Customer Feedback Categorizer
Customer feedback only creates value when it's read, structured, and acted on - which rarely happens consistently. This assistant reads each review, survey response, or support comment as it arrives, classifies its theme and sentiment, and drafts a suggested response. It replaces manual tagging and subjective reads with consistent, measurable output your team can act on and report on.
Category: Customer Service
How it works
- A new piece of feedback arrives - a review, survey, or comment
- The assistant reads it and identifies the main theme
- It classifies the sentiment and drafts a suggested response
- The structured record is filed to your table for review
Key benefits
- Replace manual tagging with consistent classification
- Spot negative sentiment before it escalates
- Ground product decisions in measurable evidence
- Respond to feedback faster, with a ready draft
Use cases
- Product teams
- Support and customer success
- CX and operations
- Marketing and brand teams
Good to know
Runs with no external connection - your feedback data stays in your Gaia workspace. The assistant suggests a response; you review before anything is sent.
Frequently asked questions
How does the Customer Feedback Categorizer work?
When a new review, survey response, or support comment is added to your Gaia table, the assistant reads it, identifies the main theme, classifies the sentiment, and drafts a suggested reply - all without any external connections.
Do I need to write any code to use this template?
No, it's a no-code template that runs entirely within your Gaia workspace. You just add your feedback data to the table, and the assistant processes it automatically.
Does it send replies to customers automatically?
No, it only drafts a suggested response. You review and approve the reply before anything is sent - the assistant never sends messages on its own.
Which apps or platforms does it connect to?
It works with your data inside Gaia's native table and does not connect to any external apps like Zendesk or SurveyMonkey. You would need to manually import or paste feedback into the table.
How accurate is the sentiment and theme classification?
The assistant provides consistent, measurable classification based on the text it reads. However, you should always review the output for edge cases or nuanced feedback before acting on it.
