🧭 Tripadvisor Reviews & Places Scraper - Extract Tripadvisor Data at Scale

Fast, request-based Tripadvisor scraper for Apify. Search Tripadvisor by keyword or scrape direct Tripadvisor URLs, then extract reviews, ratings, addresses, photos, owner responses, contact details, coordinates, and clean place data - without running a headless browser.

Scrape hotels, restaurants, attractions, tours, and other Tripadvisor listings. Start from search keywords like Paris restaurants or from direct Tripadvisor review URLs. Export clean data to JSON, CSV, Excel, XML, RSS, Google Sheets, Make, Zapier, n8n, or your own API pipeline.

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🔥 What does this Actor do?

Tripadvisor Reviews & Places Scraper turns public Tripadvisor pages into structured datasets. Use it to:

• 🏨 Scrape hotel reviews - ratings, guest text, dates, trip type, owner replies, reviewer profile details
• 🍽️ Collect restaurant data - rating, review count, phone, address, website, images, review text
• 🎟️ Extract attraction and tour reviews - landmarks, museums, tours, experiences, and things to do
• 🔎 Search Tripadvisor by keyword - city, category, landmark, brand, restaurant name, or hotel name
• 🔗 Scrape exact Tripadvisor URLs - paste direct listing URLs when you already know the pages
• 🖼️ Display images directly in Apify datasets - imageUrl is rendered as an image preview
• 📍 Enrich travel directories - address, geo coordinates, phone, website, country, city, category
• 📊 Build review monitoring dashboards - filter by rating, date range, place, and source query
• 🤖 Feed AI and BI workflows - sentiment analysis, lead enrichment, reputation tracking, competitor research

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⚙️ Two ways to scrape Tripadvisor

Mode 1 - SEARCH: discover places from keywords

Provide search queries such as:

• New York City hotels
• Paris restaurants
• London attractions
• Eiffel Tower
• Grand Canyon tours

The Actor searches Tripadvisor, picks matching places, then fetches place details and reviews.

Mode 2 - URL: scrape exact Tripadvisor pages

Provide direct Tripadvisor URLs when you already know the listings:

• hotel review pages
• restaurant review pages
• attraction review pages
• activity or tour review pages
• cruise review pages

💡 Pro tip: use precise queries with city + category, for example Amsterdam restaurants or Paris France hotels. If a query is ambiguous, adding country or region improves matching.

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🧩 Data flow

searchQueries / startUrls
        |
        v
Tripadvisor search and detail pages
        |
        v
Request-based fetcher with retries and proxy support
        |
        v
Place parser + review parser
        |
        v
Default dataset + places / errors / summary datasets

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📥 Input examples

Search hotels and scrape reviews

{
  "searchQueries": ["New York City hotels"],
  "category": "hotels",
  "maxPlacesPerQuery": 5,
  "includeReviews": true,
  "maxReviewsPerPlace": 20,
  "maxConcurrency": 3,
  "outputMode": "reviews"
}

Scrape direct Tripadvisor URLs

{
  "startUrls": [
    {
      "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"
    }
  ],
  "includeReviews": true,
  "maxReviewsPerPlace": 50,
  "outputMode": "reviews"
}

Collect place details only

{
  "searchQueries": ["restaurants in Paris"],
  "category": "restaurants",
  "maxPlacesPerQuery": 25,
  "includeReviews": false,
  "maxReviewsPerPlace": 0,
  "outputMode": "places"
}

Track recent negative reviews

{
  "searchQueries": ["London hotels"],
  "category": "hotels",
  "maxPlacesPerQuery": 10,
  "includeReviews": true,
  "maxReviewsPerPlace": 100,
  "reviewRatings": ["1", "2"],
  "recentDays": 30,
  "outputMode": "reviews"
}

Export both places and reviews

{
  "searchQueries": ["Rome restaurants", "Barcelona restaurants"],
  "category": "restaurants",
  "maxPlacesPerQuery": 3,
  "includeReviews": true,
  "maxReviewsPerPlace": 10,
  "outputMode": "both"
}

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📋 Input schema

Field	Type	Default	Description
searchQueries	array	["New York City hotels"] when no input is provided	Keywords used to find Tripadvisor places.
startUrls	array	[]	Direct Tripadvisor hotel, restaurant, attraction, activity, or cruise review URLs.
category	string	all	all, hotels, restaurants, or attractions. In all, the Actor can infer obvious categories from the query.
maxPlacesPerQuery	integer	20	Maximum places to take from each search query. Range: 1 to 500.
includeReviews	boolean	true	Fetch review pages for every discovered place.
maxReviewsPerPlace	integer	50	Maximum reviews per place. Set 0 to collect place details only.
reviewRatings	array	[]	Keep only selected ratings, for example ["1", "2"] or ["4", "5"].
recentDays	integer	0	Keep only reviews from the last N days when an exact date is available.
outputMode	string	reviews	Default dataset content: reviews, places, or both.
locale	string	en-US	Tripadvisor locale used for search and page requests.
proxyConfiguration	object	Apify Residential Proxy	Proxy settings. Residential proxies are recommended for larger runs.
maxConcurrency	integer	3	Number of place pages fetched in parallel. Range: 1 to 10. Use 1 for the cheapest/safest test run.
requestDelayMs	integer	350	Delay between requests in milliseconds. Increase for larger runs.
maxRetries	integer	4	Retry budget for blocked, timed out, or temporarily failed requests.

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📤 Output datasets

The Actor writes results to the default dataset and also creates helper datasets.

Dataset	What it contains
Default dataset	Controlled by outputMode: reviews, places, or both.
places	One row per Tripadvisor place. Best for directories, lead enrichment, and maps.
errors	Failed URLs, unsupported URLs, search errors, or page fetch problems.
summary	Run totals, request stats, errors count, runtime, and client metrics.

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🧾 Review item schema

Every review row is enriched with place details so CSV and Excel exports are easy to analyze without joins.

Field	Type	Description
itemType	string	Always review.
reviewId	string	Tripadvisor review ID.
reviewUrl	string	Direct URL to the review.
title	string	Review title.
text	string	Full review text visible on the page.
rating	number	Review rating from 1 to 5.
publishedDateText	string	Original date text from Tripadvisor.
publishedDate	string	Normalized date when possible, such as 2026-06-27 or 2025-07.
dateOfStay	string	Date of stay, visit, or experience when visible.
tripType	string	Trip type such as Family, Couples, Friends, Business, or Solo.
helpfulVotes	integer	Helpful vote count when visible.
photoCount	integer	Number of photos attached to the review when visible.
isMachineTranslated	boolean	Whether Tripadvisor marks the review as machine translated.
reviewerName	string	Public reviewer display name.
reviewerLocation	string	Public reviewer location when visible.
reviewerContributions	integer	Public reviewer contribution count when visible.
ownerResponseText	string	Owner or management response text.
ownerResponseDateText	string	Owner response date text.
ownerResponseAuthor	string	Owner response author or role.
placeName	string	Name of the reviewed place.
placeUrl	string	Tripadvisor URL of the place.
locationId	integer	Tripadvisor location ID.
parentGeoId	integer	Tripadvisor parent geo ID.
category	string	hotel, restaurant, attraction, or place.
placeRating	number	Overall Tripadvisor place rating.
placeReviewCount	integer	Total Tripadvisor review count for the place.
address	string	Full address when available.
city	string	City.
region	string	Region or state.
postalCode	string	Postal code.
country	string	Country.
latitude	number	Latitude.
longitude	number	Longitude.
phone	string	Phone number.
website	string	Official website when listed.
imageUrl	string	Primary image URL. Rendered as an image preview in the Apify dataset table.
thumbnailUrl	string	Search thumbnail URL when available.
searchQuery	string	Source search query.
snippet	string	Search result snippet.
mentionCount	integer	Search mention count when available.
source	string	Discovery source, such as search or startUrl.
sourceUrl	string	URL used for the source page request.
crawledAt	string	ISO timestamp of the run.

---

📍 Place item schema

Field	Type	Description
itemType	string	Always place.
name	string	Place name.
category	string	hotel, restaurant, attraction, or place.
locationId	integer	Tripadvisor location ID.
parentGeoId	integer	Tripadvisor parent geo ID.
url	string	Canonical Tripadvisor place URL.
rating	number	Overall place rating.
reviewCount	integer	Total review count.
priceRange	string	Price range when available.
phone	string	Phone number.
website	string	Official website when listed.
address	string	Full address.
city	string	City.
region	string	Region or state.
postalCode	string	Postal code.
country	string	Country.
latitude	number	Latitude.
longitude	number	Longitude.
amenities	array	Amenities when listed in structured data.
imageUrl	string	Primary image URL. Rendered as an image preview in the Apify dataset table.
images	array	Full image URL list from structured data.
description	string	Meta description or listing description.
snippet	string	Search result snippet.
mentionCount	integer	Search mention count when available.
thumbnailUrl	string	Search thumbnail URL.
searchQuery	string	Source search query.
source	string	Discovery source, such as search or startUrl.
sourceUrl	string	URL used for the source page request.
crawledAt	string	ISO timestamp of the run.

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🧪 Example output

Review row

{
  "itemType": "review",
  "reviewId": "1065913654",
  "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g187147-d12714552-r1065913654-Pizzeria_Arrivederci-Paris_Ile_de_France.html",
  "title": "Wonderful",
  "text": "The best pizza in Paris. Super thin and flavorful. Gorgeous ingredients, lovely atmosphere, and kind service. We will be back!",
  "rating": 5,
  "publishedDateText": "June 27, 2026",
  "publishedDate": "2026-06-27",
  "dateOfStay": "Jun 2026",
  "tripType": "Couples",
  "reviewerName": "Morgan D",
  "reviewerLocation": "Los Angeles, California",
  "placeName": "Pizzeria Arrivederci",
  "category": "restaurant",
  "placeRating": 4.9,
  "placeReviewCount": 6432,
  "city": "Paris",
  "country": "FR",
  "imageUrl": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/31/36/7e/8e/the-best-pizza-in-paris.jpg?w=500&h=-1&s=1",
  "searchQuery": "Paris restaurants"
}

Place row

{
  "itemType": "place",
  "name": "Pizzeria Arrivederci",
  "category": "restaurant",
  "locationId": 12714552,
  "parentGeoId": 187147,
  "url": "https://www.tripadvisor.com/Restaurant_Review-g187147-d12714552-Reviews-Pizzeria_Arrivederci-Paris_Ile_de_France.html",
  "rating": 4.9,
  "reviewCount": 6432,
  "priceRange": "$$ - $$$",
  "phone": "+33 1 77 32 45 57",
  "address": "47 rue Gay Lussac, Paris, Ile-de-France, 75005, FR",
  "city": "Paris",
  "region": "Ile-de-France",
  "postalCode": "75005",
  "country": "FR",
  "latitude": 48.84172,
  "longitude": 2.343511,
  "imageUrl": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/31/36/7e/8e/the-best-pizza-in-paris.jpg?w=500&h=-1&s=1",
  "images": [
    "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/31/36/7e/8e/the-best-pizza-in-paris.jpg?w=500&h=-1&s=1"
  ],
  "searchQuery": "Paris restaurants"
}

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🛡️ Request-based scraping, no browser

This Actor is built to be lightweight:

• No Playwright / Puppeteer browser - lower memory usage and cheaper runs
• HTTP requests with browser-like TLS impersonation - the request layer behaves closer to a real browser connection
• Session warm-up before scraping - helps obtain the cookies needed for Tripadvisor pages
• Retries with session refresh - temporary blocks and network failures are retried
• Parallel place fetching - maxConcurrency speeds up multi-place runs while keeping retries and proxy sessions isolated
• Residential proxy support - recommended for bigger jobs and more stable production runs
• Polite request delay - configurable via requestDelayMs

Tripadvisor can still apply traffic protection or change its page layout. For large runs, keep proxies enabled, start with a small sample, and increase limits gradually.

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💼 Use cases

• 📈 Reputation monitoring for hotels, restaurants, attractions, and local businesses
• 🎯 Lead generation for travel, hospitality, restaurants, agencies, and tourism products
• 📊 Competitor analysis by review volume, rating, owner replies, and guest complaints
• 🤖 Sentiment analysis and AI pipelines using review text and rating filters
• 🌍 Travel directory enrichment with addresses, websites, coordinates, images, and categories
• 🔔 Negative review alerts with reviewRatings and recentDays
• 🧾 Market research across cities, categories, and specific Tripadvisor places
• 🔌 Automation workflows with Apify integrations, webhooks, Google Sheets, Make, Zapier, and n8n

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💰 Cost notes

This Actor is designed to be cheaper than browser-based scrapers because it does not run a headless browser. Your final cost depends on:

• number of search queries
• maxPlacesPerQuery
• maxReviewsPerPlace
• proxy configuration
• maxConcurrency
• request delay and retries
• selected Apify plan and Actor pricing settings

For a quick test, use maxPlacesPerQuery: 1, maxReviewsPerPlace: 3, and maxConcurrency: 1. For production, increase limits gradually.

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❓ FAQ

Q: Do I need a Tripadvisor API key?
No. The Actor extracts publicly visible Tripadvisor data from the website.

Q: Can I scrape only places without reviews?
Yes. Set includeReviews to false, maxReviewsPerPlace to 0, and outputMode to places.

Q: Can I scrape direct Tripadvisor URLs?
Yes. Add direct URLs to startUrls. You can combine startUrls with searchQueries in one run.

Q: Can I filter by star rating?
Yes. Use reviewRatings, for example ["1", "2"] for negative reviews or ["4", "5"] for positive reviews.

Q: Can I filter recent reviews?
Yes. Use recentDays. Exact daily filtering is applied when Tripadvisor exposes an exact review date. Month-only dates are kept because the exact day is not available.

Q: Why are some fields missing from some rows?
Tripadvisor does not expose every field on every listing or review card. Empty values are omitted to keep the output clean.

Q: Why are there both imageUrl and images?
imageUrl is the primary image and is shown directly in the Apify dataset table. images is the full image URL array for users who need all available images.

Q: What proxy should I use?
Residential proxies are recommended for larger runs. The default input already uses Apify Residential Proxy.

Q: Can I export to CSV or Excel?
Yes. Apify datasets can be exported to JSON, CSV, Excel, XML, RSS, and HTML. You can also access results with the Apify API.

Q: What happens if a page fails?
Failed URLs or search errors are saved to the errors helper dataset. The summary dataset also reports totals and failure counts.

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🛠️ Run locally

pip install -r requirements.txt
apify run

Deploy to Apify:

$apify push

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🏷️ Tags

tripadvisor scraper · tripadvisor reviews · tripadvisor api · hotel reviews scraper · restaurant reviews scraper · travel data scraper · tourism data · review monitoring · sentiment analysis · hospitality analytics · attraction scraper · places scraper · restaurant data · hotel data · tripadvisor dataset · apify tripadvisor · travel lead generation · reviews api · web scraping

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🧑‍💻 Support and feature requests

If you find a bug, a page type that is not covered yet, or a field you want added, open an issue on the Actor page and include:

• the Tripadvisor URL or search query
• what you expected to get
• what was missing or incorrect
• a small sample of your run input if possible

Feature requests are welcome. If Tripadvisor exposes the data publicly, it can usually be added.

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🔗 Built for Apify · Request-based · No browser · Search + direct URLs · Reviews + places · Image previews