Trip.com Scraper — Hotels, Attractions, Trains & Cruises ✈️

🎉 The ONLY Trip.com scraper that covers Hotels, Attractions, Trains AND Cruises — in one actor

One vertical dropdown, one clean dataset. The complete Trip.com / Ctrip travel-data toolkit for analysts, agencies, and travel-tech builders.

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📋 Overview

Pull travel data from Trip.com across four categories with a single tool — hotels, things-to-do, China rail, and cruises, all from one Apify actor and exported as one tidy dataset.

Most Trip.com tools on the market do one thing: a hotels-only scraper here, a reviews-only scraper there. This actor is different — it is the only Trip.com scraper covering four verticals at once, so you stop juggling five separate tools and APIs to research a single destination.

Why thousands of travel professionals choose us:

• ✅ 4 verticals, 1 actor: Hotels, Attractions, Trains, and Cruises — no other Trip.com scraper does all four
• ⚡ Richer rows than the competition: hotel detail mode returns rooms, the full photo album, a reviews sample, and nearby points of interest — all in a single row
• 🎯 93–95% hotel field coverage: prices, star ratings, review sub-scores, WGS84 coordinates, address + zones, photos and video
• 💰 Free tier + pay-per-result: try it for free, then only pay for the data you successfully receive
• 💎 Built for China travel: native China rail timetables with seat-class fares, plus international hotels, attractions and cruises
• ✨ NEW: pasted-URL mode — apply Trip.com's own star, price and district filters by copying any search URL

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✨ Features

• 🏨 Hotel Search: name, star rating, live price + currency, struck-through price, lead room, review score and count, sub-scores, coordinates, address, photos and video
• 🔍 Hotel Detail Mode: a reviews sample, the full ~130-image photo album, ~30 nearby attractions, and reservation/policy notes — all in one row
• 🎡 Attractions & Things-to-Do: tickets, tours and sightseeing spots with price, rating, review count, category, plus address, opening hours and coordinates for points of interest
• 🚄 China Rail Timetables: every train for a route and date — train number, stations, times, duration, high-speed flag, and seat classes with fares and live ticket availability
• 🛳️ Featured Cruises: a curated set of featured sailings with ship, itinerary, departure city, sailing date and price
• 🎚️ Native Filters: paste any Trip.com search URL to carry over its star, price-band and district filters
• 🌍 WGS84 Coordinates: map-ready latitude/longitude for hotels, sightseeing spots and rail stations
• 📦 One Unified Dataset: a single vertical field labels every row, so mixed exports stay clean
• 💱 Currency & Locale Control: choose your output currency and language

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🎬 Quick Start

Pick a vertical, give it a city (and dates for hotels), and run. Results stream into the Apify dataset as JSON you can export to CSV or Excel. Start on the free tier — no credit card required.

curl -X POST https://api.apify.com/v2/acts/sian.agency~trip-com-scraper/runs?token=YOUR_TOKEN \
-H 'Content-Type: application/json' \
-d '{"vertical": "hotels", "hotelCityId": "2", "hotelCityName": "Shanghai", "maxResults": 20}'

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🚀 Getting Started (3 Simple Steps)

Step 1: Choose your vertical

Select Hotels, Attractions, Trains, or Cruises from the dropdown.

Step 2: Tell it where

Enter a city (hotels: city + check-in/check-out dates; attractions: city keyword; trains: from + to + date) — or paste a Trip.com search URL to reuse its filters.

Step 3: Run and export

Click Start and watch results fill the dataset. Download as JSON, CSV, or Excel.

That's it! In a couple of minutes, you'll have:

• A clean, structured dataset of Trip.com travel data
• Map-ready coordinates and rich per-row detail
• Export-ready files for your spreadsheet, database or BI tool

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📥 Input Configuration

Field	Type	Required	Description
vertical	string	Yes	hotels, attractions, trains, or cruises
maxResults	number	No	Cap how many rows to collect
currency	string	No	Output currency (e.g. USD, CNY)
locale	string	No	Output language (e.g. en-US)
hotelCityId	string	Hotels	Trip.com city ID (e.g. 2 = Shanghai)
hotelCityName	string	Hotels	City display name
checkin / checkout	string	Hotels	Stay dates (YYYY-MM-DD)
enableDetail	boolean	No	Hotels: also fetch rooms, full album, reviews and nearby POIs
searchUrl	string	No	Paste a Trip.com search URL to reuse its star/price/district filters

Hotels example:

{
  "vertical": "hotels",
  "hotelCityId": "2",
  "hotelCityName": "Shanghai",
  "checkin": "2026-07-10",
  "checkout": "2026-07-11",
  "enableDetail": true,
  "maxResults": 25
}

Trains example (China rail):

{
  "vertical": "trains",
  "from": "Shanghai",
  "to": "Beijing",
  "date": "2026-07-10"
}

Attractions example:

{
  "vertical": "attractions",
  "cityKeyword": "Tokyo"
}

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📤 Output

Every row carries a vertical discriminator field so all four categories merge into one clean dataset. Headline fields by vertical:

Hotels

Field	Type	Description
name / name_en	string	Hotel name
star	number	Star rating
price / currency	number / string	Live price + currency
display_price / delete_price	string	Shown price + struck-through price
comment_score / comment_count	number	Review score + count
sub_scores	object	Cleanliness, location, service sub-ratings
address / zone_names	string / array	Address and district zones
lat / lng	number	WGS84 coordinates
photos / video_url	array / string	Imagery
album_photos / reviews / nearby_pois	array	Detail mode only

Attractions: name, price, original_price, comment_score, comment_count, category, plus address, open_time, description, lat, lng for sightseeing spots.

Trains: train_numbers, departure_station, arrival_station (+ local names + coordinates), departure_time, arrival_time, duration_display, has_high_speed, is_direct, and fares (seat classes with price and ticket availability).

Cruises: name, ship_name, company_name, departure_city, start_date, nights, price, currency.

Example (hotel row):

{
  "vertical": "hotels",
  "id": "1234567",
  "url": "https://www.trip.com/hotels/detail/?hotelId=1234567",
  "name": "The Bund Riverside Hotel",
  "star": 5,
  "price": 180,
  "currency": "USD",
  "display_price": "$180",
  "delete_price": "$240",
  "comment_score": 4.7,
  "comment_count": 2310,
  "sub_scores": { "location": 4.8, "cleanliness": 4.7, "service": 4.6 },
  "address": "No. 99 Zhongshan East Road, Huangpu",
  "zone_names": ["The Bund"],
  "lat": 31.2401,
  "lng": 121.4905,
  "photos": ["https://..."]
}

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💼 Use Cases & Examples

1. Hotel Rate & Competitor Intelligence

Revenue managers and OTAs tracking how rival hotels price the same dates.

Input: vertical hotels, a city + check-in/check-out Output: live prices, struck-through rates, star ratings and review scores Use: benchmark your property against the comp set and time your rate changes.

2. Destination Market Research

Travel-tech startups and analysts mapping a city's full travel supply.

Input: run all four verticals for the same city Output: hotels, attractions, trains and cruises in one merged dataset Use: build a complete destination supply picture without stitching five tools together.

3. China Rail Planning & Fare Monitoring

Travel agencies and mobility apps surfacing China high-speed rail options.

Input: vertical trains, origin → destination → date Output: every train with seat-class fares and live ticket availability Use: power a rail-search feature or watch fares and availability over time.

4. Things-to-Do Content & Affiliate Catalogs

Content creators and affiliate marketers building city activity guides.

Input: vertical attractions, a city keyword Output: ~144 tours and sightseeing spots with prices, ratings, hours and descriptions Use: populate a "Top things to do in Tokyo" page or affiliate feed.

5. Hotel Listing Enrichment

Data teams that need deep, structured hotel profiles, not just a price.

Input: vertical hotels with detail mode on Output: the full ~130-image album, a reviews sample and nearby POIs — per hotel Use: enrich a property database or train a recommendation model.

6. Cruise Deal Discovery

Cruise resellers and deal sites curating featured sailings.

Input: vertical cruises Output: a curated set of featured sailings across multiple cruise lines with itinerary and price Use: seed a "featured cruises" page or monitor promoted departures.

7. Location & Mapping Datasets

GIS and proptech teams that need map-ready travel POIs.

Input: hotels or attractions in any city Output: WGS84 coordinates plus address and zone metadata Use: plot supply on a map or join against your own geospatial layers.

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🔗 Integration Examples

JavaScript/Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });

const run = await client.actor('sian.agency/trip-com-scraper').call({
  vertical: 'hotels',
  hotelCityId: '2',
  hotelCityName: 'Shanghai',
  maxResults: 20,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')

run = client.actor('sian.agency/trip-com-scraper').call(
    run_input={
        'vertical': 'attractions',
        'cityKeyword': 'Tokyo',
    }
)

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

cURL

curl -X POST 'https://api.apify.com/v2/acts/sian.agency~trip-com-scraper/runs?token=YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-d '{"vertical": "trains", "from": "Shanghai", "to": "Beijing", "date": "2026-07-10"}'

Automation Workflows (N8N / Zapier / Make)

1. Trigger: Schedule or webhook
2. HTTP Request: Call the actor API
3. Process: Handle the JSON results
4. Action: Save to a database, notify a channel, or transform for BI

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📊 Performance & Pricing

FREE Tier (Try It Now)

• A generous sample of rows per run — full feature access, same data quality
• No credit card required
• Perfect for testing and small projects

PAID Tier (Production Ready)

• Unlimited rows per run across all four verticals
• Pay-per-event: you're only charged for the data you successfully receive
• Hotel detail enrichment available for deep, structured profiles

💰 Outstanding value — competing hotel-only scrapers charge per item for a single vertical; here you get four verticals plus richer per-row detail (rooms + full album + reviews + nearby in one hotel row) under one pay-per-result actor.

🔗 View current pricing

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❓ Frequently Asked Questions

Q: Which travel categories does it cover? A: Four — Hotels, Attractions / things-to-do, China Trains, and Cruises — all from one actor, selected by a dropdown.

Q: How many results can I get? A: FREE tier returns a sample per run; PAID tier is unlimited.

Q: How complete is the hotel data? A: Around 93–95% field coverage on hotels — prices, ratings, review sub-scores, coordinates, address, photos and video.

Q: Does the cruises vertical return every cruise? A: No — cruises returns a curated set of featured sailings, not the full cruise catalogue. Hotels, attractions and trains return full results for your search.

Q: What output formats are available? A: JSON, CSV, and Excel — export directly from the Apify dataset.

Q: Can I apply Trip.com's own filters (star, price, district)? A: Yes — paste a Trip.com search URL and the actor reuses its filters.

Q: Is this legal? A: Yes — we only extract publicly available data. See the legal section below.

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🐛 Troubleshooting

No results returned

• Double-check the city ID / city name, or paste a working Trip.com search URL
• For trains, confirm the route and date have scheduled service

Hotel detail fields are empty

• Enable detail mode (enableDetail: true) to fetch rooms, the full album, reviews and nearby POIs

Fewer rows than expected

• The FREE tier returns a sample — upgrade to PAID for unlimited rows
• Cruises always returns a curated featured set, not the full catalogue

Prices look off

• Set the currency and locale inputs to your preferred output

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⚖️ Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Trademark notice: Trip.com and Ctrip are trademarks of Trip.com Group Limited. This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Trip.com Group Limited.

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🤝 Support

Join our active support community

• For issues or questions, open an issue in the actor's repository
• Check the SIÁN Agency Store for more automation tools
• 📧 apify@sian-agency.online

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