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Retail
Solutions - Retail
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Retail
The large volume of transactions and data sources affecting projections means that traditional systems are no longer accurate. Instead, we use optimal, raw material for predictive analysis.
Machine learning techniques make perfect use of all the information hidden among millions of data to draw business-related conclusions.
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Applications and usage
• Predict which customers will stop buying
• Increase lifetime value
• Increase cross-selling and up-selling sales based on data
• Attract new customers with lead scoring
• Predict product demand
• Create customer segments based on hundreds of variables
• Determine which products will be purchased simultaneously
• Increase sales of promotions
• Create custom recommendations
TOURISM | RETAIL | MASS CONSUMPTION | BANKING | INSURANCE |
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Sectors
Campaign optimization - Customer segmentation - Customer retention - Custom recommendations - Cross-selling & Upselling - Demand forecasting
Overbooking management - Customer retention - Custom recommendations - Customer segmentation
Demand forecasting - Cross-selling & Upselling - Lead Scoring - Optimization of promotional campaigns
Prediction of non-payments - Fraud detection - Lead Scoring - Customer retention - Risk Scoring
Risk Scoring - Prediction of abandonment - Prediction of non-payments - Automatic dispatching of operations
Demand forecasting - Lead Scoring - Automatic dispatching of operations