Module 3: Hands-on Lab: Building a Lead Qualification Workflow
This hands-on lab will guide you through the process of building a practical n8n workflow that uses a raiaAI agent to qualify a new lead.
Objective: To create a workflow that is triggered by a new lead, uses a raiaAI Analyst Agent to score the lead, and then sends a notification to a sales team based on the score.
Materials:
Access to n8n
An Analyst Agent that you have created in the raiaAI Launch Pad (instructions below)
Access to a Slack workspace
Step 1: Create the Analyst Agent
In the raiaAI Launch Pad, create a new agent named "Analyst Agent - Lead Scoring - [Your Name]".
In the instructions, define the agent's role: "You are a data analyst. Your job is to score a new lead based on the provided information. A good lead is a company with more than 100 employees and a budget of over $10,000. A great lead is a company with more than 500 employees and a budget of over $50,000. Respond with only the score: 'Poor', 'Good', or 'Great'."
Step 2: Build the n8n Workflow
The Trigger: For this lab, we will use a "Webhook" trigger. A webhook is a URL that can receive data from other applications. In a real-world scenario, this webhook would be called by a lead capture form on a website.
Add a Webhook node to your canvas.
Copy the "Test URL" provided by the node.
Simulate a New Lead: Open a new browser tab and paste the webhook URL. Add the following query parameters to the URL to simulate a new lead:
?companyName=TechCorp&employeeCount=250&budget=25000Press Enter. You should see a message in your browser that says "Workflow executed."The raiaAI Node:
Add a raiaAI node to your workflow and connect it to the Webhook node.
Configure the node with your raiaAI credentials.
Select your "Analyst Agent - Lead Scoring" agent.
In the "Prompt" field, you will use data from the webhook. N8n allows you to reference data from previous nodes using expressions. Use the following expression to create the prompt:
Company: {{ $json.query.companyName }}, Employees: {{ $json.query.employeeCount }}, Budget: {{ $json.query.budget }}
The IF Node:
Add an IF node and connect it to the raiaAI node. The IF node will allow us to branch the workflow based on the agent's response.
Configure the IF node to check the output of the raiaAI node. Set the condition to:
{{ $node["raiaAI"].json.response }}- "is" - "Great".
The Slack Nodes:
Add two Slack nodes to your canvas.
Connect the "true" output of the IF node to the first Slack node. Configure this node to send a message to a #sales channel: "🔥 Great new lead! Company: {{ $json.query.companyName }}. Get on it!"
Connect the "false" output of the IF node to the second Slack node. Configure this node to send a message to a #marketing channel: "New lead for nurture campaign: {{ $json.query.companyName }}."
Step 3: Test the End-to-End Workflow
Execute the workflow by calling the webhook URL with different data. Try a "Poor" lead and a "Great" lead.
Verify that the correct message is sent to the correct Slack channel based on the lead score.
This lab has demonstrated how to build a powerful, automated workflow that combines the data-processing capabilities of n8n with the intelligence of a raiaAI agent. This is a foundational pattern that you will use to build a wide variety of automated solutions for our clients.
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