Picture this: it’s your much-anticipated first date with someone you’ve been chatting with on a dating app. You’re not just looking for a pair of pants or a stylish jacket; you’re after a seamless experience, a one-stop shop where your personal stylist crafts outfit suggestions tailored specifically for your special evening. You pick your pieces, make a swift payment, and await their delivery, all in time for your rendezvous.
In this era of booming AI technology, e-commerce has reached new heights. Today’s customers are selective, wanting more than just a transaction. They seek an elevated experience, one that goes beyond the usual online shopping. They crave a ‘jamais vu’, an unparalleled luxury that leaves them captivated and eager for more.
Having a stylist for each of your e-commerce customers is no longer a dream. In today’s article, I will show you the easiest step-by-step way to implement your stylist with Gen AI.
When you visit our e-commerce website and type: ‘I want an edgy party outfit,’ magic begins. Through advanced prompt engineering and our state-of-the-art LLM model, we craft a response in two key parts:
- A carefully selected outfit suggestion that perfectly matches your desires.
- Based on this suggestion, we assemble a customized list of products, neatly organized in JSON format.
As for product lists, we work our magic by translating product descriptions into powerful embeddings.
Then, we embark on a mission to find ’n’ products from our e-commerce product catalog, using the precision of vector search to ensure each item has several perfect fit.
Finally, we present you with the ultimate outfit suggestion, accompanied by a selection of perfectly matched products. It’s an experience that’s nothing short of extraordinary.