Today I’m excited to share one of my most impactful automation builds:
a complete AI-powered Customer Feedback Intelligence System built in Make.
Most companies collect feedback…
But very few are able to analyze, classify, and act on it instantly.
So I built a workflow that turns raw customer messages into real-time insights.
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🔥 What the Workflow Does
This automation runs the entire feedback lifecycle end-to-end:
🧹 1. Data Normalization
Raw text is cleaned, standardized, and prepared for analysis so every input becomes usable.
🎭 2. Sentiment Analysis
Detects mood (positive, neutral, negative) and adds a numeric sentiment score.
💛 3. Emotion Extraction
Identifies deeper emotional layers like frustration, excitement, confusion, urgency, etc.
🏷️ 4. Topic Classification
Automatically categorizes the message under tags such as:
Product Issue
Feature Request
Billing
Support Quality
UX Feedback
🤖 5. AI Response Suggestion
Generates a ready-to-send professional reply that customer teams can use immediately.
📊 6. Enriched Data Storage
All insights are written back into Google Sheets — turning it into a live feedback dashboard.
🚨 7. Urgent Feedback Escalation
If the system detects anything critical, it auto-routes the message to Slack
so the team can act instantly.
💡 Why This Workflow Matters
✔ Saves hours of manual reading
✔ Helps teams understand customer emotions
✔ Fast-tracks resolution of urgent issues
✔ Creates structured data from messy feedback
✔ Improves support quality + customer satisfaction
✔ Works at scale without adding new staff
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