How to Leverage NLP for Product Data Science

Natural language processing techniques can significantly enhance traditional product data science models that typically rely on behavioral data. The guide outlines how to apply NLP to common business problems such as customer churn prediction, lifetime value (CLV) modeling, and customer segmentation. Textual data from sources like support tickets, reviews, and surveys often provides earlier signals and explains the "why" behind user actions. Specific NLP methods covered include sentiment classification, topic modeling, and using text embeddings for similarity search and recommendations, complete with code examples.