TripAdvisor Scraper

TripAdvisor Scraper by Omkar Cloud gets you 🎯 accurate, 🔍 detailed TripAdvisor data.

TripAdvisor Scraper is scraped live on every run — no proxies, no selectors, no data cleaning — so you get the data, and can successfully complete your project.

$1 per 1,000 places. And with Apify's free plan you get $5 of credit every month, so your first ~5,000 places each month are free.

This is an excellent Actor made by Omkar Cloud, which is Rated Excellent — 4.7 based on 30 reviews on Trustpilot.

👉 Try TripAdvisor Scraper free — your first ~5,000 places are Free.

What can I get

• 🏨 Every hotel, restaurant & attraction in a city — 30 per page, as many pages as TripAdvisor lists
• ⭐ Ratings, rankings & awards — "#12 of 543 hotels in New York", Travelers' Choice, hotel class
• 💵 Live prices — nightly price range and booking offers for your dates
• 📞 Contacts, in full-detail mode — phone, email, website plus emails & socials found on the website

Why TripAdvisor Scraper

Most other scrapers fail you in one of four ways:

• 🗄️ Inaccurate, cached, stale data
• 🧩 Low-detail data — a few fields per row, never the full picture
• 💸 Pay more to get the same data
• 🪦 Works today, breaks next month — nobody maintains it

TripAdvisor Scraper is scraped live on every run, priced honestly, and actively maintained.

Example: One Row

{
  "place_type": "hotel",
  "location_input": "new york",
  "tripadvisor_entity_id": 11998087,
  "name": "Embassy Suites By Hilton New York Manhattan Times Square",
  "link": "https://www.tripadvisor.com/Hotel_Review-g60763-d11998087-Reviews-Embassy_Suites_By_Hilton_New_York_Manhattan_Times_Square-New_York_City_New_York.html",
  "rating": 4.3,
  "reviews": 3130,
  "ranking_current_rank": 139,
  "ranking_total": 779,
  "award_name": "Travelers Choice",
  "award_year": 2026,
  "hotel_class": 4,
  "price": 519,
  "address": "60 West 37th Street, New York City, NY 10018",
  "detailed_address_city": "New York City",
  "latitude": 40.75134,
  "longitude": -73.98582,
  "phone": "1 (855) 605-0319",
  "website": "https://www.tripadvisor.com/Commerce?p=TABAIndependentHotels&src=139925291&geo=11998087&from=Hotels&area=&slot=2&matchID=1&oos=0&cnt=1&silo=30356&bucket=899440&…",
  "featured_image": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/12/67/2e/ab/exterior.jpg",
  "subratings_location": 4.73,
  "subratings_cleanliness": 4.39,
  "rating_distribution_5": 2016,
  "rating_distribution_1": 192,
  "amenities_highlighted_amenities_property_amenities": [
    "Paid private parking on-site",
    "Free High Speed Internet (WiFi)"
  ]
}

Trimmed for readability. Every row is flat — each value is its own column, so CSV and Excel exports need no clean-up.

Get Started with 5,000 Free Places

1. Hit Try for Free Button — the input is pre-filled with New York hotels.
2. Enjoy your data 😎.

Pricing

High value, Low price.

What	Price	What you get
Standard places	$1 per 1,000	name, rating, reviews, ranking, address, price, photo, coordinates + city context
Detailed places	$2.50 per 1,000	Everything above + phone, email, website, emails & socials found on the website, amenities, AI review summary, rating breakdown, photos, FAQs

No start fee — you pay only for the rows you get. Control your spend with Max Places per City and Type: 1,000 places ≈ $1.

💡 Apify's free plan includes $5 of credit every month — about 5,000 free places or 2,000 fully-detailed places, every month.

👉 Scrape your first 5,000 places free

How to scrape TripAdvisor hotels, restaurants and attractions

1. Click Try for free.
2. Add Cities (new york, paris) and pick What to Scrape: hotels, restaurants and/or attractions. Or paste TripAdvisor Place URLs.
3. Optionally filter by minimum rating or Travelers' Choice award, and turn on Scrape Full Details for contacts, amenities and review summaries.
4. Click Start. Each place becomes one flat row.
5. Open the Output tab — switch between the Places, Hotels, Restaurants, Attractions and Contacts views — or export as JSON, CSV or Excel.

No proxies, no browser setup, no CAPTCHA solving.

Input

Field	What it does
Cities (locations)	Cities to scrape — each is scraped separately.
What to Scrape (placeTypes)	Hotels, restaurants and/or attractions for every city above.
Max Places per City and Type (maxResultsPerLocation)	Cap for each city × place type.
Scrape Full Details (scrapePlaceDetails)	Adds the full place page to every row: phone, email, website, emails & socials found on the website, amenities, AI review summary, rating breakdown, photos, FAQs and more.
Minimum Rating (minRating)	Only keep places rated at least this high (restaurants support 3+ only).
Awards (hotels & attractions) (awards)	Only keep Travelers' Choice winners.
Place URLs (startUrls)	Hotel_Review, Restaurant_Review and Attraction_Review URLs.
Currency (currency)	Currency for hotel and attraction prices, e.g.
Language & Country (locale)	Language–country TripAdvisor site to use.

Output

One flat row per place — 194 documented columns, no nested objects. The main ones:

Column	What it holds
featured_image	URL of the main photo.
name	Name of the place.
place_type	Kind of place: hotel, restaurant or attraction.
location_input	The city you entered that this row came from. City rows only.
rating	TripAdvisor rating, 1.0 to 5.0; null when the place has no reviews.
reviews	Number of TripAdvisor reviews.
award_name	Name of the TripAdvisor award the place holds, e.g. Travelers Choice; null when it has none.
address	Full address as one line.
phone	Phone number as shown on TripAdvisor.
link	TripAdvisor page URL of the place.
ranking_current_rank	Position of the place in its city ranking, 1 = best.
ranking_total	Number of places in that ranking.
hotel_class	Star class of the hotel, 1 to 5. Hotel rows only.
price	Lowest nightly price found, in the chosen currency. Hotel rows only.
price_range_min	Low end of the usual nightly price range. Hotel rows only.
price_range_max	High end of the usual nightly price range. Hotel rows only.
booking_offers_offer_provider_name	Booking site of the featured offer. Hotel rows only.
booking_offers_offer_booking_link	Link to book the featured offer. Hotel rows only.
cuisines	Cuisines the restaurant serves. Restaurant rows only.
price_range	Price level as TripAdvisor shows it, e.g. $$ - $$$. Hotel and restaurant rows only.
is_open_now	True when the place is open at scrape time. Restaurant and attraction rows only.
status_text	Opening status as TripAdvisor words it, e.g. Closed now. Restaurant rows only.
has_delivery	True when the restaurant offers delivery. Restaurant rows only.
has_reservation	True when the restaurant can be reserved online. Restaurant rows only.
menu_link	URL of the restaurant's menu. Restaurant rows only.
categories	Attraction categories, each with id and name. Attraction rows only.
neighborhood	Neighborhood the place is in. Restaurant and attraction rows only.
pricing_text	Ticket price as TripAdvisor words it; null when no tickets are sold. Attraction rows only.
commerce_tickets_link	Link to buy admission tickets; null when no tickets are sold. Attraction rows only.
experiences_count	Number of bookable experiences at the attraction. Attraction rows only.
description	Description of the place.
email	Contact email of the place.
website	Website of the place.
detailed_address_city	City.
detailed_address_country	Country.
latitude	Latitude of the place.
longitude	Longitude of the place.
website_contacts_emails	Emails found on the place's website, each with value, sources (pages it was found on) and is_likely_official. Detailed rows only.
website_contacts_phones	Phone numbers found on the place's website, each with value, sources and is_likely_official. Detailed rows only.
website_contacts_instagrams	Instagram links found on the place's website, each with value, sources and is_likely_official. Detailed rows only.
website_contacts_facebooks	Facebook links found on the place's website, each with value, sources and is_likely_official. Detailed rows only.

The Output tab shows this data as 5 ready-made views: Places, Hotels, Restaurants, Attractions, Contacts. Every column has a description and an example in the Actor's dataset schema.

Use cases

• Lead generation — build lists of hotels and restaurants with phone, email, website and the socials found on their sites.
• Hotel price monitoring — schedule a daily run and track nightly prices and booking offers in any city.
• Market research — rank every hotel, restaurant or attraction in a city by rating, reviews and award.
• Travel apps & content — fill a travel site with places, photos, coordinates, opening hours and descriptions.
• Competitor benchmarking — compare ratings, sub-ratings and rankings against the places next door.

Schedule it and connect it

Scraping once is useful. Scraping on a schedule is where the value is.

• ⏰ Schedule it — run TripAdvisor Scraper every hour, day or week from the Apify Schedules tab and track ratings, rankings and hotel prices over time.
• 🔗 Send the data anywhere — push results to Google Sheets, Slack, Airtable or your CRM with Make, Zapier or n8n, or call your own webhook the moment a run finishes.
• 🧑‍💻 Use the API — start runs and read results from any language. See Run It from Code.
• 🤖 Use it from AI agents — the Actor is available to Claude, ChatGPT and other agents through the Apify MCP server, so an agent can fetch TripAdvisor places for you on demand.
• 📥 Export — download any run as JSON, CSV, Excel, XML or an HTML table.

Run It from Code

Grab your API token from Integrations Settings here and replace <YOUR_API_TOKEN> below.

Python (pip install apify-client)

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("omkar-cloud/tripadvisor-scraper").call(run_input={"locations": ["paris"], "placeTypes": ["restaurants"], "maxResultsPerLocation": 50})
for place in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(place["name"], place["rating"], place["reviews"])

Node.js (npm install apify-client)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });
const run = await client.actor('omkar-cloud/tripadvisor-scraper').call({ locations: ['new york'], placeTypes: ['hotels'], scrapePlaceDetails: true });
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

FAQ

How much does it cost to scrape TripAdvisor?

$1 per 1,000 places, flat on every Apify plan, with no start fee. 10,000 places ≈ $10. Full-detail rows are $2.50 per 1,000. Apify's free plan gives you $5 of credit every month, about 5,000 places.

Do I need proxies or a TripAdvisor account?

No. Everything runs on our side — you just give the input.

How many places can I get per city?

As many as TripAdvisor lists, up to Max Places per City and Type (100,000 max). The Actor pages through the results for you.

Can I get phone numbers, emails and websites?

Yes. Turn on Scrape Full Details to get the phone, email and website of every place, plus the emails and social links found on its own website.

Do hotel rows include prices?

Yes. Hotel rows carry the lowest nightly price, the usual price range and the featured booking offer, in the Currency you choose.

What if an input is wrong?

It is skipped with a clear message in the log and never billed. If a full-detail page cannot be loaded, you keep the list row and pay only the standard rate for it.

Is the output nested JSON?

No. Every row is flat — detailed_address_city, ranking_current_rank, latitude — so CSV and Excel exports need no clean-up. Only real lists (photos, cuisines, opening hours) stay as arrays.

Can I scrape the reviews too?

Use TripAdvisor Reviews Scraper — every review of any hotel, restaurant or attraction, at $0.40 per 1,000 reviews.

Is it legal to scrape TripAdvisor?

The Actor collects only public data that any visitor can see without logging in. Review TripAdvisor's terms and make sure your use complies with the law of your jurisdiction, including data-protection law.

💬 Have Questions? We Have Answers.

You're a business owner — we know how hard completing a project can be. So we offer full support: just message us and we'll reply ✅ with a solution within 1 working day.

You are important to us — just message us and we will solve your problem ✅ within 1 working day. 🩷 Pinky Promise 🤙!

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👉 Scrape your first 5,000 places free now