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Case study: jeans retailer

This step-by-step case study explores how to implement AI in your online retail store to enhance product recommendations:

AI for jeans retailers

AI for jeans retailers

We'll focus on a jeans store and walk through various techniques to optimize data, vectorize it, and perform vector database queries. Here are the steps we'll cover:

  1. Examine data
  2. Why vectorize data?
  3. Vectorize data
  4. Optimize data
  5. Understanding hybrid search
  6. Hybrid search in practice
  7. Understanding reranking
  8. Reranking in practice
  9. AI recommendations playground

This guide will show you how to use text and product image vectors to provide enhanced product recommendations based on customer inquiries. We’ll explore hybrid search, comparing it to purely dense and sparse queries.

By the end, you'll see how these techniques can be implemented in your store chatbot agent to answer customer inquiries like "I'm looking for light blue jeans" or "I'm looking for women's jeans for a summer party".

Let's dive in!

All images/dataset used throughout this guide are from: Aggarwal, P. (2022). Fashion Product Images (Small). Available online: https://www.kaggle.com/datasets/paramaggarwal/fashion-product-images-dataset