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Ethan Teague
Ethan Teague

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How to Scrape Airbnb Listings and Prices in 2026 (No Code Required)

Heads-up: this post references a tool I built. It's a genuinely useful walkthrough either way — the technique applies to any Airbnb scraping project.

If you've ever tried to scrape Airbnb, you already know the two walls you hit: the pages are rendered by JavaScript, and Airbnb aggressively blocks datacenter IPs. Below is the reliable way to get clean Airbnb data in 2026 — listing prices, ratings, coordinates, and discounts — without running a headless browser or babysitting proxies.

The key insight: Airbnb ships its data in the HTML

You don't need to render the page. Every Airbnb search response embeds the full result set as JSON inside a <script id="data-deferred-state-0"> tag. Parse that and you get structured data straight away — no DOM scraping, no selectors that break on the next redesign.

The path to the results is:

niobeClientData[*][1].data.presentation.staysSearch.results
  ├── searchResults[]      // ~18 listings per page
  └── paginationInfo.pageCursors[]   // all page cursors, upfront
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Each listing carries a base64-encoded ID in demandStayListing.id (decode it, take the segment after the last colon, and you have the numeric listing ID for airbnb.com/rooms/<id>), a price line with discounts, avgRatingLocalized ("4.95 (123)"), and GPS coordinates.

The two gotchas

  1. Datacenter IPs get blocked. You need residential proxies. If a response comes back without the data-deferred-state marker, you've been served a bot check — rotate to a fresh IP and retry.
  2. ~270 result cap per search. Airbnb won't paginate past ~15 pages. To cover a whole market, split into narrower searches (by price band or neighborhood) and dedupe by listing ID.

The no-code way

If you'd rather not maintain proxy pools and parsers, I published an Airbnb Scraper on Apify that does exactly the above. Paste a location or a full Airbnb search URL (every filter is honored), and get flat JSON/CSV back.

curl -X POST "https://api.apify.com/v2/acts/ethanteague~airbnb-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"locations": ["Austin, Texas"], "checkIn": "2026-08-16", "checkOut": "2026-08-21", "maxListingsPerSearch": 180}'
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Example output per listing:

{
  "listingId": "1652957843916333450",
  "url": "https://www.airbnb.com/rooms/1652957843916333450",
  "name": "Stylish Pool Home 4BR Near Siesta Key",
  "rating": 5.0,
  "reviewsCount": 8,
  "badges": ["Guest favorite"],
  "priceLabel": "$3,190 for 5 nights",
  "latitude": 27.30754,
  "longitude": -82.52108
}
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It's pay-per-result ($4 per 1,000 listings), residential proxies included, and callable from Python/JS/Make/Zapier or as an AI-agent tool via MCP.

What you can build with this

  • Nightly price tracking across a market for revenue management
  • Supply/rating analysis by neighborhood (coordinates make it map-ready)
  • Discount hunting at scale
  • A data feed for an AI travel agent

Happy scraping. If you hit an edge case, drop it in the comments.

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