GMS Report Dashboard: Enterprise Amazon BI
The Bottleneck
"Amazon sellers often deal with fragmented data, making it difficult to track strategic goals (OKRs), manage daily operations, and optimize product performance (ASINs) in real-time. Manual reporting and lack of AI-driven insights lead to operational inefficiencies and missed growth opportunities."
Key Features
AI-Powered OKR Engine: Automated monthly/weekly goal breakdown via Perplexity AI
Advanced ASIN Analytics: 12-week historical tracking of Price, BSR, and LQS trends
Real-time Operational Pulse: Socket.io & SSE-driven task updates and notifications
Hierarchical RBAC: Granular access control for Admins, Brand Managers, and Researchers
Integrated Communication: Native vendor messaging powered by CometChat sync
Automated FBA & Referral Fee Engine: Real-time profitability calculations
The Architecture
I developed a full-stack BI ecosystem using the MERN stack with React 19 and Tailwind CSS 4. The platform integrates Perplexity AI for automated OKR generation and task suggestions. It features a real-time notification system via Socket.io and SSE, and a sophisticated ASIN analytics engine that tracks BSR, price trends, and LQS over 12-week windows. The system also includes a hierarchical RBAC system and CometChat integration for vendor communication.
Overcoming Challenges
Real-time Synchronization: Ensuring consistent task states across multiple users using a combination of Socket.io and SSE.
AI Resilience: Implementing robust JSON parsing and error handling for LLM-generated OKR structures.
Data Isolation: Engineering a multi-tenant data layer that strictly separates seller data between different Brand Managers.
Protocol & Process
Phase 01: Requirement analysis for high-volume Amazon seller operations and OKR workflows.
Phase 02: Designing the MERN architecture with a focus on real-time updates and AI integration.
Phase 03: Developing the ASIN tracking engine and fee calculation logic.
Phase 04: Building the AI-powered OKR generation pipeline and hierarchical RBAC system.
Phase 05: Deployment and optimization on Vercel and Render with automated sync scripts.
Engineered Impact
Streamlined corporate-level OKR tracking for high-volume Amazon brands. Reduced time spent on manual task reporting and goal setting by leveraging AI-powered breakdowns. Enhanced data visibility for Brand Managers through automated ASIN trend analysis, leading to more responsive pricing and inventory strategies.