MV_SetupCustomer: Demographics, contact info, location data, purchase history
MV_Sales & MV_SalesDetail: Order history, item details, pricing, quantities
MV_SetupBrand, MV_SetupCategory, MV_SetupSubCategory: Product hierarchy
MV_SetupArea, MV_SetupCity: Location-based segmentation
ETL processes from multiple data sources (GA4, CRM, POS systems)
Standardization, deduplication, validation of customer and transaction data
Customer segmentation, RFM analysis, seasonal patterns, product affinity
Live transaction processing for immediate recommendation updates
User-based and item-based recommendations using customer behavior patterns
Trending products, seasonal recommendations, category-wise popular items
Deep learning for complex pattern recognition, ensemble methods for accuracy
Live model serving for instant recommendations during customer interactions
REST/GraphQL endpoints for personalized product suggestions
KPI tracking, conversion metrics, A/B testing results
Dynamic customer classification and targeting services
Automated data collection from online sources for market intelligence
Real-time metrics, sales performance, recommendation effectiveness
Personalized recommendations, targeted offers, product discovery
Model management, A/B testing, algorithm performance monitoring
Quick insights, performance queries, automated reporting