Tripadvisor Review Scraper

🚀 What is Tripadvisor Review Scraper?

Tripadvisor Review Scraper is an Apify Actor that collects public reviews of Tripadvisor hotels, restaurants, attractions and tours. Each review comes with its stars, title, full text, trip type, photos and owner reply, plus rating and rank details of the place. You paste place links, choose filters and export the results.

• Many places per run: add as many links or place ids as you like.
• Live results: every review is saved as soon as it is read, so the Output tab fills while the run is going.
• Seven tables: reviews, places, reviewers, photos, owner replies, sub-ratings and a status row per input link.
• Filters: narrow reviews by stars, language, keyword, traveler type, month or date before they are saved.
• No Tripadvisor account: the Actor reads public pages that any visitor can see.

Click Try for free, paste a place link and press Start.

📊 What data can you extract from Tripadvisor?

The default dataset holds the core tripadvisor review data, one review per row. You can download Tripadvisor reviews as JSON, CSV, Excel, XML or HTML. The example values below are made up for illustration.

Field	Description	Example
id	Tripadvisor review ID	900000001
url	Link to the review on Tripadvisor	https://www.tripadvisor.com/ShowUserReviews-g100000-d1234567-r900000001-Example_Harbour_Hotel-Example_City.html
title	Review title	Example review title
lang	Language the review is shown in	en
locationId	Tripadvisor ID of the place	1234567
publishedDate	Date the review was written (YYYY-MM-DD)	2026-10-20
rating	Stars given, 1 to 5	2
helpfulVotes	Helpful votes the review received	0
travelDate	Month or day of the stay or visit	2026-09
tripType	FAMILY, COUPLES, SOLO, BUSINESS or FRIENDS when given	COUPLES
text	Full review text	Example review text written for this README. It is not a real review.
originalLanguage	Language the review was written in	en
isMachineTranslated	True when Tripadvisor translated the text	false
subratings	Extra ratings such as Value, Service or Rooms as name/value pairs	[{"name": "Service", "value": 2}]
ownerResponse	The owner's reply with text, date, responder and days to respond	{"daysToRespond": 2, ...}
hasOwnerResponse	True when the owner replied	true
wordCount	Words in the review text	13
photoCount	Real number of photos on the review	1
photos	Photo links, sizes and captions	[{"id": 1, "width": 1200, ...}]
reviewerTip	Tip the reviewer left for other travelers	null
isPinnedFavorite	True when the reviewer pinned the review	false
hasTrustSafetyAlert	True when Tripadvisor flagged the review	false
user	Reviewer name, username, link, hometown, country and contribution counts	{"name": "Example Traveler", ...}
placeInfo	Place details: rating histogram, rank, address, amenities	{"name": "Example Harbour Hotel", ...}
scrapedAt	When the review was read (UTC)	2026-10-27T09:00:00Z

Six more tables are filled in the same run. Each one is a separate dataset in the Output tab.

Table	One row per	Main fields
Places	place	name, rating, rank, rank category, star counts, address, amenities
Reviewers	review author	name, username, hometown, country, contributions
Photos	review photo	link, width, height, caption
Owner replies	owner reply	reply text, responder, days to respond
Sub-ratings	sub-rating on a review	name, value
Inputs	input link	status, place name, reviews saved, note

The places table adds the star histogram, rank and rank category of each place. The reviewers table holds name, username, hometown and country. The photos table lists photo links, sizes and captions. The owner replies table holds tripadvisor owner responses with the days it took to answer. Together the tables form a tripadvisor reviews dataset that you can filter by place.

💡 Use cases for Tripadvisor data

• Hotel review analysis: read text, rating and subratings side by side to see what guests praise or criticize. The same rows support guest feedback analysis for one property or a whole city.
• Reputation monitoring: schedule a weekly run with reviewsSince for online reputation monitoring for hotels. A list of venues works the same way for restaurant reputation monitoring.
• Alerts on bad reviews: set ratings to 1 and 2 and reviewsSince to a short period to monitor low star reviews. Compare publishedDate with ownerResponse.daysToRespond to track owner response time.
• Competitor benchmarking: add the links of rival places for competitor hotel review analysis in one run. The places table adds rating, rank and star counts for hotel competitor benchmarking.
• Tourism research: user.country, user.hometown and user.isDomesticReviewer feed tourism market research. Count them per place for visitor origin analysis.
• Seasonal patterns: the months and travelerTypes inputs support seasonal review analysis, for example June to August reviews written by families. Group tripType for review analysis by traveler type.
• Tours, attractions and restaurants: tour pages give you tripType and travelDate for tour operator review analysis. Attraction links work for attraction review analysis. Restaurant links work for restaurant review analysis. Mixing hotels, restaurants and tours in one run supports customer feedback analysis across a portfolio.
• Complaints and datasets: the keyword input and low star ratings help find recurring complaints in reviews, such as breakfast or noise. Export the clean rows as a review dataset for machine learning. Use the stars and text for hotel review sentiment analysis in your own tool.

🛠️ How to scrape Tripadvisor reviews

1. Create a free Apify account and open Tripadvisor Review Scraper in Apify Console.
2. Paste one or more Tripadvisor hotel, restaurant, attraction or tour links into Tripadvisor links. A place id such as d1234567 also works.
3. Add several links to collect bulk Tripadvisor reviews in one run, and set Max reviews per place (50 by default, 0 for every review) and any filters you need.
4. Click Start. Every review is saved as soon as it is read, so you can get Tripadvisor reviews in the Output tab while the run is going.
5. Open the Output tab to browse the tables.
6. Download the dataset as JSON, CSV, Excel, XML or HTML.

How to get Tripadvisor reviews by rating

Set Star ratings to the stars you want, for example 1 and 2 for complaints. The Actor keeps only reviews with those ratings.

How to get Tripadvisor reviews by language

Pick a code in Review language, such as en or de. Tripadvisor then shows the reviews in that language, and isMachineTranslated and originalLanguage tell you which ones were translated.

How to get Tripadvisor reviews by date

Set Reviews since to a date such as 2025-01-31 or a relative value such as 6 months.

How to get Tripadvisor reviews by keyword

Type a word such as breakfast into Keyword in review to keep only reviews that mention it.

How to get Tripadvisor reviews by month

Choose one or more months in Months written to keep reviews written in those months of any year.

How to get Tripadvisor reviews by traveler type

Pick family, couples, solo, business or friends in Traveller types.

How to export Tripadvisor reviews to Excel

Open the dataset in the Output tab, choose Excel in the export menu and download the file. To export Tripadvisor reviews to CSV, pick CSV in the same menu.

💰 How much does it cost to scrape Tripadvisor?

The Actor uses pay per event. The main_result event is charged once per saved review, and the apify-actor-start event is charged once per run at $0.00005. Apify platform usage (compute) is billed on top of the events above.

Plan tier	Price per review	Price per 1,000 reviews
Free	$0.001	$1.00
Bronze	$0.0009	$0.90
Silver	$0.0008	$0.80
Gold, Platinum, Diamond	$0.0007	$0.70

Example: 1,000 reviews on the Free tier cost 1,000 x $0.001 = $1.00, and 500 reviews on the Gold tier cost 500 x $0.0007 = $0.35, each plus the $0.00005 start event. Only reviews in the default dataset are charged; the other tables are not. Check the Pricing tab for the current rates, and set a maximum spend per run to cap the total. The Actor is configured with 1024 MB of memory.

⬇️ Input

Only Tripadvisor links (urls) is required. The example below reads up to 20 recent one and two star English reviews for one place. Replace the link with your own place; the id in it is a placeholder.

{
  "urls": [
    "https://www.tripadvisor.com/Hotel_Review-g100000-d1234567-Reviews-Example_Harbour_Hotel-Example_City.html"
  ],
  "maxReviewsPerPlace": 20,
  "reviewsSince": "6 months",
  "ratings": ["1", "2"],
  "language": "en",
  "sort": "newest",
  "includePlaceInfo": true,
  "includeReviewerDetails": true,
  "includePhotos": true,
  "proxyConfiguration": { "useApifyProxy": false }
}

Field	What it does
urls (required)	Tripadvisor hotel, restaurant, attraction or tour links, or place ids, one per line.
maxReviewsPerPlace	Most reviews saved for each place. 0 means every review. Default 50.
reviewsSince	Only reviews written on or after a date (2025-01-31) or a relative value such as 6 months. Empty means no limit.
ratings	Keep only these star ratings ("1" to "5"). Empty means all.
language	all or one language code such as en, fr, de or zh-CN.
sort	newest (default), detailed or insightful.
keyword	Only reviews that mention this text.
travelerTypes	family, couples, solo, business or friends. Empty means all.
months	Only reviews written in these months of any year. Empty means all.
includePlaceInfo	Add the place block to every review row. Default on. The places table is always filled.
includeReviewerDetails	Add the reviewer block to every review row. Default on.
includePhotos	Add photo links to every review row. Default on.
proxyConfiguration	Optional. Leave the default to start without a proxy.

💡 Start with a small maxReviewsPerPlace to check the result before a large run.

💡 Reviewer details are personal data. Switch includeReviewerDetails off when you only need ratings and text.

⚠️ When reviewsSince is combined with a sort other than newest, the Actor reads at most 100 pages of reviews per place before filtering.

⬆️ Output

The scraped results are shown as a dataset in the Storage tab. The table view is for convenience and doesn't show all the fields. You can export the data as JSON, CSV, Excel, XML or HTML. This sample continues from the input above and uses made-up values, not a real review.

{
  "id": 900000001,
  "url": "https://www.tripadvisor.com/ShowUserReviews-g100000-d1234567-r900000001-Example_Harbour_Hotel-Example_City.html",
  "title": "Example review title",
  "lang": "en",
  "locationId": 1234567,
  "publishedDate": "2026-10-20",
  "rating": 2,
  "helpfulVotes": 0,
  "travelDate": "2026-09",
  "tripType": "COUPLES",
  "text": "Example review text written for this README. It is not a real review.",
  "originalLanguage": "en",
  "isMachineTranslated": false,
  "subratings": [{ "name": "Service", "value": 2 }, { "name": "Value", "value": 3 }],
  "ownerResponse": {
    "id": 900000002,
    "text": "Example reply text.",
    "lang": "en",
    "publishedDate": "2026-10-22",
    "responder": "Manager",
    "responderName": "Example Manager",
    "daysToRespond": 2
  },
  "hasOwnerResponse": true,
  "wordCount": 13,
  "photoCount": 1,
  "photos": [{ "id": 1, "url": "https://example.com/photo.jpg", "width": 1200, "height": 800, "caption": null }],
  "reviewerTip": null,
  "isPinnedFavorite": false,
  "hasTrustSafetyAlert": false,
  "user": {
    "userId": "EXAMPLE0000",
    "name": "Example Traveler",
    "username": "example_traveler",
    "link": null,
    "isVerified": false,
    "avatar": null,
    "hometown": "Sampletown, Germany",
    "userLocation": { "name": "Sampletown, Germany", "id": null },
    "country": "Germany",
    "isDomesticReviewer": false,
    "totalContributions": 12,
    "helpfulVotesReceived": 0
  },
  "placeInfo": {
    "id": "1234567",
    "name": "Example Harbour Hotel",
    "placeType": "HOTEL",
    "rating": 4.0,
    "numberOfReviews": 250,
    "ratingDistribution": { "1": 10, "2": 20, "3": 40, "4": 80, "5": 100 }
  },
  "scrapedAt": "2026-10-27T09:00:00Z"
}

Each row is one review, so the export opens as a Tripadvisor reviews spreadsheet. A RUN_SUMMARY record in the key-value store lists the counts of the run: reviews saved and charged, places read, places with problems and requests sent.

⚠️ Limitations and error handling

• Only public reviews are collected. Nothing that needs a Tripadvisor login is read.
• The number of reviews can be lower than the count shown on Tripadvisor. Filters, maxReviewsPerPlace and what Tripadvisor returns all reduce it, and the log notes when fewer reviews came back than the place reports.
• One language can be selected per run. Run again for another language.
• Fields such as rank, address, price range, cuisines, phone and website depend on what the place page shows, and can be null.
• Pages that are not hotel, restaurant, attraction or tour pages are not supported.
• If Tripadvisor cannot be reached, the run stops and keeps everything saved so far. It fails only when nothing was saved.
• If you set a maximum spend per run, the Actor stops cleanly when it is reached.

The Inputs table has one row per link with a status:

Status	Meaning	What to do
ok	All reviews that match the filters were read	Nothing
limit	The run stopped at maxReviewsPerPlace or at your spend limit	Raise the limit and run again
empty	No review matched your filters	Relax the filters
error	The place could not be read; the note field says why	Check the link and run again later
invalid	The input is not a Tripadvisor hotel, restaurant, attraction or tour link	Fix the link
skipped	The run stopped before this place	Run it again

🔌 Integrating Tripadvisor Review Scraper with other apps

You can start Tripadvisor Review Scraper from the Apify API, on a schedule or from a webhook, and send the results on to other tools. For a weekly check, set reviewsSince to 7 days and run the Actor on a schedule; each run then saves only recent reviews.

• Apify integrations, including Make and Zapier
• Webhooks to trigger your own code when a run finishes
• The Apify API with the Actor id data_wiki/tripadvisor-review-scraper; see the API tab for ready-made code
• AI agents can call this Actor through the Apify MCP server

🔗 Other travel and feedback scrapers by data_wiki

Actor	What it extracts	When to use it
Airbnb scraper	Airbnb listings for a city or link: prices, hosts, amenities, photos, ratings	When you compare hotels with short-term rentals
Facebook comment scraper	Comments and replies from public Facebook posts	When guest feedback is posted on Facebook
Instagram comment scraper	Comments from public Instagram posts and reels	When guests comment under a venue's Instagram posts
TikTok data extractor	TikTok videos by link, profile, hashtag or keyword	When you research how a destination is shown on TikTok
LLM pricing and speed data	Model prices, latency, uptime and benchmark scores from OpenRouter	You build AI analysis and need to compare language models

If you study short-term stays next to hotels, you can collect Airbnb listings for a city with the same research list. You can export comments from public Facebook posts or read the comments on Instagram posts and reels to see feedback outside Tripadvisor, and find TikTok videos about a destination for trend research.

⚖️ Is it legal to scrape Tripadvisor?

Tripadvisor Review Scraper only collects reviews and profile details that users have made public on Tripadvisor, and it does not read private data or anything behind a login. Reviews still contain personal data such as names, usernames, hometowns, photos and review text. Collect it only with a legitimate reason, follow rules such as the GDPR and CCPA, respect Tripadvisor's terms and the copyright of review text and photos, and do not use the data to profile or contact individual reviewers. This is not legal advice; consult a lawyer if you are unsure. See is web scraping legal and ethical web scraping for background.

❓ FAQ

Do I need a Tripadvisor account or API key?

No. You can get Tripadvisor reviews without login because the Actor uses public pages, so you only need an Apify account. For programmatic access, use the Apify API with your Apify token.

Which Tripadvisor pages does it support?

Hotel, restaurant, attraction and tour pages from any Tripadvisor domain, plus place ids. Other page types get the status invalid or error.

Can I use it as a Tripadvisor hotel review scraper?

Yes. Paste hotel links and the Actor reads their reviews, with amenities and the rating histogram in the places table.

How many reviews can Tripadvisor Review Scraper get?

As many as Tripadvisor returns for the place and your filters. maxReviewsPerPlace defaults to 50, and 0 reads every review. Run a small test first to confirm the count.

Is there a tripadvisor reviews api for this?

Yes, in the sense that you can run the Actor and read its dataset through the Apify API. It is not an official Tripadvisor API.

Can I scrape restaurant reviews only?

Yes. Paste restaurant links and the Actor will scrape restaurant reviews for each one, with the cuisines and rank in the places table.

Do I need proxies?

No. The Actor starts without a proxy, retries when Tripadvisor rejects a request and switches to another connection. You can also choose a proxy in the input.

Can I scrape private data or reviewer emails?

No. Only public review and profile details are collected.

Can I use it through an MCP server?

Yes. Agents can find and call the Actor through the Apify MCP server with the same input as above.

💬 Your feedback

Found a problem or need another field? Open an issue in the Issues tab of the Actor. Need a custom solution? Contact hello.datawiki@gmail.com.