{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/37b98ab8495d4aa69f0e48e0fe90adba\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/37b98ab8495d4aa69f0e48e0fe90adba-32c12c048f29413a.gif","duration":555.829,"title":"Contextual Embedded Micro-Insurance Recommendation Engine Demo","description":"In this video, I present GrabInsurance, a contextual embedded micro-insurance recommendation engine designed to offer relevant insurance products at the moment a user redeems a deal. The system features a React storefront UI, a fast API backend, and a SQLite analytics database, all working together to provide personalized insurance recommendations based on user intent. I demonstrate how the system adapts to different purchase contexts and discuss the A-B testing implemented to optimize conversion rates. Additionally, I showcase the real-time analytics dashboard that tracks user interactions and conversion metrics. I encourage you to check out the GitHub link I’ll provide to explore the code and see how to run the project yourself."}