AI-Powered Product Recommendations
I moved beyond "Customers also bought" by using OpenAI embeddings to analyze product descriptions and suggest truly complementary items.
- Vector Search: I use product metafields to generate vectors, allowing the app to find "visually similar" items for merchants.
- Caching Results: AI calls are expensive; I cache recommendations in Redis for 24 hours to balance cost and performance.
- A/B Testing: I built a dashboard to track the Conversion Rate of AI-driven vs. Standard recommendations.