Real-Time Retail Analytics Platform on Google Cloud
Retail
What They Were Facing
MegaMart operated 1,200 stores nationwide but lacked a unified analytics platform. Merchandising decisions relied on week-old batch reports, and the data team spent 80% of their time preparing data rather than generating insights. The absence of real-time inventory analytics was leading to both stockouts on high-demand SKUs and overstock write-downs exceeding $18M annually.
How We Solved It
AQBEE built a real-time retail analytics platform on Google Cloud, ingesting point-of-sale transactions, inventory movements, and customer loyalty data through Pub/Sub into BigQuery. Vertex AI models were trained to forecast demand at the store-SKU level, enabling automated replenishment recommendations. Looker dashboards provided store managers and merchandising teams with self-service analytics, while Cloud Functions powered real-time alerting for stockout predictions and pricing anomalies. Data Studio reports were configured for executive leadership with automated weekly and monthly distribution.
The Impact
The platform delivered a 340% ROI within the first year through optimised inventory management and data-driven merchandising decisions.
AI-driven product placement and promotion recommendations increased average basket size by 28% across participating stores.
Delivered real-time inventory visibility across all 1,200 stores, replacing week-old batch reports with live dashboards refreshed every 15 minutes.
“Before AQBEE, our buyers were making million-dollar inventory decisions based on last week's numbers. Now they have real-time demand signals powered by Vertex AI. The 28% basket size increase alone justified the investment, but the reduction in stockout-related lost sales has been even more impactful.”
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