- 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

Multichannel Marketing Attribution
Problem/Pain
Businesses spend billions of dollars each year on advertising – but are they spending it well? Traditional measurements such as last-click attribution are widely acknowledged by industry leaders to be flawed. Marketers need a better way to determine which advertising activities are the true drivers of sales so they can focus their resources accordingly.
Solution
Modern machine learning algorithms objectively determine how each touchpoint contributes to sales, allowing you to accurately calculate its ROI. By re-allocating advertising spend to the touchpoints with the highest ROI, you will increase sales while simultaneously reducing costs.
Why DataRobot
Developing models capable of combining the complexities of human behavior and the need to allow for delays between advertising activities and subsequent purchases is a monumental task. The DataRobot automated machine learning platform finds the most accurate models for this complex problem with just one click.