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Product Summary

This project demonstrates how I apply AI product management concepts learned from:

• AI Product Management: Strategy, Roadmaps & ChatGPT (Udemy)
• AI for Product Management (Pendo AI)

I designed an end-to-end AI customer support solution covering: problem discovery, user research, feature definition, roadmap planning, AI system design, risk analysis, and success metrics — simulating how an AI Product Manager would build and ship a real product.

Problem Statement

Modern digital businesses receive high volumes of repetitive customer queries (order status, refunds, basic troubleshooting), overwhelming human support teams and increasing response times. Customers expect instant, 24/7 assistance, but scaling human-only support is expensive and slow.

Target Users

• Customer support leaders and operations managers in B2C and SaaS companies
• Frontline support agents handling high ticket volumes
• Product and CX teams looking to improve self-service and reduce support friction

Key Pain Points

• Long first-response and resolution times for simple, repetitive questions
• High support costs due to growing ticket volumes
• Inconsistent responses across agents and time zones
• Limited visibility into what customers are actually asking, at scale
• Agents spending too much time on low-value tickets instead of complex issues

Business Goals

• Reduce support ticket volume handled by human agents (deflection through self-service)