📊 Aggregate commercial property listings with ScrapeGraphAI, Baserow and Teams

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Description

Property Listing Aggregator with Microsoft Teams and Baserow

⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template.

This workflow automatically aggregates commercial real-estate listings from multiple broker and marketplace websites, stores the fresh data in Baserow, and pushes weekly availability alerts to Microsoft Teams. Ideal for business owners searching for new retail or office space, it runs on a timetable, scrapes property details, de-duplicates existing entries, and notifies your team of only the newest opportunities.

Pre-conditions/Requirements

Prerequisites

An n8n instance (self-hosted or n8n.cloud)
ScrapeGraphAI community node installed
A Baserow workspace & table prepared to store property data
A Microsoft Teams channel with an incoming webhook URL
List of target real-estate URLs (CSV, JSON, or hard-coded array)

Required Credentials

ScrapeGraphAI API Key – Enables headless scraping of listing pages
Baserow Personal API Token – Grants create/read access to your property table
Microsoft Teams Webhook URL – Allows posting messages to your channel

Baserow Table Schema

Column Name	Type	Notes
`listing_id`	Text	Unique ID or URL slug (primary)
`title`	Text	Listing headline
`price`	Number	Monthly or annual rent
`sq_ft`	Number	Size in square feet
`location`	Text	City / neighborhood
`url`	URL	Original listing link
`scraped`	Date	Timestamp of last scrape

How it works

Key Steps:

Schedule Trigger: Fires every week (or on demand) to start the aggregation cycle.
Load URL List (Code node): Returns an array of listing or search-result URLs to be scraped.
Split In Batches: Processes URLs in manageable groups to avoid rate-limits.
ScrapeGraphAI: Extracts title, price, size, and location from each page.
Merge: Reassembles batches into a single dataset.
IF Node: Checks each listing against Baserow to detect new vs. existing entries.
Baserow: Inserts only brand-new listings into the table.
Set Node: Formats a concise Teams message with key details.
Microsoft Teams: Sends the alert to your designated channel.

Set up steps

Setup Time: 15-20 minutes

Install ScrapeGraphAI node:
In n8n, go to “Settings → Community Nodes”, search for “@n8n-nodes/scrapegraphai” and install.
Create Baserow table:
Follow the schema above. Copy your Personal API Token from Baserow profile settings.
Generate Teams webhook:
In Microsoft Teams, open channel → “Connectors” → “Incoming Webhook”, name it, and copy the URL.
Open the workflow in n8n and set the following credentials:
- ScrapeGraphAI API Key
- Baserow token (Baserow node)
- Teams webhook (Microsoft Teams node)
Define target URLs:
Edit the “Load URL List” Code node and add your marketplace or broker URLs.
Adjust schedule:
Double-click the “Schedule Trigger” and set the cron expression (default: weekly Monday 08:00).
Test-run the workflow manually to verify scraping and data insertion.
Activate the workflow once results look correct.

Node Descriptions

Core Workflow Nodes:

stickyNote – Provides inline documentation and reminders inside the canvas.
Schedule Trigger – Triggers the workflow on a weekly cron schedule.
Code – Holds an array of URLs and can implement dynamic logic (e.g., API calls to get URLs).
SplitInBatches – Splits URL list into configurable batch sizes (default: 5) to stay polite.
ScrapeGraphAI – Scrapes each URL and returns structured JSON for price, size, etc.
Merge – Combines batch outputs back into one array.
IF – Performs existence check against Baserow’s listing_id to prevent duplicates.
Baserow – Writes new records or updates existing ones.
Set – Builds a human-readable message string for Teams.
Microsoft Teams – Posts the summary into your channel.

Data Flow:

Schedule Trigger → Code → Split In Batches → ScrapeGraphAI → Merge → IF → Baserow
IF (new listings) → Set → Microsoft Teams

Customization Examples

Add additional data points (e.g., number of parking spaces)

// In ScrapeGraphAI "Selectors" field
{
  "title": ".listing-title",
  "price": ".price",
  "sq_ft": ".size",
  "parking": ".parking span"   // new selector
}

Change Teams message formatting

// In Set node
return items.map(item =&gt; {
  const l = item.json;
  item.json = {
    text: `🏢 *${l.title}* — ${l.price} USD\n📍 ${l.location} | ${l.sq_ft} ft²\n🔗 &lt;${l.url}|View Listing&gt;`
  };
  return item;
});

Data Output Format

The workflow outputs structured JSON data:

{
  "listing_id": "12345-main-street-suite-200",
  "title": "Downtown Office Space – Suite 200",
  "price": 4500,
  "sq_ft": 2300,
  "location": "Austin, TX",
  "url": "https://broker.com/listings/12345",
  "scraped": "2024-05-01T08:00:00.000Z"
}

Troubleshooting

Common Issues

ScrapeGraphAI returns empty fields – Update CSS selectors or switch to XPath; run in headless:true mode.
Duplicate records still appear – Ensure listing_id is truly unique (use URL slug) and that the IF node compares correctly.
Teams message not delivered – Verify webhook URL and that the Teams connector is enabled for the channel.

Performance Tips

Reduce batch size if websites block rapid requests.
Cache previous URLs to skip unchanged search-result pages.

Pro Tips:

Rotate proxies in ScrapeGraphAI for larger scraping volumes.
Use environment variables for credentials to simplify migrations.
Add a second Schedule Trigger for daily “hot deal” checks by duplicating the workflow and narrowing the URL list.

🔗 Nodes Used

Microsoft Teams, Baserow, Schedule Trigger

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup