RetailZone Live Dashboard
RetailZone, Chennai
Overview
RetailZone operates 4 stores across Chennai selling home appliances and electronics. Leadership was reviewing sales data that was 2 days old, making restocking decisions based on lagging information and losing sales to preventable stockouts.
The Challenge
Store managers sent daily WhatsApp messages with sales numbers. Someone compiled it into a spreadsheet. Finance reviewed it 2 days later. By the time a stockout was noticed, the item had been out for 3–4 days.
Our Solution
Built a real-time ETL pipeline pulling from all 4 store POS systems every 15 minutes into a central PostgreSQL database. Built a Metabase dashboard with store-wise revenue, top products, stock levels, and target vs actual comparisons. Added n8n automations for daily Slack summaries at 9 AM, stock alerts when any item falls below the reorder threshold, and a weekly PDF report emailed to all directors every Monday at 8 AM.
The Outcome
First week of use: management identified a fast-moving product going out of stock across 2 stores 3 days earlier than they would have with the old system, preventing an estimated ₹80,000 in lost sales. Report preparation dropped from 3 hours weekly to zero.
How we delivered it
Data Audit (Days 1–3)
Audited POS system APIs across all 4 stores, identified data quality issues, designed the unified schema.
ETL Pipeline (Days 4–8)
Python ETL scripts running every 15 minutes, data normalization, historical data import (6 months), PostgreSQL setup on cloud.
Dashboard Build (Days 9–14)
Metabase questions and dashboards for: daily revenue, product performance, store comparison, inventory levels, and weekly trends.
Automation Layer (Days 15–18)
n8n workflows for morning Slack digest, stock threshold alerts, and weekly PDF report generation and email.
Rollout & Training (Days 19–21)
Dashboard walkthroughs with store managers and leadership. Set threshold levels collaboratively. 2-week check-in to adjust metrics.
Tech Stack
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