A growing online retailer aimed to increase customer engagement and conversion rates by providing a highly personalized shopping experience, moving beyond generic product recommendations.
We developed an E-Commerce Engine using Next.js and a Node.js backend, integrated with OpenAI for GenAI-powered recommendations and personalized search. A headless CMS allows for flexible content management, and Stripe handles secure payments. Customer data is unified in a PostgreSQL database, feeding into the personalization models. This project evolved under a Time & Material model, allowing for iterative feature enhancement.
Integrating GenAI models for real-time recommendations without impacting site performance.
Optimized API calls to the GenAI service and implemented intelligent caching strategies to serve recommendations quickly.
Ensuring the "cold start" problem for new users or products was effectively handled by the recommendation engine.
Combined content-based filtering and trending product data for new users, gradually shifting to collaborative filtering as user data accumulated.
The GenAI-Powered E-Commerce Engine, developed with flexibility under a Time & Material model, transformed the client's online store into a highly engaging and conversion-optimized platform.