Conclusion
The custom machine learning model delivered significant business value by enabling instant LTV forecasting, which improved ROAS and optimized marketing spend. Precise user segmentation and the ability to predict LTV for underrepresented segments enhanced targeting efficiency, while the model's scalability ensured long-term adaptability. The project met all technical objectives, reduced advertising waste by over 10% within the first few months, and provided a full ROI within three months after deployment, paving the way for continued growth and efficiency.