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Classify lead sentiment with Google Gemini and send WhatsApp responses via Typeform & Supabase

Danielle GomesDanielle Gomes
1360 views
2/3/2026
ExportWebhookData TransformationAPICSV
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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

n8n Workflow: Classify Lead Sentiment with Google Gemini and Send WhatsApp Responses

This n8n workflow automates the process of classifying lead sentiment from incoming messages using Google Gemini and then sending a tailored WhatsApp response. It integrates with Supabase for data storage and WhatsApp Business Cloud for communication.

What it does

This workflow simplifies and automates the following steps:

  1. Receives Incoming Data: It listens for incoming data via a webhook, which is expected to contain lead information.
  2. Prepares Data: It edits and sets specific fields from the incoming data, likely extracting the lead's message and contact details.
  3. Analyzes Sentiment: It uses the Google Gemini Chat Model and a Sentiment Analysis node to determine the sentiment (e.g., positive, negative, neutral) of the lead's message.
  4. Stores Data: It stores the original lead information and the classified sentiment in a Supabase database.
  5. Sends WhatsApp Response: Based on the classified sentiment, it sends a personalized WhatsApp message back to the lead using the WhatsApp Business Cloud API.
  6. Merges Data: It merges the original and processed data for a complete record.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • Webhook: An external service or application configured to send data to the n8n webhook URL.
  • Google Gemini API Key: Credentials for the Google Gemini Chat Model.
  • Supabase Account: Access to a Supabase project with a configured table for storing lead data.
  • WhatsApp Business Cloud Account: Configured WhatsApp Business Cloud API access and credentials.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Webhook:
    • The Webhook node (ID: 47) is the trigger for this workflow.
    • Copy the webhook URL and configure your external system (e.g., Typeform, a custom application) to send lead data to this URL.
  3. Configure Credentials:
    • Google Gemini Chat Model (ID: 1262): Provide your Google Gemini API credentials.
    • Supabase (ID: 545): Configure your Supabase credentials (Project URL, API Key). Ensure your Supabase table schema matches the data being sent and received by the workflow.
    • WhatsApp Business Cloud (ID: 827): Set up your WhatsApp Business Cloud credentials (e.g., Access Token, Phone Number ID).
  4. Review and Customize Nodes:
    • Edit Fields (Set) (ID: 38): Adjust this node to correctly extract and format the necessary lead information (e.g., message, phone_number, lead_id) from your incoming webhook data.
    • Sentiment Analysis (ID: 1272): Ensure this node is configured to analyze the correct text field from the lead's message.
    • Supabase (ID: 545): Verify the table name and the fields being inserted/updated in your Supabase database.
    • WhatsApp Business Cloud (ID: 827): Customize the message templates and logic for sending responses based on the sentiment analysis. You might want to add conditional logic (e.g., an IF node) before this node to send different messages for positive, negative, or neutral sentiments.
  5. Activate the Workflow: Once all configurations are complete, activate the workflow.

The workflow is now ready to automatically classify lead sentiment and respond via WhatsApp.

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