

Identify bottlenecks and propose data-backed recommendations to improve tool usability, automation coverage, and integration efficiency.

Translate insights into clear narratives and presentations for leadership, highlighting business impact and next-step recommendations

Key Analytics

Average Handle Time (AHT) and First Contact Resolution (FCR)

Automation Rate (% of tasks resolved without human intervention)

Tool Adoption Rate and Feature Utilization

Customer Satisfaction (CSAT / NPS)

Cost per Resolution and Time to Resolution

LLM Accuracy / Confidence vs. Human Benchmark

Create new metrics as required

Required Skills & Qualifications

Analytical Expertise : Excellent SQL skills (Snowflake preferred) and experience in data visualization tools (Tableau preferred)

Experimentation & Measurement : Knowledge of A / B testing, causal inference, and performance benchmarking.

Product & Process Understanding : Familiarity with contact-center workflows, CRM / ticketing tools (Salesforce, Genesys, etc.), and LLM-driven automation systems.

Statistical & ML Awareness : Understanding of accuracy metrics, confusion matrices, and model performance trade-offs when comparing human vs. AI output.

Business Acumen : Ability to translate complex data into clear business stories that drive action.

Collaboration & Communication : Strong cross-functional skills; able to partner with engineers, data scientists, and operations teams effectively.

Preferred Tools : SQL, Python (for data analysis), Tableau (visualization)

Preferred Background

6-10 years of experience in analytics, product operations, or data-driven process improvement.

Experience working in e-commerce , customer service, automation, or LLM-based platforms .

Exposure to contact center analytics, AI evaluation, or operational excellence functions.