vinci-king-01 This workflow corresponds to n8n.io template #6625 — we link there as the canonical source.
This workflow follows the Google Sheets → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"id": "VhEwspDqzu7ssFVE",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "My workflow 2",
"tags": [
{
"id": "DxXGubfBzRKh6L8T",
"name": "Revenue Optimization",
"createdAt": "2025-07-25T16:24:30.370Z",
"updatedAt": "2025-07-25T16:24:30.370Z"
},
{
"id": "IxkcJ2IpYIxivoHV",
"name": "Content Strategy",
"createdAt": "2025-07-25T12:57:37.677Z",
"updatedAt": "2025-07-25T12:57:37.677Z"
},
{
"id": "PAKIJ2Mm9EvRcR3u",
"name": "Trend Monitoring",
"createdAt": "2025-07-25T12:57:37.670Z",
"updatedAt": "2025-07-25T12:57:37.670Z"
},
{
"id": "YtfXmaZk44MYedPO",
"name": "Dynamic Pricing",
"createdAt": "2025-07-25T16:24:30.369Z",
"updatedAt": "2025-07-25T16:24:30.369Z"
},
{
"id": "wJ30mjhtrposO8Qt",
"name": "Simple RAG",
"createdAt": "2025-07-28T12:55:14.424Z",
"updatedAt": "2025-07-28T12:55:14.424Z"
}
],
"nodes": [
{
"id": "b3039a5a-fac6-42bc-8165-df16a3a3e610",
"name": "\ud83d\udccb Schedule Info",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1152,
144
],
"parameters": {
"color": 2,
"width": 400,
"height": 852,
"content": "# Daily CRE Scanner \u23f0\n\n**Automated Market Monitoring:**\n- Runs every 24 hours automatically\n- Triggers the entire CRE intelligence pipeline\n- No manual intervention required\n- Consistent market data collection\n\n**Schedule Benefits:**\n\u2705 Fresh data daily\n\u2705 Catches new listings immediately\n\u2705 Tracks market changes over time\n\u2705 Reliable automation\n\n**Configuration:**\n\u2022 Interval: 24 hours\n\u2022 Timezone: Server default\n\u2022 Error handling: Built-in retry\n\u2022 Next execution: Visible in logs\n\n**What Happens Next:**\n\u2192 Triggers CRE data collection from major platforms\n\u2192 Initiates complete market analysis\n\u2192 Generates daily intelligence report"
},
"typeVersion": 1
},
{
"id": "072af1a6-fc7e-435e-bd7e-b68e5eeb6d84",
"name": "Daily CRE Scanner",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-1008,
832
],
"parameters": {
"rule": {
"interval": [
{
"field": "hours",
"hoursInterval": 24
}
]
}
},
"typeVersion": 1.2
},
{
"id": "5239bd82-fc3a-42df-bea8-40e1f0d2c01b",
"name": "\ud83d\udccb Data Collection",
"type": "n8n-nodes-base.stickyNote",
"position": [
-752,
144
],
"parameters": {
"color": 3,
"width": 400,
"height": 852,
"content": "# CRE Data Collector \ud83d\udd77\ufe0f\n\n**AI-Powered Web Scraping:**\n- Uses ScrapeGraphAI for intelligent extraction\n- Targets major CRE platforms (LoopNet)\n- Structured data output with schema\n- Handles dynamic content automatically\n\n**Data Points Collected:**\n\u2705 Property ID & type\n\u2705 Size (square footage)\n\u2705 Location details\n\u2705 Pricing information\n\u2705 Lease rates ($/sqft)\n\u2705 Contact information\n\n**API Configuration:**\n\u2022 Endpoint: ScrapeGraphAI smart scraper\n\u2022 Method: POST with JSON payload\n\u2022 Timeout: 60 seconds\n\u2022 Authentication: Header-based\n\n**Target Platform:**\n\u2022 LoopNet commercial listings\n\u2022 Real-time market data\n\u2022 Comprehensive property details\n\n**Output Format:**\n\u2192 Structured JSON with listings array\n\u2192 Ready for immediate analysis"
},
"typeVersion": 1
},
{
"id": "22906cc4-e61a-440d-8a62-61c0633549bb",
"name": "CRE Data Collector",
"type": "n8n-nodes-base.httpRequest",
"position": [
-608,
816
],
"parameters": {
"url": "https://api.scrapegraphai.com/v1/smartscraper",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "headerAuth",
"bodyParameters": {
"parameters": [
{
"name": "website_url",
"value": "https://www.loopnet.com/search/commercial-real-estate/"
},
{
"name": "user_prompt",
"value": "Extract commercial real estate listings: property type, size, location, price, lease rate, contact info"
},
{
"name": "output_schema",
"value": "{\"listings\": [{\"id\": \"string\", \"type\": \"string\", \"size_sqft\": \"number\", \"location\": \"string\", \"price\": \"number\", \"lease_rate\": \"number\", \"contact\": \"string\"}]}"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "131f2431-f6f1-44b7-87ef-d0cdf7690f3e",
"name": "\ud83d\udccb Analysis Engine",
"type": "n8n-nodes-base.stickyNote",
"position": [
-352,
144
],
"parameters": {
"color": 4,
"width": 400,
"height": 852,
"content": "# CRE Analyzer & Dashboard \ud83d\udcca\n\n**Comprehensive Market Intelligence:**\n- Processes scraped listings data\n- Generates market summary & insights\n- Identifies investment opportunities\n- Creates actionable dashboard\n\n**Analysis Features:**\n\u2705 Property type distribution\n\u2705 Location popularity ranking\n\u2705 Average lease rate calculation\n\u2705 Below-market opportunity detection\n\u2705 Alert generation system\n\n**Key Calculations:**\n\u2022 Total listings processed\n\u2022 Market rate averages\n\u2022 Geographic clustering\n\u2022 Opportunity scoring\n\u2022 Priority rankings\n\n**Alert Triggers:**\n\u2022 High opportunity count (>10 properties)\n\u2022 Rate alerts (>$30/sqft average)\n\u2022 Market anomalies\n\n**Dashboard Output:**\n\u2192 Executive summary with KPIs\n\u2192 Top 5 property types & locations\n\u2192 Priority opportunities list\n\u2192 Actionable next steps"
},
"typeVersion": 1
},
{
"id": "702d76c3-3229-446b-adaf-2c0d8e751121",
"name": "CRE Analyzer & Dashboard",
"type": "n8n-nodes-base.code",
"position": [
-192,
864
],
"parameters": {
"jsCode": "// Simplified CRE Analysis & Dashboard\nconst scrapedData = $input.all()[0].json;\nconst listings = scrapedData.listings || [];\n\n// Core analysis\nconst analysis = {\n total_listings: listings.length,\n avg_lease_rate: 0,\n property_types: {},\n top_locations: {},\n opportunities: [],\n alerts: []\n};\n\n// Process listings\nlet totalRate = 0;\nlet rateCount = 0;\n\nlistings.forEach(listing => {\n // Track property types\n const type = listing.type || 'Unknown';\n analysis.property_types[type] = (analysis.property_types[type] || 0) + 1;\n \n // Track locations\n const location = listing.location || 'Unknown';\n analysis.top_locations[location] = (analysis.top_locations[location] || 0) + 1;\n \n // Calculate average rates\n if (listing.lease_rate) {\n totalRate += listing.lease_rate;\n rateCount++;\n }\n \n // Identify opportunities (below market rate)\n if (listing.lease_rate && listing.lease_rate < 20) {\n analysis.opportunities.push({\n id: listing.id,\n type: listing.type,\n location: listing.location,\n rate: listing.lease_rate,\n size: listing.size_sqft,\n opportunity: 'Below Market Rate'\n });\n }\n});\n\nanalysis.avg_lease_rate = rateCount > 0 ? (totalRate / rateCount).toFixed(2) : 0;\n\n// Generate alerts\nif (analysis.opportunities.length > 10) {\n analysis.alerts.push({\n type: 'High Opportunity Count',\n message: `${analysis.opportunities.length} below-market properties found`,\n priority: 'High'\n });\n}\n\nif (analysis.avg_lease_rate > 30) {\n analysis.alerts.push({\n type: 'Rate Alert',\n message: `Average lease rate (${analysis.avg_lease_rate}) above $30/sqft`,\n priority: 'Medium'\n });\n}\n\n// Create dashboard summary\nconst dashboard = {\n generated_at: new Date().toISOString(),\n market_summary: {\n total_properties: analysis.total_listings,\n avg_lease_rate: `${analysis.avg_lease_rate}/sqft`,\n opportunities_found: analysis.opportunities.length,\n active_alerts: analysis.alerts.length\n },\n top_property_types: Object.entries(analysis.property_types)\n .sort(([,a], [,b]) => b - a)\n .slice(0, 5)\n .map(([type, count]) => ({ type, count })),\n top_locations: Object.entries(analysis.top_locations)\n .sort(([,a], [,b]) => b - a)\n .slice(0, 5)\n .map(([location, count]) => ({ location, count })),\n priority_opportunities: analysis.opportunities\n .sort((a, b) => a.rate - b.rate)\n .slice(0, 10),\n alerts: analysis.alerts,\n next_actions: [\n analysis.opportunities.length > 0 ? `Review ${analysis.opportunities.length} opportunities` : 'No immediate opportunities',\n analysis.alerts.length > 0 ? `Address ${analysis.alerts.length} alerts` : 'No alerts requiring action',\n 'Update market analysis tomorrow'\n ]\n};\n\nconsole.log(`CRE Analysis Complete: ${dashboard.market_summary.total_properties} properties, ${dashboard.market_summary.opportunities_found} opportunities`);\n\nreturn [{ json: dashboard }];"
},
"typeVersion": 2
},
{
"id": "422fb0a3-a654-4239-bcf4-3da927626df6",
"name": "\ud83d\udccb Decision Logic",
"type": "n8n-nodes-base.stickyNote",
"position": [
48,
144
],
"parameters": {
"color": 6,
"width": 400,
"height": 852,
"content": "# Opportunity Check \ud83c\udfaf\n\n**Smart Conditional Logic:**\n- Evaluates if opportunities were found\n- Only sends alerts when action needed\n- Prevents notification spam\n- Optimizes workflow efficiency\n\n**Decision Logic:**\n\u2705 Checks opportunities_found > 0\n\u2705 Routes to notification if true\n\u2705 Skips alerts if no opportunities\n\u2705 Always logs data regardless\n\n**Benefits:**\n\u2022 Reduces noise in communications\n\u2022 Focuses attention on actionable items\n\u2022 Saves API calls when not needed\n\u2022 Maintains clean notification history\n\n**Routing Logic:**\n\u2192 TRUE: Send Telegram alert with details\n\u2192 FALSE: Skip notification, continue logging\n\u2192 BOTH: Always log to Google Sheets\n\n**Configuration:**\n\u2022 Condition: opportunities_found > 0\n\u2022 Type: Number comparison\n\u2022 Case sensitive: True\n\u2022 Strict validation: Enabled"
},
"typeVersion": 1
},
{
"id": "9fcce7ef-60c1-422e-9e0c-de5f684d3bdb",
"name": "Check for Opportunities",
"type": "n8n-nodes-base.if",
"position": [
192,
848
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "has-opportunities",
"operator": {
"type": "number",
"operation": "gt"
},
"leftValue": "={{ $json.market_summary.opportunities_found }}",
"rightValue": 0
}
]
}
},
"typeVersion": 2
},
{
"id": "864ba85a-3b21-4bde-a6b2-686368436e6d",
"name": "\ud83d\udccb Telegram Setup",
"type": "n8n-nodes-base.stickyNote",
"position": [
448,
-176
],
"parameters": {
"color": 5,
"width": 400,
"height": 852,
"content": "# Send Opportunity Alert \ud83d\udcf1\n\n**Instant Telegram Notifications:**\n- Sends formatted CRE daily report\n- Includes market summary & top opportunities\n- Only triggers when opportunities exist\n- Professional message formatting\n\n**Message Content:**\n\u2705 Market summary with key metrics\n\u2705 Total properties analyzed\n\u2705 Average lease rate\n\u2705 Top 3 opportunities with details\n\u2705 Alert summary\n\n**Setup Requirements:**\n\u2022 Telegram Bot Token (from @BotFather)\n\u2022 Chat ID (your Telegram user/group ID)\n\u2022 Bot must be added to chat\n\u2022 Proper permissions configured\n\n**Message Format:**\n\ud83c\udfe2 **CRE Daily Report**\n\ud83d\udcca Market metrics\n\ud83c\udfaf Top opportunities\n\u26a0\ufe0f Active alerts\n\n**Benefits:**\n\u2192 Immediate awareness of opportunities\n\u2192 Mobile-friendly notifications\n\u2192 Formatted for quick reading\n\u2192 Historical message log"
},
"typeVersion": 1
},
{
"id": "b4b5cccf-a7da-403f-a7fc-13226b929040",
"name": "Send Opportunity Alert",
"type": "n8n-nodes-base.telegram",
"position": [
608,
544
],
"parameters": {
"operation": "send"
},
"typeVersion": 1.2
},
{
"id": "4ce23013-8b82-439a-8e33-89291516078c",
"name": "\ud83d\udccb Data Logging",
"type": "n8n-nodes-base.stickyNote",
"position": [
448,
672
],
"parameters": {
"color": 7,
"width": 400,
"height": 916,
"content": "# Log to Google Sheets \ud83d\udcc8\n\n**Historical Data Tracking:**\n- Automatically logs daily CRE metrics\n- Builds historical trend database\n- Enables long-term market analysis\n- Creates data foundation for reporting\n\n**Logged Metrics:**\n\u2705 Date (YYYY-MM-DD format)\n\u2705 Total properties analyzed\n\u2705 Average lease rate\n\u2705 Opportunities count\n\u2705 Top location\n\u2705 Alert count\n\n**Setup Requirements:**\n\u2022 Google Sheets document ID\n\u2022 Sheet name: 'CRE_Analysis'\n\u2022 Service account authentication\n\u2022 Proper column headers\n\n**Benefits:**\n\u2022 Track market trends over time\n\u2022 Identify seasonal patterns\n\u2022 Monitor alert frequency\n\u2022 Export data for analysis\n\u2022 Historical performance review\n\n**Data Structure:**\n\u2192 One row per day\n\u2192 Standardized column mapping\n\u2192 Automatic date stamping\n\u2192 Consistent data format"
},
"typeVersion": 1
},
{
"id": "501df296-9ece-4f93-ac15-d6b753c10813",
"name": "Log to Google Sheets",
"type": "n8n-nodes-base.googleSheets",
"position": [
576,
1456
],
"parameters": {
"resource": "spreadsheet",
"operation": "appendOrUpdate"
},
"typeVersion": 4.4
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "3d0f65de-749a-42e4-bbfc-b7073454c025",
"connections": {
"Daily CRE Scanner": {
"main": [
[
{
"node": "CRE Data Collector",
"type": "main",
"index": 0
}
]
]
},
"CRE Data Collector": {
"main": [
[
{
"node": "CRE Analyzer & Dashboard",
"type": "main",
"index": 0
}
]
]
},
"Check for Opportunities": {
"main": [
[
{
"node": "Send Opportunity Alert",
"type": "main",
"index": 0
}
]
]
},
"CRE Analyzer & Dashboard": {
"main": [
[
{
"node": "Check for Opportunities",
"type": "main",
"index": 0
},
{
"node": "Log to Google Sheets",
"type": "main",
"index": 0
}
]
]
}
}
}
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About this workflow
This workflow automatically scrapes commercial real estate listings from LoopNet and sends opportunity alerts to Telegram while logging data to Google Sheets. Scheduled Trigger - Runs every 24 hours to collect fresh CRE market data AI-Powered Scraping - Uses ScrapeGraphAI to…
Source: https://n8n.io/workflows/6625/ — original creator credit. Request a take-down →
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