Quick Overview
This workflow captures leads via an n8n form, stores them in an n8n Data Table, uses a Groq Llama 3.3 chat model to score and categorize each lead and draft a reply, optionally alerts in Slack and creates a Google Task, and writes the results back to the Data Table.
How it works
- Receives a new lead submission through an n8n Form trigger (name, email, company, source, and message).
- Saves the submitted lead into an n8n Data Table and keeps only the fields needed for scoring.
- Sends the lead details to a Groq Chat Model via an AI Agent to generate a JSON response with a score (1–100), tier (Hot/Warm/Cold), and a suggested reply.
- Uses the AI Agent’s tool actions to post an alert to Slack and create a task in Google Tasks only when the lead’s score is above the defined threshold.
- Parses the AI Agent output as JSON and updates the original Data Table row with the generated score, tier, and reply.
Setup
- Configure the n8n Form trigger and embed or share its URL where you collect leads.
- Create or select an n8n Data Table for leads and ensure it includes columns for score, tier, reply, and an id used to match rows during updates.
- Add a Groq API credential and select the Groq chat model used by the AI Agent.
- Add Slack credentials and set the target channel for high-score lead alerts.
- Add Google Tasks credentials (and optionally Google Sheets OAuth credentials if you intend to use the Google Sheets tool) for the AI Agent’s follow-up actions.