🏠 AI Real Estate Lead Qualifier — Typeform to Airtable with 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. 📖 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. ✨ 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 🔄 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) 🤖 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 📧 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 🛠 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 ⚙️ 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 | 🔧 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. 🛡 Robustness Features The Parse AI Output node uses a 4-layer fallback to ensure the workflow never breaks due to AI formatting issues: Direct JSON parse — if Gemini returns clean JSON Strip markdown fences — if Gemini wraps in Regex JSON extraction — if there's extra text around the JSON Field-by-field regex — if JSON is malformed, extracts each field individually 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. 📊 Sample Airtable Record Full Name: Sarah Johnson Email Address: sarah@example.com 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. 📦 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 💡 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 Built with n8n · Google Gemini AI · Typeform · Airtable · SMTP. An n8n automation workflow template by Nirav Gajera.
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