- 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

Product Personalization
Target and personalize content and product recommendations, resulting in increased customer engagement, brand value, and sales.
Problem/Pain
Consumers increasingly expect (even demand) individualized brand experiences. Businesses need to provide highly personalized product and service offerings – but it is not practical or scaleable for human teams to understand and adapt to the individual preferences of millions of customers.
Solution
Modern machine learning algorithms accurately discover the preferences and purchasing behaviors of individual consumers. This knowledge enables businesses to target and personalize content and product recommendations, resulting in increased customer engagement, brand value, and sales.
Why DataRobot
Individualization requires complex models that are adept at capturing the complexity of human behaviors and preferences. DataRobot chooses the most accurate model that works best for your data from hundreds the most powerful open-source algorithms.