Retail analytics concept with POS integration and demand forecasting
What this concept would cover
Multi-POS ingestion, SKU-level demand forecasting, automated reorder suggestions
The Challenge
Retail chains lose revenue to overstocking slow-moving products and stockouts of high-demand items. With data trapped in many different POS systems across stores, they have no unified analytics or demand forecasting capability.
The Solution
Ubikon would build a Python + Next.js analytics platform that ingests data from multiple 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.
POS Integration
Built standardised connectors for multiple 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.
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