Customer Feedback Routing

The Problem with Unprocessed Feedback

Customers leave feedback across many channels — post-purchase surveys, NPS forms, support follow-up emails, and review requests. Most of it sits unread because manually processing high volumes of feedback is impractical. An automated routing workflow reads every response, classifies it by sentiment, and ensures the right people see the right feedback at the right time.

The Workflow Architecture

1. Trigger — a Webhook Trigger connected to your survey tool (Typeform, Google Forms, Tally), or an n8n Form Trigger if you want a self-hosted survey. The response text and any rating score are passed in the payload.
2. Sentiment Analysis node — classify the feedback text. Use five categories for nuance: Very Positive, Positive, Neutral, Negative, Very Negative.
3. Information Extractor node — extract structured fields from the free-text response: main_issue, product_mentioned, requested_feature (if any). This turns unstructured feedback into queryable data.
4. Switch node — route on sentiment category:

• Very Positive or Positive: Airtable node → add to testimonials database with extracted fields + original text.
• Neutral: Airtable node → log for quarterly review with no immediate action.
• Negative or Very Negative: Slack node → alert #customer-success with full feedback text, customer email (if available), and extracted issue fields. Add an AI Agent draft response for the team to review and personalise before sending.

Net Promoter Score Tracking

If your survey includes an NPS rating (0–10), add a separate branch before the sentiment routing. Classify the score: 9–10 = Promoter, 7–8 = Passive, 0–6 = Detractor. Append each response to a Google Sheets NPS tracker with the date, score, and category. This gives you a rolling NPS chart without any manual data entry. Connect a weekly formula row to calculate the current NPS score: % Promoters minus % Detractors.

Generating Testimonials Automatically

For Very Positive feedback routed to the testimonials database, add a Basic LLM Chain step after the Airtable append. Pass the raw feedback text and ask the model to rewrite it as a clean, publishable testimonial quote — preserving the customer's meaning but removing filler words and correcting obvious typos. Store the generated testimonial alongside the original. Review before publishing to your website.

Closing the Loop with Respondents

For negative feedback where you have the customer's email, add a Gmail node to send an acknowledgement within minutes: "Thank you for your feedback — a member of our team will be in touch shortly." This acknowledgement alone significantly improves customer perception of how their feedback was handled, even before the actual response is sent.