Tripadvisor Reviews Scraper

Fast, reliable Tripadvisor reviews scraper for hotels, restaurants, and attractions. Drop in any Tripadvisor property URL and get every review back as clean JSON, ready to load into a database, BI tool, or LLM pipeline. No headless browser, no per-cookie setup, no user logins required.

This actor is built for analysts, hospitality consultants, market researchers, and anyone who needs Tripadvisor review data at scale. It paginates through the full review history of a property and returns rich fields including the review body, star rating, traveler context, dates, language, reviewer profile, helpful votes, photos, management responses, and per-aspect subratings (hotels).

What this Tripadvisor reviews scraper extracts

For every review on a property, the actor returns:

• Review ID, full text body, headline title, star rating (1 to 5)
• Published date and original creation date (ISO 8601)
• Stay or visit date and trip type (couples, family, solo, business, friends)
• Language and original language codes (BCP-47)
• Helpful vote count
• Reviewer profile: display name, username, profile URL, hometown, avatar, total contributions, verified flag
• Photo IDs and rendered photo URL templates for any images attached
• Management or owner response: text, date, responder name, role
• Per-aspect subratings (Value, Rooms, Location, Cleanliness, Service, Sleep Quality) for hotels
• Direct deep link to the review page on Tripadvisor

Every output field is camelCase JSON. The dataset schema declares each field so the Apify Console table view and the CSV / XLSX exports work out of the box.

How it works

The scraper reads Tripadvisor's server-rendered HTML once to seed the session and pull the first page of reviews for free. Pages two onward come from Tripadvisor's internal GraphQL endpoint at /data/graphql/ids using the persisted query id documented in our recon. Pagination is limit / offset with a 20-per-page server cap, and there is no upper depth limit, so the scraper happily walks the full review history of properties with tens of thousands of reviews.

Anti-bot is handled automatically. The actor uses Safari TLS impersonation via curl_cffi and rotates through a pool of impersonation profiles when DataDome challenges appear. Apify Residential proxies in the US are recommended for production runs and are configured by default.

Input

Provide at least one Tripadvisor property URL in startUrls. URLs can be hotel, restaurant, or attraction listings on any Tripadvisor locale (.com, .co.uk, .ca, .de, etc.).

{
    "startUrls": [
        {"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93437-Reviews-The_Plaza-New_York_City_New_York.html"}
    ],
    "maxReviewsPerProperty": 1000,
    "language": "en",
    "sortBy": "MOST_RECENT",
    "minRating": 0,
    "includePhotos": true
}

Key inputs:

• startUrls (required): one or more Tripadvisor property URLs.
• maxReviewsPerProperty (default 1000): cap on reviews returned per property.
• language: BCP-47 language filter, or leave empty for all languages.
• sortBy: MOST_RECENT, SERVER_DEFAULT, or MOST_FAVORABLE.
• minRating: only return reviews at or above this star value.
• includePhotos: include photo URL templates and IDs on each review.
• proxyConfiguration: Apify proxy config, defaults to US Residential.

Output

One record per review. Sample (truncated):

{
    "reviewId": 1060541589,
    "locationId": 93437,
    "propertyName": "Hotel Edison",
    "propertyType": "HOTEL",
    "title": "Birthday on Broadway",
    "text": "This trip was for my mother's 79th Birthday on Broadway...",
    "rating": 5,
    "publishedDate": "2026-05-12",
    "stayDate": "2026-04-30",
    "tripType": "FAMILY",
    "language": "en",
    "helpfulVotes": 3,
    "reviewerName": "Jane D",
    "reviewerHometown": "Atlanta, GA",
    "subratings": [
        {"label": "Value", "rating": 5},
        {"label": "Rooms", "rating": 5}
    ],
    "managementResponse": {
        "text": "Dear Jane, we thank you for staying...",
        "publishedDate": "2026-05-13",
        "responderName": "Rommel",
        "responderRole": "Guest Services / Front Office"
    },
    "photos": [
        {"id": 859139197, "urlTemplate": "https://...{width}x{height}...jpg"}
    ],
    "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g60763-d93437-r1060541589-..."
}

Pricing

Flat pay-per-event pricing. You only pay for review records actually written to the dataset. No per-run fees, no minimums, no surprises.

Volume	Price
Per review	$0.0035
Per 1,000 reviews	$3.50

Apify subscription tier discounts apply automatically.

Use cases

• Build a Tripadvisor review database for a hotel chain or restaurant brand for sentiment tracking
• Monitor competitor reviews and management response cadence
• Power LLM agents that summarize traveler feedback for property managers
• Generate trend reports on traveler types, stay dates, and seasonal sentiment
• Track aspect subratings over time (cleanliness, service, value) for revenue management
• Enrich a hotel or restaurant CRM with verified guest review history
• Feed review text into translation or analytics pipelines

Tips for best results

• Use Apify Residential proxies in the US (default). Datacenter proxies work for small runs but DataDome rotates blocks weekly.
• Start with maxReviewsPerProperty: 50 to confirm a target property is alive, then scale up.
• For multi-property runs, pass an array of URLs in startUrls; the actor walks them sequentially and rotates sessions between properties.
• If you only need the latest sentiment, set sortBy: MOST_RECENT and a small maxReviewsPerProperty.
• Restaurant locationIds are sometimes recycled by Tripadvisor; if a known property returns zero reviews, search Tripadvisor again to get the current URL.
• Subratings only appear on hotel reviews; restaurants and attractions return an empty array, as designed.

Compliance

This actor scrapes only public review pages and respects Tripadvisor's server-side review filters (verified, published, public). It does not attempt to access any private content or any data behind a login wall. The actor does not require any user-supplied cookies, session IDs, or login credentials.

Support

If a property returns zero reviews or the actor flags repeated DataDome blocks, leave a message on the actor issue tracker on Apify Console with the property URL. The recon notes for Tripadvisor are kept up to date and most issues resolve with a proxy refresh.