Advertising Optimization Module
Businesses may find online advertising complex and confusing. One challenge is to maximize results in a cost-effective manner. Based on historical data from advertising campaigns, we developed a response model to simulate different types of custom audience behavior.
Combining this with a model for campaign parameter selection, we created a virtual environment to run advertising campaign simulations.
- Reinforcement Learning
- Recurrent Neural Network
- Random Forest
- Decision Tree