AI-powered product recommendation engine for building custom PCs
What Makes AI-Powered Recommendation Engines Different?
Traditional recommendation systems often rely on simple rules or collaborative filtering. A rule-based system might suggest a CPU cooler simply because it’s in the “cooling” category. Collaborative filtering, as used on many e-commerce sites, recommends products based on what other users with similar browsing or purchasing habits have bought. While effective for simple products, these methods fall short for the intricate task of building a PC, where component compatibility is a non-negotiable requirement.
AI-powered engines go much further by using a hybrid approach that combines various data points.
- Content-Based Filtering: The AI analyzes the attributes of each PC component—such as the socket type of a motherboard, the power draw of a graphics card, or the form factor of a case—to ensure compatibility. For instance, if you select an AMD CPU, the AI will only recommend motherboards with a compatible AMD socket.
- Collaborative Filtering: It