Build a Customer Feedback Analysis Engine
Turn scattered customer feedback into tracked, actionable themes in about an hour a month.
Download workflow config (JSON)How the data moves
This is a handoff plan, not an automatic integration. Review outputs before the next step. Unlabeled arrows show order, not a verified data format. Use the capability links to explore tool substitutions.
Step 1
Aggregate Reviews, Feedback, and Survey Responses
Collect all customer feedback from reviews, support tickets, and surveys into one place before analysis begins.
Tools
No catalog tool specified
Step 2
Categorize Sentiment and Themes
Run the collected feedback through ChatGPT to tag each item by sentiment and recurring theme.
Step 3
Extract Actionable Insights
Ask Claude to turn the categorized feedback into a short list of concrete actions worth prioritizing.
Step 4
Track Trends Over Time
Log each month's themes and sentiment scores in Airtable AI so you can see whether things are improving or slipping.
Time Required
1 hour per month
Expected Result
A running trend log of customer sentiment and themes pulled automatically from every review and survey response.
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