Tripadvisor Review Scraper

TripAdvisor Review Scraper — Ratings, Text and Reviewer Profiles

Extract TripAdvisor reviews as structured JSON: review text, star rating, subratings, travel date, reviewer profile, owner responses, photos, and place metadata — no HTML parsing required. Works on hotels, restaurants and attractions. Point it at a TripAdvisor URL, a place name, or a keyword and it returns typed, ready-to-use rows. Start a run from the Apify Console or the API and watch reviews land in your dataset in real time.

🏨 What is TripAdvisor Review Scraper?

TripAdvisor Review Scraper is an Apify Actor that pulls reviews from TripAdvisor hotel, restaurant and attraction pages (Hotel_Review-*, Restaurant_Review-*, Attraction_Review-* URLs) and returns each review as a JSON row — text, rating, subratings, trip details, reviewer profile, and the place's own metadata. No TripAdvisor account or login is required — the Actor reads the same public review pages any visitor sees. It's built for hospitality teams, market researchers, and developers who need review data in a pipeline rather than a browser tab.

🔓 What TripAdvisor review data is publicly available to scrape?

Everything a TripAdvisor visitor can see on a place's review page is public — no login is required to read reviews, ratings, or place details. What's gated sits behind a TripAdvisor account for writing, not reading.

Data Category	Publicly Available	Restricted (TripAdvisor account required)
Review text, title, star rating	Yes
Subratings (Value, Location, Cleanliness, Service, Sleep Quality...)	Yes
Reviewer display name, username, home location, contribution count	Yes
Owner / management responses	Yes
Place name, place type, canonical TripAdvisor URL, total review count	Yes
Review photos	Yes
Writing a review or voting a review "helpful"		Login required
Reviewer's private contact details (email, phone)		Not published by TripAdvisor at all, with or without login

TripAdvisor Review Scraper only returns publicly visible data — what any visitor sees. Nothing behind a login wall.

📋 What data can I extract with TripAdvisor Review Scraper?

Every review row carries the fields below, read directly from the row-building code in src/main.py — not just the columns shown in the default dataset view.

📝 Review identity and content fields

Field	Description
id	TripAdvisor's internal review ID
url	Direct link to the review on TripAdvisor
title	Review headline
text	Full written review body
lang	Language code the review was written in
locationId	TripAdvisor location ID for the place
publishedDate	Date the review was published
travelDate	Month/year of the reviewer's stay (YYYY-MM)
tripType	Trip context TripAdvisor assigns (e.g. FAMILY, COUPLES, BUSINESS)
roomTip	Reviewer's tip for future guests, if one was given (null otherwise)

⭐ Ratings and engagement fields

Field	Description
rating	Overall star rating, 1–5
helpfulVotes	Helpful-vote count on the review itself
subratings	Array of {name, value} category ratings (Value, Rooms, Location, Cleanliness, Service, Sleep Quality — categories vary by place type; empty when the reviewer rated no categories)

🧩 Nested objects: reviewer, owner response, photos, and place info

Field	Description
user	Reviewer profile object — userId, name, username, isVerified, userLocation, avatar, link, contributions.totalContributions and contributions.helpfulVotes. null when scrapeReviewerInfo is disabled
ownerResponse	Management's reply object — id, text, lang, publishedDate, responder, connectionToSubject. null when the property never responded
photos	Array of reviewer-submitted photos — id, url, caption
placeInfo	Place metadata — id, name, webUrl, placeType (ACCOMMODATION, EATERY, ATTRACTION, ACTIVITY) and numberOfReviews (the place's full review count on TripAdvisor, unaffected by this run's language filter). Every value is read from TripAdvisor's review API — fields TripAdvisor does not expose on this data source (street address, geo-coordinates, rating histogram) are deliberately absent rather than filled with placeholders, and publishPlatform / accommodationCategory are dropped because TripAdvisor returns a constant for them rather than a real value
scrapedAt	ISO-8601 UTC timestamp of when the row was collected

🤖 Add-on: Need additional TripAdvisor data?

This Actor is scoped to reviews. For place discovery beyond reviews, or for Google-side review data on the same properties, pair it with Google Maps Extractor in the same account. For the accommodation-listing side of a trip (not reviews), Airbnb Rooms URLs Scraper covers Airbnb host portfolios.

🔌 How does TripAdvisor Review Scraper differ from the official TripAdvisor Content API?

TripAdvisor publishes an official Content API, but its Location Reviews endpoint returns only the 5 most recent reviews per location — nowhere near enough for trend analysis or bulk research. TripAdvisor Review Scraper returns up to 10,000 reviews per place, in the order you choose, with the full reviewer profile attached.

Feature	TripAdvisor Content API	TripAdvisor Review Scraper
Reviews per location	Up to 5 most recent (as documented on the API's ReadMe portal, checked 2026-08-04)	Up to 10,000 per place per run
Historical / oldest reviews	Not supported — most-recent only	sortOrder: "oldest" available
Reviewer profile fields	Not documented in the public reference	Full profile (name, username, location, avatar, contributions) when scrapeReviewerInfo is enabled
Rating filtering	Not documented	Filter by star rating or positive/negative/average via reviewRatings
Rate limit	Up to 50 calls per second (as documented, checked 2026-08-04)	No published call-rate cap — bound by TripAdvisor's own anti-bot response during a run
Setup	TripAdvisor developer account, billing details, and a pay-as-you-go budget	Apify account only — no TripAdvisor account needed

Use the official Content API if 5 recent reviews per property is enough and you already have TripAdvisor developer credentials. Use TripAdvisor Review Scraper when you need deep review history, reviewer profiles, or rating-filtered datasets without opening a TripAdvisor developer account.

▶️ How to use TripAdvisor Review Scraper

1. Open the Actor's page on the Apify Store and click Try for free (or find it in your Apify Console under Actors).
2. Add at least one entry to the required startUrls field — a direct TripAdvisor review URL, a place name, or a keyword.
3. Optionally set maxComments, sortOrder, reviewsLanguages, reviewRatings, and scrapeReviewerInfo.
4. Click Start. Reviews are pushed to the dataset one at a time as they're collected, so results appear during the run.
5. Download results as JSON, CSV, Excel, XML, or RSS from the dataset toolbar, or pull them with apify_client / a webhook once the run finishes.

🏨 How to scale to bulk review extraction

startUrls is an array — add as many TripAdvisor URLs, place names, or keywords as you want in one run, and the Actor works through them one place at a time, applying the same maxComments, sort, language, and rating settings to each. There's no separate "bulk mode" to enable; a longer list is the bulk method.

💡 What can you do with TripAdvisor review data?

• 🏨 Revenue managers monitoring guest sentiment use rating and subratings to track category-level trends (cleanliness, service, value) across a property over time.
• 📊 Market researchers and analysts pull text, rating, tripType, and travelDate into a BI dashboard to compare guest experience by season or traveler segment.
• 🕵️ Competitive intelligence teams compare rating distributions and subratings across competitor properties to benchmark positioning.
• 💬 Customer experience teams filter on ownerResponse to find reviews a property has, or hasn't, responded to.
• 🤖 AI engineers feed the text field into an LLM summarization or sentiment pipeline, using placeInfo and subratings as structured grounding context — no scraping or HTML cleanup needed before it reaches the model.

🛡️ How does TripAdvisor Review Scraper handle rate limits and blocking?

TripAdvisor's HTML pages sit behind DataDome bot protection, which answers a server-side HTTP client with a 403 challenge stub no matter which proxy tier it comes from. The Actor sidesteps that entirely: it never fetches an HTML review page. Reviews come from TripAdvisor's own review API (/data/graphql/ids), which is not behind DataDome and answers a plain HTTP request with the same review objects the site renders. That endpoint was verified working on direct, datacenter and residential egress, so proxyConfiguration is about spreading request volume rather than getting past a block.

Failed or non-200 requests to TripAdvisor's GraphQL endpoint are retried up to 3 times with a short delay before the Actor gives up on that page and moves on. TripAdvisor's review API only reliably accepts its default SERVER_DETERMINED sort; if it rejects sortOrder: "oldest" or "rating" mid-run, the Actor automatically falls back to the default order and keeps collecting rather than failing the run.

⚠️ TripAdvisor's own pagination caps each request at 20 reviews per page regardless of maxComments, and the Actor enforces a hard safety ceiling of 10,000 reviews per place even if you request more.

⬇️ Input

Parameter	Required	Type	Description	Example Value
startUrls	Yes	array	Direct TripAdvisor review URLs (Hotel_Review, Restaurant_Review, Attraction_Review, AttractionProductReview, VacationRentalReview, ShowUserReviews), place names, or keywords. Mix and match freely.	["https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"]
maxComments	No	integer	Maximum reviews to collect per URL. Default 10, minimum 1, maximum 10000.	100
sortOrder	No	string	Order reviews are fetched in. Enum: newest (default), oldest, relevant, rating. relevant currently returns the same order as newest — TripAdvisor does not expose a distinct relevance ranking on this data source.	"newest"
reviewsLanguages	No	string	Language to filter reviews by. Default "English". Enum: ALL_REVIEW_LANGUAGES plus 29 named languages (Spanish, French, German, Italian, Portuguese, Dutch, Russian, Japanese, Korean, Chinese Simplified/Traditional, Arabic, Turkish, Hebrew, Swedish, Norwegian, Danish, Finnish, Polish, Czech, Hungarian, Romanian, Greek, Thai, Vietnamese, Indonesian, Malay, Hindi).	"English"
reviewRatings	No	string	Star-rating filter applied after fetching. Default "ALL_REVIEW_RATINGS". Enum: ALL_REVIEW_RATINGS, POSITIVE (4–5★), NEGATIVE (1–2★), AVERAGE (3★), or a specific value "5", "4", "3", "2", "1".	"ALL_REVIEW_RATINGS"
scrapeReviewerInfo	No	boolean	Include the full reviewer profile object. Default true. When false, the user field is null in every row.	true
reviewQueryId	No	string	Advanced: pin a specific TripAdvisor persisted-query id instead of letting the Actor resolve one. Leave empty unless you know you need it.	"ef3cb4f569f27e43"
proxyConfiguration	No	object	Apify Proxy configuration. Defaults to Residential, which gives the most rate-limit headroom; datacenter and no-proxy both work too.	{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}

Example input

{
  "startUrls": [
    "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html",
    "luxury hotel New York"
  ],
  "maxComments": 200,
  "sortOrder": "newest",
  "reviewsLanguages": "English",
  "reviewRatings": "ALL_REVIEW_RATINGS",
  "scrapeReviewerInfo": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

⬆️ Output

Each collected review is pushed to the Apify dataset as one typed JSON row, with a consistent schema across runs. Export as JSON, CSV, Excel, XML, or RSS from the dataset toolbar, or read it via API/apify_client. The Actor is billed pay-per-event on the row_result event — one charge per review row actually pushed to the dataset. Reviews filtered out post-fetch by reviewRatings, or rows that fail to parse, are never pushed and never charged.

Example output

{
  "id": "1074754117",
  "url": "https://www.tripadvisor.com/ShowUserReviews-g60763-d208453-r1074754117-Hilton_New_York_Times_Square-New_York_City_New_York.html",
  "title": "great stay and so relaxing",
  "lang": "en",
  "locationId": "208453",
  "publishedDate": "2026-08-24",
  "rating": 5,
  "helpfulVotes": 0,
  "text": "The location was fabulous - so convenient to the subway and theatre.  The service was always friendly.  The rooms were clean, with a great view and no noise from the street!!!  The room was so comfortable I even slept through the night.  The room rate was a bargain considering the location, room, noise level and service.  We really enjoyed our stay and will definitely come again and recommend the hotel to others.",
  "roomTip": null,
  "travelDate": "2026-08",
  "tripType": "FAMILY",
  "user": {
    "userId": "BC7A336921ADD01F88AFB392620494E8",
    "name": "Passport503119",
    "username": "Passport503119",
    "isVerified": false,
    "contributions": {
      "totalContributions": 1,
      "helpfulVotes": 0
    },
    "userLocation": null,
    "avatar": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/1a/f6/f1/79/default-avatar-2020-21.jpg?w=100&h=100&s=1",
    "link": "https://www.tripadvisor.com/Profile/Passport503119"
  },
  "ownerResponse": {
    "id": "1075167008",
    "text": "Thank you for sharing such a wonderful review and recommendation with us! We're thrilled to have met the mark in terms of both convenience and comfort. Placing our guests in the center of the action, while maintaining a quiet atmosphere, is something we're very proud to offer here at Hilton Times Square. We sincerely appreciate your kind recognition and hope to welcome you back for another stellar stay in the future!",
    "lang": "en",
    "publishedDate": "2026-08-27",
    "responder": "Front Desk",
    "connectionToSubject": "General Manager"
  },
  "subratings": [
    {
      "name": "Value",
      "value": 5
    },
    {
      "name": "Rooms",
      "value": 5
    },
    {
      "name": "Location",
      "value": 5
    },
    {
      "name": "Cleanliness",
      "value": 5
    },
    {
      "name": "Service",
      "value": 5
    },
    {
      "name": "Sleep Quality",
      "value": 5
    }
  ],
  "photos": [],
  "placeInfo": {
    "id": "208453",
    "name": "Hilton New York Times Square",
    "webUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html",
    "placeType": "ACCOMMODATION",
    "numberOfReviews": 9004
  },
  "scrapedAt": "2026-08-30T06:48:00.819365+00:00"
}

⚙️ How does it work?

TripAdvisor Review Scraper reads reviews straight from TripAdvisor's own paginated review API, 20 at a time, resolving place names and keywords to a TripAdvisor page first when you don't provide a direct URL. That API only accepts persisted queries — opaque 16-character ids that stand in for the query text and change whenever TripAdvisor edits the query — so before each place the Actor proves an id with a live one-review request. If none of the ids it already knows still works, it reads TripAdvisor's current front-end manifest from the CDN, finds the module that issues the review query, recovers the new id from it and caches that for later runs. Nothing is hardcoded that cannot repair itself.

One behaviour worth knowing: on an attraction page TripAdvisor's own review list also includes reviews of that attraction's bookable products (for example ticket and tour listings sold for the same landmark). Those rows are kept, because TripAdvisor genuinely publishes them on the page you asked for — and each one is attributed to the entity it actually reviews, so its locationId, placeInfo and review url all point at the product rather than at the parent landmark. Filter on placeInfo.id if you want the parent only. Only publicly visible review and hotel data is returned — nothing behind a login. Because the output schema is fixed by the Actor rather than by TripAdvisor's page markup, the field names and structure stay stable even when TripAdvisor changes its front-end.

🔗 Integrations

TripAdvisor Review Scraper runs like any other Apify Actor, so it works with the tools you already use to run Actors.

Calling TripAdvisor Review Scraper programmatically

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_API_TOKEN>")

run = client.actor("tripadvisor-review-scraper-pay-per-events").call(run_input={
    "startUrls": ["https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"],
    "maxComments": 200,
    "sortOrder": "newest",
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Works in Go, Ruby, Node.js, cURL — any language that can make an HTTP request against the Apify API.

No-code tools (n8n, Make)

In n8n, use the official Apify node (or the HTTP Request node against the Apify API) to start a run and read back the dataset. In Make, the Apify app module can run the Actor and pass results into a subsequent scenario step, the same way it would for any other Apify Actor.

⚖️ Is it legal to scrape TripAdvisor reviews?

Scraping publicly available data — data any visitor can see without logging in — is generally lawful, and that is what TripAdvisor Review Scraper does. It returns only what's already visible on a place's public review page: no login, no bypassing an authentication wall.

Reviewer profile fields (name, username, location, avatar) returned when scrapeReviewerInfo is enabled are personal data, so GDPR (EU/UK) and CCPA (California) considerations apply to how you store, use, and retain that data — not to whether you may access the public page itself. Set scrapeReviewerInfo to false if you only need review text and ratings and want to avoid collecting personal data at all. Consult legal counsel if your use case involves bulk storage of personal data.

❓ Frequently asked questions

What TripAdvisor review fields does TripAdvisor Review Scraper return?

The top fields are text, rating, subratings, title, and publishedDate, plus the full reviewer profile in user and place metadata in placeInfo. See What data can I extract for every field.

Does TripAdvisor Review Scraper require a TripAdvisor account or login?

No. The Actor reads the same public review data any visitor sees; no TripAdvisor account, login, or API key is needed.

How many reviews can I extract in one run?

Up to 10,000 per place, set with maxComments (minimum 1, maximum 10,000). The Actor auto-paginates through TripAdvisor's 20-reviews-per-page API until it hits that number, the place's total review count, or its own 10,000-review safety cap.

What happens if a place name or keyword doesn't resolve?

startUrls accepts place names and keywords in addition to direct URLs. When you don't supply a direct review URL, the Actor resolves it via a Google search (TripAdvisor's own on-site search returns a bot challenge). If no matching place is found, that entry is skipped and logged with a warning — direct TripAdvisor URLs give the most reliable results.

Can I scrape multiple TripAdvisor places at once?

Yes — startUrls is an array. Add as many TripAdvisor URLs, place names, or keywords as you want and the Actor collects reviews for each one in the same run, applying the same settings to all of them.

Does TripAdvisor Review Scraper work with Claude, ChatGPT, and other AI agent tools?

It's callable as a standard HTTP endpoint through the Apify API by any agent framework that can make HTTP requests — see the Integrations section above for the apify_client example.

How does TripAdvisor Review Scraper compare to other TripAdvisor review scrapers?

Compare on documented capability rather than marketing copy: check what fields each scraper's own listing documents for the user, subratings, and placeInfo objects, and whether the listing states a review cap per place — this Actor documents a 10,000-review cap and a full reviewer profile object.

Does TripAdvisor Review Scraper return data in a format LLMs can use directly?

Yes. Every row is typed, normalized JSON with consistent field names across runs — no HTML, no selectors to write. Pass text and subratings straight into an LLM prompt, index them into a vector store, or feed them to an agent tool.

What happens when TripAdvisor changes its layout or anti-bot system?

The Actor's output schema is fixed by its own code, not by TripAdvisor's page markup, so field names stay stable even after a TripAdvisor front-end change. When TripAdvisor rotates its persisted-query ids the Actor detects it (the API answers a stale id with an empty 400), rediscovers the current id from TripAdvisor's own CDN manifest, and carries on. If even that fails, the run logs a clear error and returns nothing for that place rather than silently returning wrong data.

Can I use TripAdvisor Review Scraper without managing proxies or browser infrastructure?

Yes. The Actor handles proxying (Residential by default), persisted-query resolution, and request retries itself — you don't configure any of that beyond the optional proxyConfiguration field. No browser is launched, so runs are fast and cheap.

Which fields work best for AI training data and RAG indexing?

For RAG, index text alongside title, rating, and placeInfo.name for grounding context. For structured training data, rating, subratings, tripType, and travelDate are the most consistently populated fields across records, all returned as typed primitives (strings, numbers, or nested objects) rather than free-form HTML.

🔗 Related scrapers

Scraper Name	What it extracts
Google Maps Extractor	Places, business listings, and Google-side reviews for the same properties
Airbnb Rooms URLs Scraper	Airbnb host portfolios and co-host listing URLs

💬 Your feedback

Found a bug, or need a field this Actor doesn't return yet? Leave a message in the Actor's Issues tab on the Apify Store, or reach out through Apify Console support — reports like these are how this scraper keeps working as TripAdvisor changes.