TripAdvisor Reviews Scraper - All 5 Categories

What does TripAdvisor Reviews Scraper - All 5 Categories do?

TripAdvisor Reviews Scraper - All 5 Categories extracts review data from TripAdvisor — the world's largest travel platform. It works as an unofficial TripAdvisor API alternative, letting you collect structured review data from all 5 content categories: Hotels, Restaurants, Attractions, Activities (Tours & Experiences), and Cruises.

Just provide one or more TripAdvisor detail page URLs, and the Actor will return clean, structured review data in JSON, CSV, Excel, or other formats — ready for analysis.

Why use TripAdvisor Reviews Scraper - All 5 Categories?

TripAdvisor hosts over 1 billion reviews across millions of listings worldwide. Manually collecting this data is impractical. This Actor automates the entire process and gives you:

• 🏨 All 5 categories — Hotels, Restaurants, Attractions, Activities, and Cruises in one tool
• 🔍 Rich filtering — Filter by rating (1-5), traveler type, time of year, review language, and date range
• 🌍 49 country sites — Read from any localized TripAdvisor domain (US, UK, Japan, Germany, France, etc.)
• ⭐ Rating overview — Every row carries the page's own overall rating and Excellent-to-Terrible breakdown, in the page's own wording
• 📅 Date control — Scrape only recent reviews (last N days) or reviews after a specific date
• 🌐 Auto-translate — Automatically translate non-English reviews to English
• 📊 37 data fields per review — Including owner responses, user profiles, photos, and more
• ⚡ Fast & lightweight — Uses direct API calls, no browser needed. Low compute cost

Common use cases

• Hospitality analytics — Monitor guest sentiment and satisfaction trends for hotels and restaurants
• Competitive analysis — Compare review scores, traveler types, and seasonal patterns across competitors
• Market research — Understand traveler preferences by region, language, and trip type
• Reputation management — Track owner responses and identify unaddressed complaints
• Content aggregation — Build travel recommendation engines and review dashboards
• Academic research — Collect large-scale review datasets for NLP and sentiment analysis

Why choose this Actor over alternatives?

Feature	This Actor	Others
Categories	All 5 (Hotels, Restaurants, Attractions, Activities, Cruises)	Usually 1-3
Method	Direct API	Browser-based (slow, expensive)
Filters	Rating, traveler type, language, month, date range	Limited or none
Regions	49 localized domains	US only or limited
Auto-translate	✅ Built-in	❌ Not available
Cost	Low (no browser overhead)	Higher CU consumption

What data can you extract from TripAdvisor?

Each review includes 37 structured fields:

Field	Type	Description
locationId	Text	TripAdvisor location identifier
locationName	Text	Hotel, restaurant, or attraction name
locationAverageRating	Number	Overall rating shown on the page, e.g. 4.7
locationReviewCount	Number	Total reviews the page reports, e.g. 2522
locationRatingCounts	Object	Rating breakdown as shown on the page, e.g. {"Excellent": 2032, "Good": 312, "Average": 101, "Poor": 40, "Terrible": 37}
reviewId	Text	Unique review identifier
reviewUrl	Link	Direct URL to the review
title	Text	Review title/headline
text	Text	Full review text
rating	Number	Overall rating (1-5)
additionalRatings	Object	Sub-ratings (Service, Value, Location, etc.)
publishedDate	Date	When the review was published
createdDate	Date	When the review was written - this is the date the page shows, and what Most recent sorts by. Differs from publishedDate on roughly 10% of reviews
travelDate	Text	When the reviewer traveled
tripType	Text	Family, Couples, Solo, Business, or Friends
language	Text	Review language code
translationType	Text	MACHINE when the text you got was machine-translated - the page shows a "Machine Translated" badge on these
helpfulVotes	Number	Number of helpful votes received
photoUrls	Array	URLs of photos attached to the review, up to 10
photoCount	Number	How many photos the review really has, so you can tell when photoUrls was capped
username	Text	Reviewer's display name
userLocation	Text	Reviewer's location
contributionCount	Number	Reviewer's total contributions - the "N contributions" on the page
userHelpfulVotes	Number	Helpful votes the reviewer has collected across all their reviews - the "N helpful votes" shown next to it. Not the same as helpfulVotes, which counts votes on this one review
userProfileUrl	Link	Link to reviewer's profile
ownerResponseRole	Text	How the responder is described on the page, e.g. Owner, General Manager
ownerResponseText	Text	Management/owner response to the review
ownerResponseDate	Date	When the owner responded

Plus additional fields: userAvatar, originalLanguage, ownerResponseName, cruiseLabels, reviewTips, attribution, page, crawledAt, detailUrl.

How to scrape TripAdvisor reviews

1. Go to the Actor page on Apify Store and click Try for free
2. Add TripAdvisor URLs — Paste one or more detail page URLs into the Detail Page URLs field. Supported URL formats:
   • https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-...
   • https://www.tripadvisor.com/Restaurant_Review-g298113-d1176949-Reviews-...
   • https://www.tripadvisor.com/Attraction_Review-g297415-d502989-Reviews-...
   • https://www.tripadvisor.com/AttractionProductReview-g294217-d26810431-...
   • https://www.tripadvisor.com/Cruise_Review-d15691669-Reviews-...
3. Set filters (optional) — Choose rating, traveler type, language, date range, or sort order
4. Click Start — The Actor begins extracting reviews
5. Download results — Export data as JSON, CSV, Excel, XML, or HTML from the Output tab

How much does it cost to scrape TripAdvisor reviews?

This Actor uses direct API calls instead of a browser, making it significantly cheaper than browser-based alternatives. There is no browser rendering overhead, so compute unit (CU) consumption stays low even for large-scale scraping jobs.

Cost depends on the number of reviews extracted and your Apify subscription plan. Apify offers a free tier to get started — you can test the Actor before committing to a paid plan.

Input

The Actor accepts the following input parameters. Only Detail Page URLs is required — all other fields are optional with sensible defaults.

Parameter	Type	Default	Description
detailUrls	Array	(required)	List of TripAdvisor detail page URLs (up to 10,000)
maxReviews	Number	0 (all)	Maximum reviews per URL. Set 0 for unlimited
region	Select	United States	Country site, same as the selector at the bottom of the page. Changes TripAdvisor's own labels (place name, reviewer hometown, sub-rating and rating-breakdown names), not the reviews
currency	Select	U.S. Dollars	The currency selector at the bottom of the page (36 options). Reviews carry no prices, so this rarely changes anything in the output
ratingFilter	Multi-select	All	Filter by star rating (1-5)
travelerType	Multi-select	All	Family, Couples, Solo, Business, Friends
timeOfYear	Multi-select	All	Filter by month (1-12)
reviewLanguage	Select	All languages	The "Read reviews in" dropdown. Returns reviews available in that language, with the text in that language; originalLanguage still shows what it was written in
startDate	Date	None	Only scrape reviews after this date. Forces Most recent sorting
recentDays	Number	0 (all)	Only scrape reviews from the last N days. Forces Most recent sorting
sortBy	Select	Most recent	Most insightful, Most recent, or Detailed reviews - same as the Sort by dropdown on the page. Ignored when a date filter is set
searchQuery	Text	None	Keyword search inside the reviews, same as the Search reviews box on the page
autoTranslate	Boolean	true	The "Include review content translations" switch. On, review text comes back in the language you are reading in; off, every review comes back exactly as written

For full details, see the Input tab on the Actor page.

Output

The Actor stores results in a dataset. You can download the data in multiple formats: JSON, CSV, Excel, XML, HTML.

Here is a simplified example of the output in JSON format:

{
    "locationId": 93450,
    "locationName": "Hyatt Grand Central New York",
    "locationAverageRating": 3.5,
    "locationReviewCount": 15005,
    "locationRatingCounts": {"Excellent": 4361, "Good": 4325, "Average": 2947, "Poor": 1702, "Terrible": 1670},
    "reviewId": 1076974161,
    "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g60763-d93450-r1076974161-Hyatt_Grand_Central_New_York-New_York_City_New_York.html",
    "title": "September 2026",
    "text": "I selected this hotel three times is because is close by to our NYC office. Others are not too great and I may try other hotel for the next time.",
    "rating": 3,
    "additionalRatings": {},  // Sub-ratings (e.g. Service, Value, Location). Empty {} when the reviewer left none
    "publishedDate": "2026-09-09",
    "createdDate": "2026-09-09",  // The date the page shows. Differs from publishedDate on ~10% of reviews
    "travelDate": "2026-09-30",
    "tripType": "",  // Family, Couples, Solo, Business or Friends. Empty when the reviewer did not say
    "language": "en",
    "originalLanguage": "en",
    "translationType": "",  // MACHINE when the text you got was machine-translated
    "helpfulVotes": 0,  // Helpful votes on THIS review
    "photoUrls": [
        "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/34/87/02/ac/caption.jpg",
        "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/34/87/03/40/caption.jpg",
        "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/34/87/04/c7/caption.jpg"
    ],
    "photoCount": 3,  // Photos the review really has; photoUrls holds at most 10
    "username": "Tak-wai K",
    "userLocation": "Ohio",
    "contributionCount": 4,
    "userHelpfulVotes": 0,  // Helpful votes the REVIEWER has collected across all their reviews
    "userProfileUrl": "https://www.tripadvisor.com/Profile/takwaik2020",
    "userAvatar": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/1a/f6/e8/91/default-avatar-2020-62.jpg",
    "ownerResponseName": "GCC P",
    "ownerResponseRole": "Owner",
    "ownerResponseText": "Greetings from Hyatt Grand Central New York, Thank you for taking the time to share your feedback...",
    "ownerResponseDate": "2026-09-09",
    "cruiseLabels": {},  // {"Cabin Type": ..., "Type of Trip": ..., "Destination": ...}. Empty {} for non-cruise categories
    "reviewTips": [],  // Traveler tips. Empty [] for categories without tips
    "attribution": "Hyatt Hotels",  // Set when the page says "Review collected in partnership with ..."
    "page": 3,
    "crawledAt": "2026-09-13 07:23:22",
    "detailUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html"
}

Tips for best results

• Start small — Test with maxReviews: 10 first to verify the URL works and the output meets your needs
• Use date filters — For ongoing monitoring, use recentDays (e.g., 30) to only scrape new reviews since your last run
• Combine filters wisely — You can combine rating, traveler type, and language filters to extract exactly the reviews you need
• Languages — reviewLanguage works like the "Read reviews in" dropdown on the page: pick Japanese and you get the reviews available in Japanese, with the text in Japanese (machine-translated where the review was written in another language, as long as autoTranslate stays on). Turn autoTranslate off and the same reviews come back exactly as written instead. originalLanguage always tells you the language it was written in. Note that a language usually has far fewer reviews than the page total - a tour with 305 reviews may have only 33 in Japanese, so combining a language with recentDays can legitimately return nothing. region is a separate thing - it only changes TripAdvisor's own labels, never the reviews
• Sorting — The default is Most recent, which returns every review. Most insightful is TripAdvisor's own ranking and leaves out a few reviews - mostly ones written in other languages and the newest few days - exactly as the page itself does (a tour showing 305 reviews under Most recent shows 293 under Most insightful). TripAdvisor only ranks tours & activities this way; on hotels, restaurants, attractions and cruises it gives you the same order as Most recent
• Date filters override sorting — startDate and recentDays need the reviews in date order to know when to stop, so setting either one switches the run to Most recent. The run log says so when it happens
• Schedule regular runs — Use Apify's built-in scheduling to automatically collect new reviews on a daily or weekly basis
• Integrate with your tools — Connect the output to Google Sheets, Slack, Zapier, or your own API via Apify integrations

FAQ and support

Is it legal to scrape TripAdvisor?

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.

How many reviews can I scrape?

There is no hard limit from the Actor side. You can scrape all available reviews for a listing by setting maxReviews to 0. For listings with thousands of reviews, the Actor will paginate through all pages automatically.

Can I scrape reviews in languages other than English?

Yes. Use the reviewLanguage filter to select from 17 supported languages including English, Chinese (Simplified/Traditional), Japanese, Korean, German, French, Spanish, Italian, Portuguese, Russian, and more.

What if a URL is not supported?

The Actor supports 5 URL types: Hotel_Review, Restaurant_Review, Attraction_Review, AttractionProductReview, and Cruise_Review. If you provide an unsupported URL format, the Actor will log a warning and skip it.

Where can I get help?

If you encounter any issues, please open an issue on the Issues tab of this Actor's page. You can also reach out via the Apify community on Discord.