đź“Š Automating Customer Feedback with n8n + AI
Imagine running a business where hundreds — maybe thousands — of customers leave feedback every single day. Manually reading, categorizing, and analyzing all that data? Nearly impossible without a small army of employees.
That’s where automation steps in.
Step 1: The Feedback Form
The journey begins with a simple form. Instead of building a custom app, we use n8n’s internal form feature. Customers enter their name, email, and feedback directly into this form.
No coding, no extra tools — just a clean entry point to capture valuable customer insights.
Step 2: Collecting & Organizing in Google Sheets
Once submitted, every piece of feedback is instantly logged into a Google Sheet. This creates a central repository of customer voices, ready for further processing.
Think about the old way: copying, pasting, and sorting manually. With automation, this step is eliminated — the workflow does all the heavy lifting.
Step 3: The AI “Magic” — Sentiment Analysis
Here’s where things get exciting. Each feedback entry is passed through OpenAI, which classifies it as positive, neutral, or negative.
Example:
This allows businesses to instantly know how customers feel without reading every word themselves.
Step 4: Merging & Mapping Data
The workflow doesn’t just save the raw feedback — it combines it with the AI’s sentiment results. Using n8n, the data is merged and neatly mapped into the Google Sheet columns.
Now, each row contains: âś… Customer Name âś… Email âś… Feedback Text âś… Sentiment Classification
Step 5: Scaling the Process
Why does this matter? Imagine handling 10,000+ feedback entries a day. Without automation, you’d need a full-time team just to keep up. With this setup, it’s hands-off, real-time, and scalable.
And here’s the best part: this isn’t just a technical demo — it’s a business opportunity. Companies would easily pay $1K–$10K per month for a system that captures and analyzes feedback automatically.
The Bigger Picture
Customer feedback is gold. It tells you what’s working, what’s broken, and how to improve. By layering automation with AI, businesses can:
This is more than just a workflow. It’s a foundation for data-driven decision making at scale.
💡 Automation turns what looks like a “small” process into something massive — saving hours of work and unlocking new revenue streams.
👉 If you want to dive deeper into how the workflow is set up step by step, I’ll share a full Skool community post with visuals and breakdowns.