- B
- Blockchain
- C
- Customer Churn
- Counterterrorism
- Cybersecurity in the Public Sector
- Credit Card Fraudulent Transactions
- Credit Default Rates
- Conversion Modeling
- Claim Payment Automation Modeling
- Claim Development Modeling
- D
- Drug Delivery Optimization
- Disease Propensity
- Digital Wealth Management
- Direct Marketing
- E
- Estimating Sepsis Risk
- F
- Finding Duplicate Customer Records in Your Database
- Fraud detection
- Finding New Oil and Gas Sources
- Fraudulent Claim Modeling
- G
- Google AdWords Bidding
- H
- Hospital Readmission Risk
- I
- Inventory Forecasting
- Insider Threat in Public Sector
- Insurance Pricing
- L
- Loyalty Program Usage
- Life Insurance Underwriting
- M
- Multichannel Marketing Attribution
- Modeling ICU Occupancy
- N
- Next Best Offer
- Next Best Action
- P
- Product Personalization
- Q
- Quality Assurance
- S
- Supply Chain Management
- View global site search results
Machine Learning in Retail
Retailers deliver better demand forecasting, marketing efficiency, transparency in the supply chain, and profitability through advanced AI applications and a myriad of AI use cases throughout the value chain: from store-level demand and out-of-stock (OOS) predictions to marketing channel modeling and customer LTV predictions. With the abundance of consumer data, changing consumption patterns, global supply chain shakeups, and increased pressure to drive better forecasting, retail businesses can no longer ignore the potential of AI in their industry.