The Vehicle Purchase Prediction Project
With the Vehicle Purchase Prediction Model Project, Toyota created personalized
audiences based on data and increased campaign conversion rates by 71%.
- 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.
- 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.