AI automate UX feedback: Sentiment & emotion analysis in Google Sheets + OpenAI

Who's it for [](https://youtu.be/tbx5rTQqIKs)

Product managers, customer success teams, and UX researchers who collect feedback in Google Sheets and want to automatically categorize and analyze it with sentiment and emotions insights. Ideal for teams processing dozens or hundreds of customer comments daily.

- [Read on Medium](https://medium.com/@parhumm/the-future-of-listening-how-ai-turns-feedback-into-clarity-free-ux-n8n-ai-workflow-5dea288ecde1) - [Watch on Youtube](https://www.youtube.com/watch?v=tbx5rTQqIKs&feature=youtu.be)

What it does

This workflow automatically tags and analyzes customer feedback stored in Google Sheets using OpenAI's GPT-4. It reads unprocessed feedback entries, sends them in batches to OpenAI for intelligent tagging and sentiment analysis, then writes the results back to your sheet—complete with up to 3 relevant tags per feedback, sentiment scores (Very Negative to Very Positive), and emotional analysis.

The workflow uses batch processing to optimize API costs: instead of sending 10 separate requests, it sends one request with all 10 feedbacks, reducing API calls by ~90%.

How it works 1. Fetches allowed tags from a Tags sheet and new feedback entries (where Status is empty) from a Feedbacks sheet 2. Merges tags with feedbacks and processes them in batches of 10 3. Sends each batch to OpenAI with a structured prompt requesting tags, sentiment, and emotional analysis 4. Writes results back to Google Sheets with tags, sentiment, emotions, and timestamps

Requirements