Trivago Hotel Deals Scraper - Every Booking Site's Price

Trivago Hotel Deals Scraper by ScraperCompany returns every deal trivago lists for a hotel and stay: Booking.com, Expedia, Hotels.com, Agoda, the hotel's own website and the rest. Each deal has the site, price per night, stay total, room name, meal plan, free cancellation and refundability, pay-at-property flag and link, plus the hotel's lead price, stars and location. Look hotels up by trivago id, URL or name, in any of trivago's 50+ country sites and currencies. Pricing is pay-per-event: $0.018 per hotel and stay; stays with no deals and failed requests are free.

Nothing to set up: no code, no login and no keys. Start a run, then export JSON, CSV or Excel, or pull the results through the Apify API. You pay only for results; failed and empty requests are free.

What can this trivago scraper do?

• Every partner's deal for one stay in one request, often hundreds of offers.
• Room, meal plan, free cancellation, refundable and pay-at-property on each deal.
• Lead price, total and price per night, plus stars, location and the trivago link.
• 50+ trivago markets and 36 currencies; hotels by id, URL or name.
• Exact or relative check-in dates (30 days), so saved tasks never go stale.

What makes it different?

	Trivago Hotel Deals Scraper	Many alternatives
Setup	Nothing to configure: no login, no keys	Often your own accounts, cookies or network setup
You pay for	Successful results; failed and empty requests are free	Often run time, or every attempt
When a site pushes back	Retried and handled for you	Often an empty or failed run

Who uses trivago data?

• Hotels and revenue managers: See every site selling your rooms for a date, and who undercuts your own website.
• Rate-parity monitoring: Compare OTA, wholesaler and direct prices for the same stay in one request.
• Travel analysts: Track how deals and partners differ across trivago's country sites.

What trivago data can you extract?

Field	Description
property.name / hotel_id / stars / location	Hotel identity
property.lead_price / price_per_night / total / currency	Cheapest deal and its stay total
offers[].provider	Booking site selling the deal
offers[].price_per_night / total	Deal price per night and for the stay
offers[].room_name / meal_plan	Room and board
offers[].refundable / free_cancellation_until / pay_at_property	Terms
offers[].link	Link to the deal

Every dataset item also carries input (the options used for that request), request_id (quote it to support), billed and scraped_at.

How to scrape trivago hotel deals

1. Open Trivago Hotel Deals Scraper in Apify Console and go to the Input tab.
2. Enter trivago hotel ids, URLs or hotel names (one per line; add a City for names), a check-in date, nights, adults and rooms. Optionally pick a market and currency.
3. Adjust the options if needed. Dates accept an exact date (2026-12-01) or a relative one (30 days from today), so saved tasks and schedules never go stale.
4. Click Start and wait for the run to finish.
5. Download the results from the Output tab as JSON, CSV, Excel or HTML, or fetch them with the Apify API.

Input

Input	Name	What it does
hotels	Hotels	One hotel per line: a trivago hotel id (12715), a trivago hotel URL, or a hotel name (add City below to pick the right one).
city	City	.g. Paris. Ignored for ids and URLs.
check_in	Check-in	Exact (2026-12-01) or relative (30 days from today).
nights	Nights	Length of stay (1-30).
adults	Adults	Guests in total (1-32).
rooms	Rooms	Rooms (1-8).
currency	Currency	Currency for prices. Leave empty for the market's own currency.
market	Market	The trivago country site to read (prices and partners differ by country).

Input example

This is the default input; running the Actor without changes uses it.

{
  "hotels": [
    "12715"
  ],
  "check_in": "30 days",
  "nights": 2,
  "includeErrors": true,
  "maxConcurrency": 3,
  "maxRetries": 2
}

Output example

One dataset item per request (trimmed here; real items contain all the fields):

{
  "input": {
    "hotel_id": "12715",
    "check_in": "2026-12-01",
    "nights": 2,
    "adults": 2
  },
  "meta": {
    "nights": 2,
    "notes": "`total` is the stay for every room with taxes and fees as the partner reported them to Trivago; `price` is the stay as Trivago shows it in this market (befor...",
    "observed_at": "2026-08-07T01:23:45.678Z",
    "offers": 105,
    "polls": 1,
    "providers": 8,
    "source": "trivago"
  },
  "offers": [
    {
      "attributes": [
        "Breakfast not included",
        "Non-refundable"
      ],
      "currency": "USD",
      "flags": [
        "ALTERNATIVE_DEAL",
        "MINIMUM_DEAL"
      ],
      "free_cancellation_until": null,
      "link": "https://www.trivago.com/forward/en-US?forwarderA=...",
      "meal_plan": "room_only",
      "pay_at_property": false,
      "price": 2423,
      "price_per_night": 1212,
      "provenance": {
        "observed_at": "2026-08-07T01:23:45.678Z",
        "price_basis": "stay_total_including_taxes_and_fees",
        "requested_currency": "USD",
        "requested_market": "US",
        "returned_currency": "USD",
        "schema_version": 1,
        "source": "trivago",
        "source_kind": "metasearch",
        "source_property_id": "12715"
      },
      "provider": "Stayforlong",
      "provider_id": 1912,
      "rate_category": "advance_purchase",
      "rate_category_source": "brand_flag",
      "rate_code": null,
      "rate_code_scope": null,
      "refundable": false,
      "room_category": "deluxe",
      "room_name": "Deluxe Room, Double Or Twin Bed - Room Only",
      "strikethrough_price": null,
      "total": 2908,
      "total_per_night": 1454
    },
    {
      "attributes": [
        "Breakfast not included",
        "Non-refundable"
      ],
      "currency": "USD",
      "flags": [],
      "free_cancellation_until": null,
      "link": "https://www.trivago.com/forward/en-US?forwarderA=...",
      "meal_plan": "room_only",
      "pay_at_property": false,
      "price": 2424,
      "price_per_night": 1212,
      "provenance": {
        "observed_at": "2026-08-07T01:23:45.678Z",
        "price_basis": "stay_total_including_taxes_and_fees",
        "requested_currency": "USD",
        "requested_market": "US",
        "returned_currency": "USD",
        "schema_version": 1,
        "source": "trivago",
        "source_kind": "metasearch",
        "source_property_id": "12715"
      },
      "provider": "Trip.com",
      "provider_id": 634,
      "rate_category": "advance_purchase",
      "rate_category_source": "brand_flag",
      "rate_code": null,
      "rate_code_scope": null,
      "refundable": false,
      "room_category": "deluxe",
      "room_name": "Deluxe King Room - (Check out before 12:00) - (Check in from 15:00)",
      "strikethrough_price": null,
      "total": 2909,
      "total_per_night": 1454
    }
  ],
  "property": {
    "availability": "available",
    "availability_reason": null,
    "complete": true,
    "currency": "USD",
    "hotel_id": 12715,
    "is_soldout": false,
    "lead_price": 2423,
    "location": "London, United Kingdom",
    "min_length_of_stay": null,
    "name": "The Savoy",
    "price_per_night": 1454,
    "provenance": {
      "observed_at": "2026-08-07T01:23:45.678Z",
      "price_basis": "stay_total_including_taxes_and_fees",
      "requested_currency": "USD",
      "requested_market": "US",
      "returned_currency": "USD",
      "schema_version": 1,
      "source": "trivago",
      "source_kind": "metasearch",
      "source_property_id": "12715"
    },
    "provider": "Stayforlong",
    "stars": 5,
    "total": 2908,
    "url": "https://www.trivago.com/en-US/oar/hotel-the-savoy-london?search=100-12715"
  },
  "search_parameters": {
    "adults": 2,
    "check_in_date": "2026-12-01",
    "check_out_date": "2026-12-03",
    "currency": "USD",
    "hotel_id": 12715,
    "market": "US",
    "nights": 2,
    "rooms": 1
  },
  "request_id": "req_3f9c0d6e2b8a4c1f9e7d5b3a1c0e8f6d",
  "billed": true,
  "scraped_at": "2026-10-01T14:03:27.512Z"
}

A request that fails is saved with an error message instead (turn off Include failed requests to skip those). Failed requests are never charged.

How much does it cost to scrape trivago hotel deals?

This Actor uses pay-per-event pricing: you pay for successful requests, not for compute time.

Event	Charged when	Price	Per 1,000
deals-request	One hotel priced for one stay: every booking site's deal trivago lists. Stays with no deals are free.	$0.018	$18.00

Paid Apify plans pay less: deals-request up to 9% off (Bronze 5%, more on higher plans). The Pricing tab shows the price on your plan.

What a real run costs:

• 100 requests: $1.80
• 1,000 requests: $18.00
• 10,000 requests: $180.00

Apify's $5 of free monthly usage covers about 277 deals-request events.

• Failed requests (errors, invalid input, a site refusing after retries) are free.
• Requests where the source returns nothing at all (no results, nothing priced) are saved but not charged.
• Set Maximum cost per run when you start a run and the Actor stops cleanly before going over it.

Run it on a schedule

Use Apify Schedules to repeat a run hourly, daily or weekly and compare results over time, and webhooks or the Integrations tab to push new results to Make, Zapier, n8n, Google Sheets, Slack or your own warehouse.

Use it with AI agents

Results are structured JSON, so they are easy to feed to a model. AI agents such as Claude can run this Actor and read its results through the Apify MCP server.

FAQ

Do I need an account on the site, or an API key?

No. The Actor is ready to run as is, and you only pay the per-event prices above.

How do I find a trivago hotel id?

Pass the hotel's trivago URL or its name with a city instead; the id is resolved for you and returned in property.hotel_id for next time.

Why are deals different between markets?

trivago shows different partners and prices on each country site. Set Market to the country your guests book from.

Is every deal bookable at that price?

Prices are what trivago shows for the stay at the time of the request; the final price is set on the booking site.

Is it legal to scrape trivago hotel deals?

The Actor collects publicly available information that anyone can see without logging in. You are responsible for how you use the results: respect the source site's terms, copyright and privacy law (such as GDPR) and do not collect personal data without a lawful basis. If in doubt, ask a lawyer.

What happens when a request is blocked or rate-limited?

Temporary errors are retried automatically. If a request still fails it is saved with the error message and not charged, and the rest of the batch keeps going. A run only fails when every request failed.

Why did a request return an error?

Read the error field: it says what was wrong with the input, for example a malformed date or an unknown id. Fix it and run again; failed requests cost nothing.

How many requests can I run at once?

Any number per run. The Actor sends up to 3 requests in parallel by default (change it under Run options); larger batches simply take longer.

Use it from your code

Call the Actor from any language through the Apify API. With the JavaScript client (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('scrapercompany/trivago-hotel-deals-scraper').call({
    "hotels": [
        "12715"
    ],
    "check_in": "30 days"
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

With Python (pip install apify-client):

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("scrapercompany/trivago-hotel-deals-scraper").call(run_input={
    "hotels": ["12715"],
    "check_in": "30 days",
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Related scrapers

• Hotel Price Comparison: Booking.com, Expedia and Agoda prices side by side
• Japan Hotel Rates: Rakuten Travel, Jalan, Ikyu and Yahoo! Travel prices

Support

Questions, a field you need, or a site that stopped working? Open an issue on the Issues tab. Include the request_id from the dataset item so we can trace the request.