Qualify real estate leads from Typeform to Airtable with Gemini and smart email routing

🏠 AI Real Estate Lead Qualifier — Typeform to Airtable with Smart Email Routing

Automatically qualify property leads, score them with AI, save to Airtable, and send personalised emails — all in seconds.

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📖 Description

Every time a prospect submits your Typeform property inquiry, this workflow kicks in automatically. It extracts their details, runs them through an AI lead scoring engine, saves the record to Airtable, and sends a personalised email — a priority response for hot leads, a nurture email for everyone else.

No manual review. No missed leads. No delayed follow-ups.

This is built for real estate agencies, leasing companies, and property managers who receive inquiries through Typeform and want instant, intelligent responses without hiring extra staff.

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✨ Key Features

• Instant lead capture — triggers the moment Typeform receives a submission
• AI lead scoring — Google Gemini classifies every lead as High, Medium, or Low automatically
• Smart email routing — High leads get a priority response, others get a nurture sequence
• Airtable CRM sync — every lead saved with full details + AI assessment
• Robust AI parsing — 4-layer fallback system ensures AI output is always usable
• Personalised emails — name, property type, location, budget pulled into every email automatically
• No-code maintenance — update scoring rules in the prompt, email copy in the nodes

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🔄 How It Works

Prospect submits Typeform inquiry
 ↓
Webhook receives the form payload
 ↓
Extract Typeform Fields
 → name, email, phone, property type
 → purpose, location, budget, requirements
 ↓
AI Lead Qualifier (Google Gemini)
 → lead_score: High / Medium / Low
 → intent, timeline, notes
 ↓
Parse AI Output (4-layer fallback)
 ↓
Save to Airtable CRM
 ↓
High Lead? (IF check)
 ✅ YES → Priority Email (contact within 2 hours)
 ❌ NO → Nurture Email (contact within 1-2 days)

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🤖 AI Lead Scoring Rules

The AI automatically classifies leads based on these criteria:

Score	Criteria
🔴 High	Has budget + specific location + clear purpose (investment or near-term buying)
🟡 Medium	Partial information — needs follow-up to qualify further
🟢 Low	Vague inquiry, missing budget or location, early exploration

The AI also extracts:

• Intent — what the lead is trying to achieve
• Timeline — how urgently they need a property
• Notes — assessment summary for your sales team

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📧 Email Templates

High Lead Email

• Subject: 🏠 [Name], we have properties matching your needs!
• Dark blue header — premium feel
• Full inquiry summary (property, purpose, location, budget, timeline)
• AI assessment notes included
• Promise: senior agent contacts within 2 hours

Nurture Email (Medium / Low)

• Subject: Thanks for reaching out, [Name]!
• Grey header — warm and professional
• Inquiry summary (property, location, budget)
• Preparation tips while they wait
• Promise: contact within 1-2 business days

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🛠 Setup Requirements

1. Typeform Setup

Create a Typeform with these fields and note their field ref IDs from the Typeform API:

Field	Type	Required
Full Name	Short text	✅
Phone Number	Phone	✅
Email Address	Email	✅
Property Type	Multiple choice	✅
Purpose	Multiple choice	✅
Preferred Location	Short text	✅
Budget Range	Multiple choice	✅
Requirements	Long text	✅
Consent	Yes/No	Optional

Connect Typeform webhook:

• Typeform Dashboard → Connect → Webhooks
• URL: your n8n webhook URL (Production URL from the Webhook node)
• Method: POST

2. Update Field Refs

In the Extract Typeform Fields Code node, update the REF_* constants to match your actual Typeform field reference IDs:

const REF_NAME = 'your-field-ref-here';
const REF_EMAIL = 'your-field-ref-here';
const REF_PHONE = 'your-field-ref-here';
// ... etc

Find your field refs from the Typeform API or by logging a test webhook payload.

3. Airtable Setup

Create an Airtable base with a table containing these fields:

Field Name	Field Type
Full Name	Single line text
Email Address	Email
Mobile Phone Number	Phone
Property Type	Single line text
Purpose	Single line text
Preferred Location	Single line text
Budget Range	Single line text
Requirements	Long text
Submit Date	Single line text
Lead Score	Single line text
Intent	Single line text
Timeline	Single line text
Notes	Long text

Update the Save to Airtable node with your Base ID and Table ID.

4. Credentials Required

Credential	Used for	Free?
Google Gemini (PaLM) API	AI lead scoring	Free tier available
Airtable Personal Access Token	CRM save	Free
SMTP	Sending emails	Depends on provider

5. Email Configuration

In both email nodes, update:

• fromEmail — your sending address
• SMTP credential — your email provider details

Recommended SMTP providers for testing: Mailtrap (sandbox), Gmail, SendGrid

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⚙️ Workflow Nodes

Node	Type	Purpose
Webhook	Webhook	Receives Typeform POST payload
Extract Typeform Fields	Code	Parses answers by field ref ID
AI Lead Qualifier	AI Agent	Scores lead using Gemini
Google Gemini Chat Model	LLM	AI model for scoring
Parse AI Output	Code	Extracts JSON with 4-layer fallback
Save to Airtable	Airtable	Creates CRM record
High Lead?	IF	Routes by lead score
Priority Email	Email Send	Sends to High leads
Nurture Email	Email Send	Sends to Medium/Low leads

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🔧 Customisation

Change scoring criteria: Edit the prompt in the AI Lead Qualifier node. Add your own rules — e.g. score higher if budget exceeds a threshold, or if the purpose is investment.

Add more email tiers: Add a third IF branch for Low leads with a different nurture sequence, or add a Slack/WhatsApp alert for High leads.

Use a different form: The Extract Typeform Fields node uses Typeform's field.ref system. Replace it with a Google Forms or Jotform parser by adjusting how you read the incoming webhook body.

Change the AI model: Replace the Google Gemini node with Claude, OpenAI, or any other LLM Chat Model node — no other changes needed.

Add lead deduplication: Before saving to Airtable, add a search step to check if the email already exists and skip or update instead of creating a duplicate.

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🛡 Robustness Features

The Parse AI Output node uses a 4-layer fallback to ensure the workflow never breaks due to AI formatting issues:

1. Direct JSON parse — if Gemini returns clean JSON
2. Strip markdown fences — if Gemini wraps in ```json blocks
3. Regex JSON extraction — if there's extra text around the JSON
4. Field-by-field regex — if JSON is malformed, extracts each field individually
5. Default fallback — if all else fails, sets lead_score: Medium

This means the workflow continues and saves the record even if the AI returns unexpected output.

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📊 Sample Airtable Record

Full Name: Sarah Johnson
Email Address: [email protected]
Mobile Phone: +91 9876543210
Property Type: 2BHK Apartment
Purpose: Investment
Preferred Location: Bandra, Mumbai
Budget Range: ₹80L - ₹1.2Cr
Requirements: Parking, gym, sea view
Submit Date: 2026-03-18T10:30:00Z
Lead Score: High
Intent: Serious buyer looking for investment property with strong rental yield
Timeline: Within 3 months
Notes: High-intent lead with clear budget and location. Has specific amenity requirements. Recommend immediate callback.

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📦 Requirements Summary

• n8n (cloud or self-hosted)
• Typeform account (any paid plan for webhooks)
• Airtable account (free tier works)
• Google AI Studio account for Gemini API key (free tier available)
• SMTP email account

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💡 Enhancement Ideas

• WhatsApp alert — send instant WhatsApp to sales team for every High lead via Twilio
• Calendar booking link — include a Calendly link in the High lead email
• Lead follow-up reminder — add a Wait node + reminder email if no reply in 48 hours
• Slack notification — ping your team channel instantly for High leads
• Lead scoring dashboard — connect Airtable to a dashboard tool for weekly reports

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Built with n8n · Google Gemini AI · Typeform · Airtable · SMTP