Client: International Retailer

Challenge:
The retailer collected massive data from online platforms, POS systems, and loyalty programs but lacked real-time insights to optimize inventory, prevent stock issues, and personalize customer engagement.

Solution (Detailed):
Chrysalis deployed an AI-analytics engine to unify and analyze data streams. Key features:

• Demand Forecasting – Machine learning models predicted demand for specific SKUs by geography, season, and promotions.
• Inventory Optimization – AI-driven restocking alerts minimized stockouts and reduced overstocking costs.
• Sentiment & Behavior Analytics – NLP models analyzed customer feedback, reviews, and browsing behavior to optimize campaigns.

Results:
✔ 25% reduction in inventory carrying costs.
✔ 20% increase in marketing ROI via hyper-personalized campaigns.
✔ Significant improvement in store operations with predictive staffing.