RetailPulse

Retail analytics with POS integration and demand forecasting

300+

Retail Stores

42%

Stockout Reduction

-28%

Inventory Carrying Cost

91%

Forecast Accuracy

The Challenge

Australian retail chains were losing millions annually to overstocking slow-moving products and stockouts of high-demand items. With data trapped in 15 different POS systems across stores, they had no unified analytics or demand forecasting capability.

The Solution

Ubikon built a Python + Next.js analytics platform that ingests data from 15 POS systems via standardised connectors, runs scikit-learn demand forecasting models per SKU per location, generates automated reorder suggestions, and provides a React dashboard with real-time sales analytics, customer segmentation, and promotional impact analysis.

How We Built It

POS Integration

Built standardised connectors for 15 POS systems (Lightspeed, Square, Vend, Shopify POS, custom systems).

Data Warehouse

PostgreSQL data warehouse with ETL pipelines, product catalogue normalisation, sales data harmonisation.

ML Forecasting

scikit-learn demand prediction per SKU per location, seasonal adjustment, promotional lift modelling.

Analytics Dashboard

React dashboard with real-time sales, customer segmentation, basket analysis, promotional ROI tracking.

Inventory Module

Automated reorder suggestions, dead stock identification, transfer recommendations between locations.

"RetailPulse unified data from our 12 store locations running 3 different POS systems into one dashboard. The demand forecasting reduced our stockouts by 42% in the first quarter. Ubikon delivered the analytics platform our retail group had been searching for."

Michael Torres

Head of Operations, RetailPulse