Ajio Return Tracking Dashboard
The Bottleneck
"Modern e-commerce sellers on platforms like Ajio face a significant bottleneck: the return lifecycle. With thousands of products being returned monthly, manual tracking through multiple courier portals is not only inefficient but also prone to massive revenue leakage. Sellers often lose up to 15% of their inventory value due to 'stuck' returns that are never delivered back and for which claims are never filed. The lack of a centralized, automated system for verifying return delivery and automating the claim process was a multi-million dollar problem for mid-market sellers."
Key Features
Automated Return Status Sync via Multi-Carrier Logistics APIs
Smart Claim Filing Assistant with Automated Evidence Generation
Real-time Financial Impact Analytics & SKU-level Performance
Centralized Multi-Account Management for Enterprise Sellers
Automated Alert System for Stalled or Delayed Shipments (>72h)
Dynamic Reporting Engine for Tax and Audit Compliance
The Architecture
I architected and developed an automated reconciliation engine that interfaces directly with courier APIs (Delhivery, BlueDart, Ecom Express). The system utilizes a background worker pool built with BullMQ and Redis to periodically sync shipment statuses. I implemented a custom web scraper using Puppeteer for couriers without public APIs, ensuring 100% data coverage. The frontend features a high-performance data grid built with TanStack Table and Framer Motion, allowing sellers to traverse 10,000+ return rows with sub-second latency. The core logic involves a state machine that tracks every return from 'Requested' to 'Delivered' or 'Claimed', automatically flagging any shipment that stays in a 'Stale' state for more than 72 hours.
Overcoming Challenges
API Rate Limiting: Overcoming aggressive rate limits from logistics providers by implementing a sophisticated request queue with exponential backoff.
Data Standardization: Normalizing inconsistent shipment statuses (e.g., 'In Transit' vs 'Out for Delivery') across 10+ different courier protocols into a unified state machine.
Performance at Scale: Optimizing PostgreSQL queries and implementing Redis-based Materialized Views to maintain fast dashboard load times as the dataset grew to millions of rows.
Protocol & Process
Phase 01: Requirement discovery and logistics lifecycle mapping with senior e-commerce consultants.
Phase 02: Architecture design focusing on background worker reliability and data integrity.
Phase 03: Developing the scraping and API integration layer to ensure robust data ingestion.
Phase 04: Crafting the high-density UI/UX with a focus on operational velocity and dark-mode aesthetics.
Phase 05: Rigorous testing with real-world datasets to calibrate the 'Stale Return' detection algorithms.
Engineered Impact
The platform has successfully recovered over $50,000 in lost inventory value for early adopters, providing a verifiable ROI within 100 days. Achieved a 99.8% accuracy rate in automated claim identification, significantly outperforming manual US/UK market standards for logistics reconciliation.