Tripadvisor Reviews Scraper

Extract structured Tripadvisor hotel and restaurant reviews, including review text, ratings, dates, traveller information, management responses and review photos where available.

Scrape multiple location URLs in one run, apply review filters and set a maximum number of reviews per URL. The Actor also saves review aggregations for each location to the key-value store.

Checkout our Trustpilot Scraper here.

n8n node: n8n-nodes-tripadvisor-reviews

Features

• Review filters and sorting: Sort by most relevant or most recent. Filter by language, rating, traveller type and time of year.
• Multiple URLs: Collect reviews from multiple hotels and restaurants in a single run.
• Set limits: Define the maximum number of reviews to scrape per URL.
• Request handling: Uses residential proxies, dynamic request headers and session pooling to help reduce IP blocking.
• Location aggregations: Saves review aggregations separately from individual review records in the run's key-value store.

What data can be extracted?

Data	Available information
Review	ID, title, text, rating, status and review URL
Dates and language	Creation and publication dates, language, original language and translation metadata
Location	Location ID, name, place type and accommodation category where available
Reviewer	Profile ID, display name, username, profile route, avatar, hometown and contribution count
Trip details	Stay date and trip type
Management response	Response text, publication date, language and responder information
Other feedback	Helpful votes, review tips and additional ratings where available
Photos	Review photo IDs, image URL templates, dimensions and captions where available

Fields depend on the review and information returned by Tripadvisor. Management responses, photos, tips and additional ratings may be absent or empty.

Use cases

• Customer feedback analysis — examine guest and diner experiences.
• Sentiment analysis — use review text to research positive and negative feedback.
• Hospitality research — compare feedback across hotels or restaurants.
• Reputation monitoring — collect recent reviews and management responses.
• Traveller research — examine feedback by trip type, rating or time of year.

Supported URLs

Supply Tripadvisor hotel review pages or restaurant review pages in start_urls, as shown below. Multiple location URLs can be included in one run.

Example input

{
  "start_urls": [
    {
      "url": "https://www.tripadvisor.co.uk/Hotel_Review-g60763-d6510520-Reviews-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html"
    },
    {
      "url": "https://www.tripadvisor.co.uk/Restaurant_Review-g60763-d7890999-Reviews-or15-Kuu_Ramen-New_York_City_New_York.html"
    }
  ],
  "original_language": "en",
  "sort_type": "Most Recent",
  "keywords": "",
  "traveller_rating": ["1", "2", "3", "4", "5"],
  "time_of_year": ["January", "February", "March"],
  "max_results": 100
}

This example requests English-language reviews, sorted by most recent, with all five ratings selected, January–March selected and a limit of 100 reviews per URL. See the Input tab for all options, including traveller-type filtering and accepted values.

Example output

Individual reviews are returned as structured JSON records. The shortened record below preserves the original field names and nested structure. The review text and management response are abbreviated from the supplied example.

[
{
  "id": 997181633,
  "locationId": 6510520,
  "status": "PUBLISHED",
  "createdDate": "2025-03-08",
  "publishedDate": "2025-03-08",
  "rating": 4,
  "title": "My Hilton Stay (1 King Bdrm, February 2025)",
  "text": "Perfect location! Right across the street from the 6 subway line. It was easy to get downtown and uptown. \n\nThe room was small but that’s to be expected in NYC. Very clean and my view was great. \n\nThe staff were helpful and friendly. However the restaurant next door (which is part of the hotel) will get a little busy. I was sitting at the bar for the a good 10 minutes with no “hello” or “I’ll be right with you.” I ended up leaving but I did return the following day for a drink \n\nA little noisy. Right now this hotel is going through a renovation process. I heard a lot of equipment machinery from the floors above.  Also the walls are pretty thin. There was a group staying in the room near me and they were loud as hell. The door slams and it’s loud too. Basically you can hear anything. \n\nBesides the noise and the busy restaurant it was a good stay. I would stay again.",
  "reviewTip": {
    "responseData": {
      "tips": [
        {
          "body": "Across the street from the subway \n\nConcierge will hold you bags after check out if you have a late flight",
          "published": true
        }
      ]
    }
  },
  "language": "en",
  "originalLanguage": "en",
  "translationType": null,
  "url": "https://www.tripadvisor.co.uk/ShowUserReviews-g60763-d6510520-r997181633-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html",
  "location": {
    "locationId": 6510520,
    "name": "Hilton Garden Inn New York/Midtown Park Ave",
    "placeType": "ACCOMMODATION",
    "accommodationCategory": "HOTEL",
    "businessAdvantageData": {
      "favoriteReview": {
        "reviewId": 1009933303
      }
    }
  },
  "publishPlatform": "MOBILE",
  "connectionToSubject": null,
  "userProfile": {
    "id": "C2280073D8CDCDBF94C12B948CEA3733",
    "isVerified": false,
    "displayName": "Jonathan S",
    "username": "jmsinatra1",
    "avatar": {
      "__typename": "MemberProfile_MediaId",
      "data": {
        "__typename": "Media_PhotoResult",
        "id": 452388669,
        "photoSizeDynamic": {
          "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/1a/f6/e7/3d/default-avatar-2020-55.jpg?w={width}&h={height}&s=1",
          "maxHeight": 1200,
          "maxWidth": 1200
        }
      }
    },
    "hometown": {
      "locationId": 32999,
      "fallbackString": "32999",
      "location": {
        "locationId": 32999,
        "additionalNames": {
          "name": "Sacramento",
          "long": "Sacramento, California"
        }
      }
    },
    "route": {
      "url": "/Profile/jmsinatra1"
    },
    "contributionCounts": {
      "sumAllUgc": 8
    }
  },
  "mgmtResponse": {
    "id": 997434150,
    "text": "jmsinatra1, thank you for your recent Trip Advisor review!  My team and I are glad that you enjoyed your time with us!  We do hope for another opportunity to serve you again in the future!",
    "language": "en",
    "translationType": null,
    "publishedDate": "2025-03-10",
    "username": "Jon Schorr",
    "connectionToSubject": "Owner",
    "userProfile": {
      "userId": "36CF052EAC1B650B840F1BCC62C222B8",
      "route": {
        "url": "/Profile/JonSchorr"
      },
      "avatar": {
        "__typename": "MemberProfile_MediaId",
        "data": {
          "__typename": "Media_PhotoResult",
          "id": 452391234,
          "photoSizeDynamic": {
            "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/1a/f6/f1/42/default-avatar-2020-20.jpg?w={width}&h={height}&s=1",
            "maxHeight": 1200,
            "maxWidth": 1200
          }
        }
      }
    }
  },
  "helpfulVotes": 0,
  "labels": [],
  "attribution": null,
  "mtProviderId": 0,
  "alertStatus": false,
  "tripInfo": {
    "stayDate": "2025-03-31",
    "tripType": "SOLO"
  },
  "additionalRatings": [],
  "photos": [
    {
      "photo": {
        "__typename": "Media_PhotoResult",
        "id": 792700165,
        "photoSizeDynamic": {
          "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/2f/3f/a5/05/caption.jpg?w={width}&h={height}&s=1",
          "maxWidth": 1536,
          "maxHeight": 2048
        },
        "caption": "",
        "albumId": 100,
        "statuses": [
          "PUBLISHED"
        ]
      }
    },
    {
      "photo": {
        "__typename": "Media_PhotoResult",
        "id": 792700166,
        "photoSizeDynamic": {
          "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/2f/3f/a5/06/caption.jpg?w={width}&h={height}&s=1",
          "maxWidth": 1536,
          "maxHeight": 2048
        },
        "caption": "",
        "albumId": 100,
        "statuses": [
          "PUBLISHED"
        ]
      }
    },
    {
      "photo": {
        "__typename": "Media_PhotoResult",
        "id": 792700167,
        "photoSizeDynamic": {
          "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/2f/3f/a5/07/caption.jpg?w={width}&h={height}&s=1",
          "maxWidth": 1536,
          "maxHeight": 2048
        },
        "caption": "",
        "albumId": 100,
        "statuses": [
          "PUBLISHED"
        ]
      }
    }
  ]
}
]

Location review aggregations

Review aggregations for each location are saved to the run's key-value store. Open that store to retrieve the aggregation records alongside the individual reviews.

AI agents and integrations

Connect chat clients such as Claude and ChatGPT to Apify through the Apify MCP server to discover and run eligible Actors.

Structured review records let agents work directly with review text, ratings, dates and location IDs.

Example requests for an agent configured to use this Actor:

Collect the 100 most recent reviews from this Tripadvisor hotel URL.

Collect one- and two-star reviews from these Tripadvisor restaurant URLs.

Automation and resources

• AI integrations — connect Actors with AI applications and agent frameworks.
• Apify MCP server — setup, authentication and Actor eligibility requirements.
• n8n integration — run Actors and retrieve their results in n8n workflows.
• n8n node: n8n-nodes-tripadvisor-reviews

Notes

• Output format: JSON preserves nested reviewer, response, trip and photo data.
• Field names: Output field names match those returned by Tripadvisor.
• Filtering and limits: Filters restrict the requested reviews; max_results sets the maximum per URL.
• Request blocking: Proxies and session handling help reduce blocking but do not guarantee every request succeeds.

Browse all Datasaurus scrapers.