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