Realtor.com Scraper for listing research
Keep Realtor.com listings ready for analysis
Move from a live search to a working property list without rebuilding it by hand.
Send listing data to your workspace
Collect visible addresses, prices, beds, baths, square footage, and property types, then move the table to Google Sheets, Airtable, Notion, Excel, or CSV.
Use one agent across property sites
Apply the same plain-English workflow to Realtor.com, brokerage sites, builder inventories, or local listing portals. There is no new selector system to learn for each source.
Refresh the same market on schedule
Save a Realtor.com search and rerun it on a schedule. Track visible price, status, open-house, and listing changes in a repeatable dataset instead of revisiting every home.
A live listing search should not become a copying task
Build a property table once, then return to the same market with a saved input.
Manual listing research
A spreadsheet that goes stale quicklyThunderbit market list
Reusable inputs and structured snapshotsWhat belongs in a Realtor.com listing table
Keep these 30 visible details when the selected search or property page provides them.
- Listing URL
- Street Address
- City
- State
- ZIP Code
- List Price
- Property Type
- Listing Status
- Bedrooms
- Bathrooms
- Living Area
- Lot Size
- Price Per Square Foot
- Year Built
- New Construction Badge
- Listed Date
- Open House Date
- Open House Time
- HOA Fee
- Parking Details
- MLS ID
- Listing Agent
- Brokerage
- Agent Contact
- Property Description
- Key Features
- Photo Count
- Primary Image URL
- Virtual Tour URL
- Captured At
Real users explain their Thunderbit workflows
Watch customers explain how they turn repeated browser research into clean tables and reusable workflows.
Realtor.com scraping questions
How searches, linked listings, schedules, and changing property information affect the table.
Compare the same market on more property sites
Add Redfin, Zillow, Trulia, brokerage, or builder pages to your research without changing the way you collect data.
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Learn more ->Ready to supercharge your data extraction?
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