Supermarket Stores
Sales Forecast and Smart Replenishment
The supermarket and convenience store industry faces fierce competition from evolving consumer demands, rapid product turnover and inventory-cost balance. Key challenges include managing diverse products across store formats and adapting to demand variations.
Core pain points are inventory inefficiencies high stock-outs and holding costs from manual replenishment (e.g., Carrefour’s fresh produce gaps, Dia’s slow turnover) and lack of real-time data, causing delayed forecasting and missed sales.
Core Problems Solved
We developed a solution that employs AI-powered inventory management systems to automate real-time monitoring, demand forecasting and replenishment planning. By integrating sales data, inventory levels and external factors (e.g., weather, holidays), the system addresses stock imbalances and reduces reliance on manual planning.
Key Features of the Solution
- Intelligent Replenishment
-
Real-Time
Alerting
- Multi-Channel Data Integration
Achievements and Benefits
91%
Stockout rate reduced by 15%, with inventory turnover improving by 9 days.
Recommendation adoption rate reached 91%, reflecting high trust in AI-generated insights.
7%
Stockout rate decreased by 7%, and inventory turnover improved by 1.8 days.
System covered 98% of stores, with 86% of replenishment suggestions implemented.
Operational Agility
Shifted from weekly to daily replenishment cycles, enabling faster response to demand surges (e.g., holiday sales).
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Supermarket Stores
Smart Store Site Selection
The retail industry faces intense competition from rapid urbanization, changing consumer behaviors and
e-Commerce growth. Key challenges include selecting high-potential store locations, optimizing regional business targets and ensuring operational consistency.
Core pain points are inefficient manual site selection, reliant on fragmented data and slow field surveys and poor data-driven management due to outdated systems and siloed data, hindering real-time decisions and operational scalability.
Core Problems Solved
The Smart Site Selection solution leverages big data and AI algorithms to automate site evaluation and planning. By integrating internal and external data (e.g., customer flow, competitor locations, demographic statistics), it addresses the challenges of manual site selection and data fragmentation, enabling data-driven expansion strategies.
Key Features of the Solution
- Intelligent Location Recommendation
-
End-to-End
Management Platform
Achievements and Benefits
60%
Efficiency Gains: Reduced site selection time from weeks to days, with AI-driven recommendations cutting manual workload by 60%.
25%
Success Rate Improvement: Increased new store profitability by 25% through data-driven location scoring.
Risk Mitigation
Risk Mitigation: Minimized site selection failures by incorporating real-time competitor analysis and demand forecasting.
