GlobeOSS
Retail Analytics
Accelerating the retail industry with AI and Machine Learning to help drive product demand planning, inventory, supply chain analytics, and real-time customer data.
Retail industry is highly competitive. The industry requires AI and Machine Learning that helps to drive product demand planning, inventory, supply chain analytics and real-time customer data.
GlobeOSS is uniquely positioned to help our retail customers in their effort in their digital modernization and transformation, especially in the area of advanced BI, AI/ML, geospatial data science, customer CDP, and IOTs.
Retail Analytics
Use Cases
Supply Chain Analytics
End to end view of supply chain throughout the organization.
Planning
Accurately plan for customer demand – down to the individual store level.
Inventory Planning.
Inventory Replenishment.
Pricing Strategies.
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Customer Insights
Know exactly what your customers want, when they want it, and make sure they get it.
*Store and location performance Insights.
* Customer Value Management
Loyalty.
* Next Best Offer.
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Merchandise & Assortment Planning
Select the right merchandise to the right stores when customers are ready to buy.
Demand Forecast
Forecast daily demand by store, for returns, and for new products.
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Next Best Offer
Determine customer loyalty state, next best action, customer lifetime value using AI.
* Churn Prediction.
* Next Best Offer.
IOT
IOT use case for retail.
Geospatial Supply Chain Optimization
Retailers have to up their game to optimize how their stores, distribution centres, & logistics partners work together to meet the demands of today’s unrelenting consumer.
Site Selection
Predict revenues, identify twin areas, & use new data streams to monitor performance & plan expansion / consolidation efforts effectively.
Geo-Marketing
Public Data and Internal Data combination. Hyper-target your campaigns at a deeper granularity.
Indoor Mapping
Location data generated from WIFI networks, beacons, GPS applications, and Apple Indoor Maps.
Technology
