Templates / Collect customer testimonials with GPT-4 analysis, Jotform, Gmail & Google Sheets

Collect customer testimonials with GPT-4 analysis, Jotform, Gmail & Google Sheets

Needs changes

by Jitesh Dugar ✓ · 70 views · created 2025-10-17 · Content Creation, AI Summarization

Needs changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 9 nodes and runs on Jotform events. Along the way it connects Google Sheets, Gmail, Jot Form and OpenAI Chat Model.

How it runs

Trigger: On Jotform events.

  1. Extract Testimonial Data (Edit Fields (Set)): sets 7 fields: customerName, customerEmail, companyName…
  2. AI Testimonial Analysis (AI Agent): runs an AI agent, with model: OpenAI Chat Model
  3. Parse AI Analysis (Edit Fields (Set)): sets 1 field: output
  4. Log to Testimonial Library (Google Sheets): append or update
  5. Generate Coupon Code (Code): runs custom JavaScript code
  6. Send Thank You Email (Gmail): uses Gmail
  7. Notify Marketing Team (Gmail): uses Gmail

Services it uses

Google SheetsGmailJot FormOpenAI Chat Model

Before you upgrade to n8n 3.0

1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:

  • AI Agent v1 (old agent modes) in AI Testimonial Analysis (v1.6): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.

Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).

Removed in 3.0Replace with
AI Agent v1 (old agent modes)
AI Testimonial Analysis (v1.6)
Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.

Nodes used (7)

From the author

Customer Testimonial Collector Workflow Transform scattered testimonials into organized marketing assets - achieving 500 percent increase in testimonial collection, instant multi-channel optimization, and turning happy customers into brand advocates with…

Excerpt from Jitesh Dugar's description on n8n.io.

View the original on n8n.io → Check your own copy

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