How to Build a Product Reco App Using JSON + Unstructured Data
Come join our upcoming webinar titled "How to Build a Product Recommendation App Using JSON + Unstructured Data" - an event that will be tailored to developers and data professionals who are eager to learn more about AI-powered recommendation engines!
During this insightful session, we will showcase how to use JSON and unstructured data to build a robust product recommendation engine. The highlight of the webinar is a live demo where we'll showcase how to ask OpenAI for suggestions to add to an in-progress online grocery cart, followed by a codeshare to foster a deeper understanding. With around 4K products in our data catalog and an extensive 1M order product history intertwined with rich web analytics, the demo is set to depict a real-world scenario that mirrors contemporary online retail challenges. This is your chance to explore, learn, and interact with the experts to gain a solid grasp on creating recommendation apps that can significantly enhance the online shopping experience.
What You'll Learn:
Utilizing JSON and unstructured data to craft sophisticated product recommendation systems.
Engaging with OpenAI to facilitate real-time suggestions for an in-progress online grocery cart.
Implementing Free-text vector search to navigate through a vast array of products swiftly and accurately.
Leveraging Cart Completion with LLMs to ensure a seamless shopping experience by suggesting relevant add-ons.
Harnessing the power of Vector Search to provide recommendations based on similar past orders.
Utilizing site analytics to introduce "Customer Also Viewed" recommendations using behavioral analytics
Personalizing the shopping experience with data on previous product page visits, browser information and web traffic data.
Featured Speaker
- Jason Thorsness, Director of Engineering at SingleStoreDB
Jason Thorsness
Director of Engineering at SingleStoreDB