Have you ever struggled with manually classifying customer feedback at scale? We certainly did. With thousands of text responses coming in every week, our manual classification process was becoming unsustainable – slow, inconsistent, and impossible to scale. That’s when we stumbled upon a surprisingly simple solution: using Snowflake Cortex’s `CLASSIFY_TEXT()` function directly in SQL. No Python, no NLP pipelines, no model fine-tuning required.
We took it a step further and plugged this into a scheduled task to automatically label incoming feedback every week. Now, the pipeline runs itself, and sentiment and category labels get applied without any manual touchpoints. It’s not perfect, but it’s consistent, fast, and gets us 90% of the way with near-zero overhead.
If you’re working with survey data, CSAT responses, or other customer feedback streams, this might be worth exploring. We’d love to hear about how you’re solving this problem in your organization.