Clustering products by text

Summary

Text clustering with NLP automates product categorization for furniture and decor businesses based on titles and descriptions.

Product clustering using text analysis and NLP

A furniture and decor business wants to automatically group products based on title, description, and dimensions. The first step is creating categories through unsupervised clustering. Techniques like TF-IDF, sentence embeddings, and K-means are well suited for this task.

Why automated categorization adds value

Manual product categorization does not scale with growing catalogs. NLP-based clustering finds patterns humans miss and enables rapid classification of new products. This improves search results, recommendations, and reporting.

Approach for BI professionals

Start with sentence embeddings (e.g., sentence-transformers) to vectorize product text. Combine with normalized numerical features like weight and dimensions. Use K-means or HDBSCAN for clustering and validate results with domain experts.