Classify lead sentiment with Google Gemini and send WhatsApp responses via Typeform & Supabase
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
Nodes used (7)
- Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Webhook
n8n-nodes-base.webhook - Edit Fields (Set)
n8n-nodes-base.set - Sentiment Analysis
@n8n/n8n-nodes-langchain.sentimentAnalysis - Supabase
n8n-nodes-base.supabase - Merge
n8n-nodes-base.merge - WhatsApp Business Cloud
n8n-nodes-base.whatsApp
What it does
Automatically classify incoming leads based on the sentiment of their message using Google Gemini, store them in Supabase by category, and send tailored WhatsApp messages via the official WhatsApp Cloud API. ✅ Use Case: This workflow is ideal for sales, onboarding, and customer support teams who want to: Understand the tone and urgency of each lead Prioritize hot leads instantly Send smart, automatic WhatsApp replies based on user sentiment 🧠 How it works: Capture lead via a Typeform webhook Clean and structure the data (name, email, message, etc.) Run sentiment analysis using Google Gemini to classify the message as: Positive → Hot Lead Neutral → Warm Lead Negative → Cold Lead Store lead data in Supabase under the corresponding category Merge data to unify flow paths Send WhatsApp message using the official WhatsApp Cloud API, with a custom reply for each sentiment result 🔧 Tools used: Typeform (incoming data) Google Gemini (AI-based sentiment classification) Supabase (database) WhatsApp Cloud API (response automation) 🏷 Tags: AI, Sentiment Analysis, Lead Qualification, Supabase, WhatsApp, Gemini, Typeform, CRM, Automation, Customer Engagement