Create a recommendation engine that analyzes user browsing and purchase history to suggest personalized products. The system will improve customer engagement and sales conversion through collaborative and content-based filtering methods.
Collect user interaction and product datasets.
Clean and preprocess behavioral data.
Implement collaborative filtering algorithms.
Develop content-based recommendation models.
Compare performance using evaluation metrics.
Create recommendation dashboards.
Optimize algorithm scalability.
Conduct performance testing.
Analyze improvement in user engagement.
Prepare documentation.
