Agoda Hotels Scraper

Extract Agoda hotel and accommodation listings in bulk and export them as clean, structured data. Give it a destination or paste Agoda search URLs, and get back one row per hotel — name, property type, address, city, country, coordinates, review score, review count, star rating, nightly price, currency, image and link — ready for spreadsheets, dashboards, databases and automation.

Perfect for travel price research, market and competitor analysis, revenue management, building hotel datasets, and feeding downstream automations.

Features

• 🔎 Search by destination — just type a city or place (e.g. Singapore, Bangkok, Bali).
• 🔗 Or paste Agoda search URLs — run the exact search you set up on the site, including your dates, guests and currency.
• 💰 Live nightly prices in the currency you choose (USD, EUR, GBP, SGD, THB and more).
• ⭐ Ratings & reviews — star rating, guest review score and total review count for each property.
• 📍 Location data — address, city, country and latitude/longitude for mapping.
• 🖼️ Images & direct links to each property.
• 📄 Automatic pagination across all result pages up to your chosen limit.
• 📊 Export anywhere — download as JSON, CSV, Excel or HTML, or pull via API.

What it does

This actor collects hotel listings from Agoda search results at scale. You can combine both input modes: paste one or more search URLs and add a destination — the actor scrapes them all, de-duplicates properties, and stops once it reaches your maximum.

Input

Example input

{
  "destination": "Bangkok",
  "checkIn": "2026-12-01",
  "checkOut": "2026-09-21",
  "adults": 2,
  "currency": "USD",
  "maxItems": 100
}

Or with pasted search URLs:

{
  "searchUrls": [
    "https://www.agoda.com/search?city=4064&checkIn=2026-12-01&los=1&rooms=1&adults=2"
  ],
  "currency": "SGD",
  "maxItems": 200
}

Output

Each hotel is one dataset record:

{
  "name": "Solaria Nishitetsu Hotel Bangkok",
  "type": "Hotel",
  "address": "Sukhumvit, Bangkok, Thailand",
  "city": "Bangkok",
  "country": "Thailand",
  "latitude": 13.7368,
  "longitude": 100.5602,
  "reviewScore": 9.2,
  "reviewCount": 17113,
  "starRating": 4,
  "price": 115.08,
  "currency": "USD",
  "url": "https://www.agoda.com/solaria-nishitetsu-hotel-bangkok/hotel/bangkok-th.html",
  "image": "https://pix8.agoda.net/hotelImages/14654101/-1/3cdaadf72911866b34b1a97eae8f92dd.jpg"
}

You can export the whole dataset as JSON, CSV, Excel or HTML from the run's Storage tab, or fetch it through the Apify API.

Use cases

• Price monitoring — track nightly rates for a destination over time.
• Competitor & market research — compare hotels, ratings and prices across a city.
• Revenue management — benchmark your property against the local set.
• Travel apps & content — build hotel datasets for maps, guides and comparison tools.
• Lead lists — collect properties in a region with contact-ready location data.

Using it with n8n and Make

The dataset works cleanly with no-code automation platforms.

FAQ — n8n

• Can I run this from n8n? Yes. Use the Apify node (or an HTTP Request node) to start the actor, then read the dataset items in the next step.
• How do I get the results into n8n? After the run finishes, call the dataset items endpoint — each hotel comes back as a flat JSON object you can map straight onto a spreadsheet, database or CRM node.
• Can I schedule it? Yes — schedule the actor on Apify, or trigger it on a cron from n8n or Make, and process new results each run.

Tips

• For accurate prices, set checkIn and checkOut (or use a URL that already includes dates).
• Choose your currency so prices are directly comparable.
• Set maxItems to control run size and cost; use 0 only when you want everything.

Notes

Original clean-room implementation. This actor is not affiliated with, authorized or endorsed by Agoda. Scrape responsibly and use the data in line with applicable laws and terms.

You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.