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AI-Driven Assortment Optimization Platform for National Pharmacy Chain
  1. case
  2. AI-Driven Assortment Optimization Platform for National Pharmacy Chain

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AI-Driven Assortment Optimization Platform for National Pharmacy Chain

dataforest.ai
Retail
Healthcare
Consumer products & services

Business Challenges

The client struggles with creating location-specific product assortments due to diverse regional demographics, varying store locations (urban vs. suburban), and complex demand patterns. Current manual processes lead to suboptimal inventory allocation, missed sales opportunities, and inefficient pharmacist operations.

About the Client

One of the largest pharmacy chains operating 2,000+ stores across 30 regions with 13,000+ product SKUs

Key Objectives

  • Develop AI-powered mathematical models for hyper-localized assortment optimization
  • Integrate location intelligence with 48-months of sales data for predictive analytics
  • Automate POS terminal synchronization for real-time inventory adjustments
  • Improve sales performance by 7-10% through data-driven assortment decisions
  • Enhance operational efficiency by streamlining pharmacist workflows

Core System Capabilities

  • Geospatial clustering based on housing density and transportation hubs
  • Dynamic product assortment recommendations using TensorFlow models
  • Real-time POS terminal integration for inventory synchronization
  • Predictive demand forecasting with 88% accuracy
  • Dashboard for monitoring stockout reduction metrics

Technology Stack

Python
PySpark
SciPy
TensorFlow
Hadoop

System Integrations

  • POS terminals
  • Existing inventory management systems
  • Sales data warehouses

Performance Requirements

  • Scalable to handle 2,000+ locations
  • Real-time data processing
  • 99.9% system uptime
  • SOC 2 compliance

Expected Business Outcomes

Implementation of this solution is projected to deliver a 7% increase in sales through optimized product offerings, 10% productivity gains in store operations, and 0.9% reduction in stockouts. The AI-driven approach will enable proactive inventory management and location-specific merchandising strategies.

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