How are e-commerce sites or websites able to sort and organize millions of items? All of those reviews, product descriptions and ratings must have some level of technical complexity. The sample web app below leverages the Watson Natural Language Classifier Service to classify e-commerce product descriptions. This can be expanded to help automatically tag reviews, ratings and more. The app accepts plain text descriptions as well as product URLs offered by Kohl’s. Kohl’s was chosen because it’s products are similar in nature to those on Flipkart, an Indian e-commerce company, and JCPenny, which were used as training data. While the intents beyond the postings are similar, the differences in verbiage, syntax and local terminology highlight the power and flexibility of Watson Natural Language Classifier. The data set we will be using consists of a cleaned flipkart and JCPenny datasets made available through Kaggle . The dataset contains product descriptions and category labels.