Sep 20 • 😎 Share Your Builds
🚀 Project: AI Website Lead Generation & Qualification Chatbot
I’ve just completed my AI Website Lead Generation & Qualification Chatbot built with n8n, AI Agent, Groq, Simple Memory, Structured Output Parser, and Google Sheets.
The goal was to build a chatbot that can interact with website visitors, understand their business requirements, collect lead information, qualify the lead, and store/update the lead in a Google Sheets CRM.
🔹 What it does
The AI collects and structures information such as:
- Name & Email
- Company / Business Name
- Business Type
- Lead Source
- Service Interested In
- Business Challenge
- Current Process
- Lead Volume
- Budget
- Timeline
- Lead Temperature
- Buying Intent
- Qualification Status
I also implemented a one-question-at-a-time rule, so the AI doesn't overwhelm the visitor with multiple questions in a single response.
🧠 Lead Qualification
The system qualifies leads based on:
Name + Email + Company + Business Challenge + Timeline
It also classifies leads as:
🔥 Hot
🟡 Warm
🔵 Cold
and determines their Buying Intent as High, Medium, or Low.
🔄 Lead Database Logic
I connected the chatbot to Google Sheets as a simple CRM.
The workflow checks whether the lead already exists using the conversation's Session ID / Lead ID.
Existing lead:
Get Row → IF → Merge → Update Row
New lead:
Get Row → IF → Append Row
This allows the workflow to update existing conversations instead of creating duplicate records within the same session.
🛡️ AI Guardrails
I spent a lot of time improving the prompt so the AI:
- Doesn't guess missing information
- Doesn't invent company names or lead sources
- Preserves the visitor's actual budget and lead volume
- Doesn't confuse business type with company name
- Doesn't make unsupported claims about integrations or capabilities
- Asks only one question at a time
📚 Biggest Learning
One of my biggest takeaways from this build is that an AI Agent is much more than just connecting an LLM to a workflow.
The prompt, memory, structured output, data mapping, qualification logic, database logic, and conditional branches all have to work together.
This project helped me understand how to build an AI automation as a complete system rather than just a chatbot.
Learning → Building → Testing → Debugging → Improving. 🚀
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🚀 Project: AI Website Lead Generation & Qualification Chatbot
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