🌍 TripAdvisor Reviews Scraper — Hotels, Restaurants & Attraction Reviews Extractor

Scrape TripAdvisor reviews, ratings, venue metadata, and traveler insights without an API key. This actor extracts structured review data from any TripAdvisor listing — hotels, restaurants, vacation rentals, attractions, and experiences — and exports it to JSON or CSV in seconds.

No TripAdvisor API required. Works on any public TripAdvisor listing.

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🚀 What It Does

The TripAdvisor Reviews Scraper is a high-performance extractor built for hospitality professionals, travel tech companies, and market researchers who need bulk access to TripAdvisor review data. It captures full review text, star ratings, reviewer profiles, trip types (business, family, solo), dates, and venue-level metadata — all structured and ready for analysis. Supports multilingual reviews and handles venues with tens of thousands of reviews through robust pagination. Export to JSON, CSV, Excel, or XML via Apify datasets.

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🎯 Use Cases

• 🏨 Hotel & Resort Managers — Aggregate guest feedback at scale to identify recurring complaints, praise patterns, and competitive positioning
• 📊 Travel Market Researchers — Build datasets of hospitality sentiment for trend analysis, pricing research, and destination popularity studies
• 🤖 NLP & AI Teams — Collect labeled review data (star-rated, categorized by trip type) for sentiment analysis, review summarization, and recommendation model training
• 🏢 Tourism Boards & DMOs — Monitor traveler perception of local attractions, restaurants, and accommodations across entire destinations
• 💼 Consulting & Strategy Firms — Perform competitive benchmarking by scraping reviews of rival properties and comparing sentiment scores
• 📱 Travel App Developers — Enrich your travel app with real review data for hotels and restaurants in target markets

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📥 Input Parameters

Field	Type	Default	Description
urls	array	required	List of TripAdvisor venue URLs (hotel, restaurant, or attraction pages)
maxReviews	integer	50	Maximum reviews to scrape per venue (1–500)
language	string	"en"	Filter reviews by language code (e.g., "en", "fr", "de", "es", "it")
includeVenueInfo	boolean	true	Whether to include venue metadata (name, address, overall rating, etc.)
sortBy	string	"recent"	Sort reviews by: "recent", "relevance", "highest_rating", "lowest_rating"
proxyConfiguration	object	auto	Proxy settings. Residential proxies strongly recommended

📋 Example Input

{
  "urls": [
    "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Plaza-New_York_City_New_York.html",
    "https://www.tripadvisor.com/Restaurant_Review-g60763-d493221-Reviews-Nobu_57-New_York_City_New_York.html"
  ],
  "maxReviews": 200,
  "language": "en",
  "includeVenueInfo": true,
  "sortBy": "recent",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

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📤 Output Sample

Each item in the output dataset represents one review with its associated venue info:

{
  "venueInfo": {
    "venueId": "d93589",
    "name": "The Plaza",
    "type": "hotel",
    "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Plaza-New_York_City_New_York.html",
    "overallRating": 4.5,
    "reviewCount": 8241,
    "address": {
      "street": "Fifth Avenue At Central Park South",
      "city": "New York City",
      "state": "New York",
      "country": "United States",
      "postalCode": "10019"
    },
    "amenities": ["Free WiFi", "Pool", "Spa", "Restaurant", "Room Service", "Fitness Center"],
    "priceRange": "$$$$",
    "hotelClass": 5,
    "rankInCity": 42,
    "rankOutOf": 512
  },
  "review": {
    "reviewId": "rv_921843021",
    "title": "Iconic luxury — worth every penny for a special occasion",
    "text": "We celebrated our anniversary at The Plaza and it exceeded every expectation. The room was immaculate, the staff went above and beyond, and the location simply cannot be beat. Afternoon tea in the Palm Court was a highlight. Will definitely be back.",
    "rating": 5,
    "date": "2024-03-10",
    "publishedAt": "2024-03-12T08:30:00.000Z",
    "tripType": "Couples",
    "stayDate": "March 2024",
    "author": {
      "username": "TravellerMaria_NYC",
      "profileUrl": "https://www.tripadvisor.com/Profile/TravellerMaria_NYC",
      "contributionCount": 47,
      "helpfulVotes": 23,
      "level": "Senior Contributor",
      "homeLocation": "London, United Kingdom"
    },
    "helpful": 12,
    "language": "en",
    "managementResponse": {
      "text": "Dear Maria, thank you so much for this wonderful review! We are thrilled you enjoyed your anniversary celebration with us...",
      "date": "2024-03-13",
      "author": "General Manager, The Plaza"
    }
  },
  "scrapedAt": "2024-03-16T09:00:00.000Z"
}

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💰 Pricing

Volume	Approximate Cost
100 reviews	~$0.10
1,000 reviews	~$0.70
10,000 reviews	~$5.00
100,000 reviews	~$40.00

Pricing is based on compute units consumed. Venues with large review counts require more pages to load and may cost slightly more per review.

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⚙️ How It Works

1. URL Normalization — The actor validates and normalizes TripAdvisor URLs for hotels, restaurants, attractions, and vacation rentals. It automatically detects the venue type from the URL structure.

2. Venue Data Extraction — On the first page load, the actor captures venue-level metadata: name, overall rating, total review count, address, amenities, price range, and ranking.

3. Review Pagination — TripAdvisor displays 10 reviews per page. The actor iterates through all pages until maxReviews is reached, using efficient URL-based pagination (no infinite scroll required).

4. Language Filtering — When a language filter is applied, the actor uses TripAdvisor's native language filter URLs, ensuring only reviews in the target language are returned.

5. Review Parsing — Each review is parsed for: title, full text, rating (1–5 stars), date, trip type (solo, family, business, couples, friends), and reviewer profile data.

6. Management Responses — When present, management responses are extracted and attached to their corresponding review records.

7. Proxy Rotation — TripAdvisor aggressively blocks scrapers. Residential proxy rotation is used to maintain session health and avoid 403/CAPTCHA responses.

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⚠️ Limitations

• Public reviews only — The actor cannot access reviews that have been removed, hidden, or require TripAdvisor login to view
• Review text truncation — TripAdvisor truncates long reviews with a "Read more" link. The actor automatically expands truncated reviews, but this adds a small amount of time per review
• 500 review cap per venue — TripAdvisor shows a maximum of 500 reviews per language filter. To get reviews across all languages, run with language: "" (no filter)
• Dynamic CAPTCHA — Occasional CAPTCHA challenges may interrupt scraping. Residential proxies reduce this significantly, but occasional retries may occur
• Rating distribution — Aggregate statistics (rating breakdowns by traveler type) are available only for hotels, not restaurants or attractions
• Photo/media — Review photos and videos are referenced by URL but not downloaded; you'll need a separate image download step if you need the actual files
• Geographical availability — Some venues are region-locked; results may vary depending on proxy location

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🔗 Related Actors

• Airbnb Listings Scraper — Extract Airbnb listings, pricing, and host data
• Booking.com Hotel Scraper — Scrape hotel listings and reviews from Booking.com
• Yelp Business Scraper — Collect business reviews and ratings from Yelp

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📞 Support

For issues or feature requests, open a ticket via the Issues tab on this actor page or contact Apify Support.