End-to-end analytics suite for Blinkit, Swiggy, and JioMart — 100k+ orders analyzed to forecast demand, optimize SLAs, and reduce churn (+37% growth impact)
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Sep 9, 2025 - Jupyter Notebook
End-to-end analytics suite for Blinkit, Swiggy, and JioMart — 100k+ orders analyzed to forecast demand, optimize SLAs, and reduce churn (+37% growth impact)
Score your quick commerce cities by ad performance. Know where to scale, hold, or cut budget.
Platform connecting local shops for ultra fast cheap delivery... Created at https://coslynx.com
Business analytics & data visualization project analyzing Blinkit’s quick commerce model-delivery speed, urgency marketing, customer behavior, and revenue insights using Tableau.
AI-powered quick commerce intelligence system that tracks products, pricing, and availability across Blinkit, Zepto, and Instamart.
Quick-commerce delivers in 10 minutes. But the customer spends 15 minutes deciding what to order. The bottleneck isn't the rider — it's the shopping itself.
This is the server side code for a real life quick commerce application clone
Excel-based analysis of 15-minute delivery SLA performance for Zepto & Instamart
Built an executive-level Quick Commerce War Room using Python, Pandas, Power BI, and DAX to analyze 500K+ orders, customer behavior, product performance, and delivery operations.
End-to-end Business Intelligence project for identifying expansion-ready districts using Python, SQL, and Power BI.
AI-powered system for optimizing inventory, demand forecasting, and supply chain in quick commerce dark stores
🏗️ System architecture study comparing e-commerce vs quick-commerce — focusing on backend architecture, data consistency, scalability, and operational complexity.
End-to-end quick commerce analytics comparing Zepto vs Blinkit — SQL, Python (t-test, chi-square, K-Means, RFM, SPC, ARIMA), Excel, Power BI 7-zone war room
DailyDelish: Fresh Produce, Your Way
Fully-featured e-commerce platform designed for performance and scalability. The backend is powered by Django Rest Framework (DRF), ensuring secure and efficient API endpoints, while the frontend is built with React to deliver a seamless, responsive user experience.
End-to-end quick commerce analytics project leveraging Excel, SQL, Python, and Power BI for sales analysis, customer insights, and business performance monitoring.
Power BI dashboard for analyzing Blinkit sales and quick commerce trends
Full-stack quick-commerce grocery app — Flutter mobile client + Node.js/Express backend with phone OTP auth, live order tracking via SSE, and admin dashboard
Quick-Commerce delivery analytics using Python — EDA, hypothesis testing, ML classification, clustering, and time series forecasting on 591K records.
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