Toyota,
The Vehicle Purchase Prediction Project

The project:

• By analyzing customer transactions, key variables and vulnerabilities that impact vehicle purchase decisions were identified, and insights were gained.
• The model was developed by examining local data from all channels and using specific daily and calendar information.
• The predictive model developed with machine learning algorithms was used to estimate customers’ likelihood of purchasing a vehicle in the next month.
• The developed model was automated, and a system was created to renew the model training and estimation process in the specified period and record the current results.

Achievements:

• Creating a decision support system for marketing activities with the knowledge gained.
• Reduction of advertising and labor costs.
• Minimizing the risk of operator errors in the mechanical structure.
• Prioritizing campaign actions using vehicle purchase estimates from customers and applying personalization during campaign times.
• Increase campaign yields to target audiences based on vehicle purchase estimates.
• Spreading data-based decision-making and an analytical culture within the company.