Tripadvisor Hotel Prices Scraper

Tripadvisor Hotel Prices Scraper reads the price comparison Tripadvisor shows for a hotel: each booking site's offer for your dates, with its price before taxes, the all-in total and the provider name. It is a quick way to see the market for a stay across OTAs in one request, in any of 30 currencies. A search mode finds a hotel's Tripadvisor location id from its name.

Powered by the ScraperCompany API: requests, proxies, retries and anti-bot handling run on ScraperCompany's servers, so you don't need your own proxies or API key. Start a run, get structured JSON.

What can this scraper do?

• Every provider's offer for a stay: Booking.com, Expedia, Hotels.com, Agoda, the official site and others.
• Before-tax price and all-in total per offer, with the price exactly as Tripadvisor displays it.
• Exact dates guaranteed: offers priced for any stay other than the one you asked for are rejected, never returned.
• 30 currencies, any stay length, adults and rooms.
• Find location id for a hotel name or place.
• Batch many hotels in one run.

Modes

Mode	What it returns	Price per request
rates	Each booking site's price for one stay as listed on Tripadvisor	$0.012
search	Tripadvisor location id for a hotel name or place	$0.002

What data can you extract?

Field	Description
offers[].provider_name	Booking site
offers[].price / price_is	Headline price before taxes, and whether it is per night or for the whole stay
offers[].nightly / total	Nightly price before taxes, all-in stay total
offers[].price_text / total_text / currency	Prices as displayed, currency
property.price_per_night / lead_price	Lowest nightly price before taxes, lowest headline price
meta.offers	Number of offers
matches[] / recommended_match	Location ids, titles and places (Find location id mode)

Every dataset item also carries input (the exact request that was sent), request_id (quote it to support), billed and scraped_at.

How to use Tripadvisor Hotel Prices Scraper

1. Open Tripadvisor Hotel Prices Scraper in Apify Console and go to the Input tab.
2. Enter Tripadvisor location ids (the number after -d in a hotel URL) and a check-in date, or use Find location id mode with hotel names.
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 example

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

{
  "mode": "rates",
  "locationIds": [
    "17768161"
  ],
  "check_in": "30 days",
  "nights": 2,
  "currency": "USD",
  "searchQueries": [
    "Moxy Boston Downtown"
  ],
  "city": "Boston",
  "includeErrors": true,
  "maxConcurrency": 3,
  "maxRetries": 2
}

Output example

One dataset item per request (trimmed here; real items contain every field the API returns):

{
  "mode": "rates",
  "endpoint": "/v1/ota/tripadvisor",
  "input": {
    "location_id": "17768161",
    "check_in": "2026-10-27",
    "nights": 4,
    "currency": "USD"
  },
  "meta": {
    "collection_id": "ratecol_0123456789abcdef0123456789abcdef",
    "egress_mode": "direct",
    "elapsed_s": 5.836,
    "nights": 4,
    "observed_at": "2026-08-07T01:23:45.678Z",
    "offers": 11,
    "polls": 6,
    "source": "tripadvisor",
    "warnings": [],
    "wire_bytes": 172675
  },
  "offers": [
    {
      "check_in": "2026-10-27",
      "check_out": "2026-10-31",
      "currency": "USD",
      "is_member_rate": false,
      "location_id": "17768161",
      "nightly": 425,
      "nightly_derived": true,
      "offer_type": "chevron",
      "price": 1700,
      "price_currency": "USD",
      "price_is": "stay",
      "price_text": "$1,700",
      "price_value": 1700,
      "pricing_mode": "BASE_PLUS_FEES_FULL_STAY",
      "provenance": {
        "collection_id": "ratecol_0123456789abcdef0123456789abcdef",
        "collector": "scrapingme.ota.tripadvisor",
        "derivation": "parsed_display_price",
        "egress_mode": "direct",
        "observation_id": "rateobs_0123456789abcdef0123456789abcdef",
        "observed_at": "2026-08-07T01:23:45.678Z",
        "price_basis": "stay_before_taxes_including_fees",
        "requested_currency": "USD",
        "requested_market": null,
        "returned_currency": "USD",
        "schema_version": 1,
        "source": "tripadvisor",
        "source_kind": "metasearch",
        "source_property_id": "17768161",
        "upstream_rate_id": null
      },
      "provider": "Booking.com",
      "provider_name": "Booking.com",
      "room_plan": "",
      "taxes_included": false,
      "total": 1980,
      "total_text": "$1,980"
    }
  ],
  "property": {
    "complete": true,
    "currency": "USD",
    "currency_verified": true,
    "hotel_id": "17768161",
    "lead_price": 1348,
    "lead_price_is": "stay",
    "location_id": "17768161",
    "price_per_night": 337,
    "pricing_mode": "BASE_PLUS_FEES_FULL_STAY",
    "provenance": {
      "collection_id": "ratecol_0123456789abcdef0123456789abcdef",
      "collector": "scrapingme.ota.tripadvisor",
      "derivation": "stay_price_divided_by_nights",
      "egress_mode": "direct",
      "observation_id": "rateobs_0123456789abcdef0123456789abcdef",
      "observed_at": "2026-08-07T01:23:45.678Z",
      "price_basis": "nightly_before_taxes_including_fees",
      "requested_currency": "USD",
      "requested_market": null,
      "returned_currency": "USD",
      "schema_version": 1,
      "source": "tripadvisor",
      "source_kind": "metasearch",
      "source_property_id": "17768161",
      "upstream_rate_id": null
    },
    "requested_currency": "USD",
    "total": 1348
  },
  "search_parameters": {
    "adults": 2,
    "check_in_date": "2026-10-27",
    "check_out_date": "2026-10-31",
    "currency": "USD",
    "engine": "tripadvisor_property",
    "location_id": "17768161",
    "nights": 4,
    "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?

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

Event	Charged when	Price	Per 1,000
rates-request	One hotel priced for one stay: every booking site's offer shown on Tripadvisor.	$0.012	$12.00
search-request	One hotel or place looked up on Tripadvisor (returns its location id).	$0.002	$2.00

For example, 1,000 requests in the default mode cost $12.00.

• Failed requests (errors, invalid input, blocked upstream 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.

FAQ

Do I need proxies or a ScraperCompany API key?

No. Proxy rotation, retries and anti-bot handling run on the ScraperCompany side, and the Actor is already connected to the API. You only pay the per-event prices above.

Where is the Tripadvisor location id?

In the hotel URL: https://www.tripadvisor.com/Hotel_Review-g60745-d17768161-Reviews-... has location id 17768161. Or run Find location id mode.

Can I get Tripadvisor reviews too?

Yes, with the Hotel Reviews Scraper (source: Tripadvisor).

Is it legal to scrape this data?

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?

Rate limits (HTTP 429) and temporary errors (5xx) are retried automatically with exponential backoff, respecting Retry-After. 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: validation problems (for example a malformed date or an unknown id) are reported exactly as the API sees them. Fix the input 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/tripadvisor-hotel-rates-scraper').call({
    "mode": "rates",
    "locationIds": [
        "17768161"
    ],
    "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/tripadvisor-hotel-rates-scraper").call(run_input={
    "mode": "rates",
    "locationIds": ["17768161"],
    "check_in": "30 days",
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

You can also schedule runs, chain them with webhooks, or connect them to Make, Zapier, n8n, Google Sheets and other integrations from the Integrations tab.

Related scrapers

• Hotel Reviews Scraper
• Hotel Price Comparison

Support

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