TripAdvisor URL Parser

The only universal TripAdvisor URL parser on Apify Store. Drop in any TripAdvisor URL - hotel detail, restaurant page, attraction listing, reviews page, geo landing - and the actor auto-detects the page type and returns the matching structured payload. Optionally pulls reviews for each hotel / restaurant / attraction URL in the same run, so one input covers both the place and its reviews. No more wiring up six different scrapers to handle six URL patterns. One actor, one input, one consistent dataset.

Built for growth teams scraping competitor inventory, travel-research analysts pulling thousands of locations, and engineers who want one API across TripAdvisor surfaces. Drop a URL → get a row (or, with reviews enabled, a row plus N more).

Why this Actor?

Capability	TripAdvisor URL Parser (Data Forge)	Typical single-vertical scrapers
Setup before you parse a URL	Zero config - paste the URL, page type is auto-detected	Pick the right per-vertical scraper first
Page types from one input	8 auto-detected (hotel, restaurant, attraction, 3 listings, reviews, geo)	1 vertical per actor
Entity plus its reviews in a single run	Yes, via maxReviewsPerEntity	2 separate runs or actors
Review sort control	5 orders (most_relevant, newest, oldest, highest, lowest)	Fixed order or none
Review language filter	14+ language codes	Usually English only
Locale domains covered	9 (.com, .co.uk, .de, .fr, .es, .it, .ca, .com.au, .co.jp)	Mostly .com
Output shape	Typed rows (hotel_detail, review, restaurants_listing, and more)	Mixed, per-tool shapes
Billing	Pay per result (per parsed URL, plus $0.001 per review row)	Monthly seat or per-page

What it does

• Accepts 1 to 500 TripAdvisor URLs in a single run.
• Auto-detects the page type from the URL pattern - 8 supported types (hotel detail, restaurant detail, attraction detail, reviews, hotels listing, restaurants listing, attractions listing, geo landing).
• Works across 9 locales: .com, .co.uk, .de, .fr, .es, .it, .ca, .com.au, .co.jp.
• Optional reviews fan-out: for any hotel / restaurant / attraction URL the actor can paginate reviews (up to 5,000 per place) and emit each review as its own dataset row - ready for SQL / Pandas / Excel without extra parsing.
• Survives mid-batch failures with stopOnError=false (default): failing URLs are recorded inline with error_code and the run continues.
• Per-event pricing - only pay for what you actually scrape. Cheap geo lookups stay cheap, reviews bill per row.

Input modes

Three ready-to-run recipes, each mapped 1:1 to a published example task. The URL below is Le Bristol Paris - swap in any of your own TripAdvisor URLs.

1. Parse any URL (zero config)

Analyst grabbing one entity fast: paste a single URL and get a structured row back, no vertical to choose.

{
  "urls": ["https://www.tripadvisor.com/Hotel_Review-g187147-d188729-Reviews-Le_Bristol_Paris-Paris_Ile_de_France.html"]
}

2. Parse the entity plus its reviews

Reputation team that wants the hotel record AND up to 100 of its reviews in one run - each review lands as its own row.

{
  "urls": ["https://www.tripadvisor.com/Hotel_Review-g187147-d188729-Reviews-Le_Bristol_Paris-Paris_Ile_de_France.html"],
  "maxReviewsPerEntity": 100
}

3. Newest reviews first

Monitoring fresh guest sentiment: pull the 100 latest reviews sorted newest-first so today's feedback sits at the top.

{
  "urls": ["https://www.tripadvisor.com/Hotel_Review-g187147-d188729-Reviews-Le_Bristol_Paris-Paris_Ile_de_France.html"],
  "maxReviewsPerEntity": 100,
  "reviewSort": "newest"
}

Input reference

{
  "urls": [
    "https://www.tripadvisor.com/Hotel_Review-g60763-d1218720-Reviews-The_Plaza-New_York_City_New_York.html",
    "https://www.tripadvisor.com/Restaurants-g187147-Paris_Ile_de_France.html",
    "https://www.tripadvisor.com/Attraction_Review-g187147-d188151-Reviews-Eiffel_Tower-Paris_Ile_de_France.html"
  ],
  "stopOnError": false,
  "maxReviewsPerEntity": 20,
  "reviewLanguage": "en",
  "reviewSort": "most_relevant"
}

Field	Type	Required	Description
urls	array of strings	✅	1-500 TripAdvisor URLs from any of the 9 supported locales
stopOnError	boolean	optional, default false	If true, abort the run on the first failing URL. Default skips and records the failure inline
maxReviewsPerEntity	integer 0-5000	optional, default 0	When set above 0, each hotel / restaurant / attraction URL also fans out into per-review rows (up to this many per place). Each review charges url-parsed-review at $0.001. Ignored for destination / listing / reviews-page URLs
reviewLanguage	string	optional, default en	TripAdvisor language code (e.g. en, fr, de, es, it, ja, zh) or all. Applied only when maxReviewsPerEntity > 0
reviewSort	enum	optional, default most_relevant	One of: most_relevant, newest, oldest, highest, lowest. Applied only when maxReviewsPerEntity > 0

Output

One dataset row per input URL (plus one row per fanned-out review when maxReviewsPerEntity > 0). On success, type and data are populated; on failure, error_code and error_message are populated instead.

Detail row example

{
  "input_url": "https://www.tripadvisor.com/Hotel_Review-g60763-d1218720-Reviews-The_Plaza-New_York_City_New_York.html",
  "type": "hotel_detail",
  "data": {
    "location_id": 1218720,
    "name": "The Plaza",
    "rating": 4.5,
    "review_count": 1487,
    "address": "768 5th Ave, New York City, NY 10019",
    "amenities": ["Free Wifi", "Bar/lounge", "Concierge"],
    "rooms": [{"name": "Deluxe King", "price_min": 895}],
    "photos": [{"url": "https://media-cdn.tripadvisor.com/media/photo.jpg"}]
  }
}

Per-review row example (when maxReviewsPerEntity > 0)

{
  "input_url": "https://www.tripadvisor.com/Hotel_Review-g60763-d1218720-Reviews-The_Plaza-New_York_City_New_York.html",
  "type": "review",
  "parent_type": "hotel_detail",
  "parent_location_id": "1218720",
  "data": {
    "rating": 5,
    "title": "Outstanding stay",
    "text": "Beautiful suite, attentive staff, flawless service.",
    "language": "en",
    "traveler_type": "couples",
    "published_date": "2026-04-12",
    "helpful_votes": 3,
    "photos": []
  }
}

parent_location_id is what you JOIN on to link reviews back to their parent hotel / restaurant / attraction row in the same dataset.

Console table view

🔗 URL slug	🏷 Type	📦 Payload	🪪 Parent location ID	❌ Error
Hotel_Review-d1218720-The_Plaza	hotel_detail	17 fields incl. rooms + photos	-	-
Hotel_Review-d1218720-The_Plaza	review	one review (rating, text, language)	1218720	-
Restaurants-g187147-Paris	restaurants_listing	paginated restaurant cards	-	-
Attraction_Review-d188151-Eiffel_Tower	attraction_detail	14 fields incl. awards	-	-
Hotel_Review-d99999-BrokenLink	-	-	-	NOT_FOUND

What data contains by type

Type	Payload
hotel_detail	17 fields: location_id, name, rating, review_count, address, amenities[], rooms[], photos[], lowest_offer + OTA prices
restaurant_detail	15 fields: id, name, cuisine, price_range, hours, location, photos[]
attraction_detail	14-15 fields: id, name, category, duration, awards[], reviews_count
review	one review row (rating, title, text, language, traveler_type, published_date, helpful_votes, photos) with parent_type + parent_location_id set
reviews	paginated reviews page (when the URL itself is a -Reviews-orN- page)
hotels_listing / restaurants_listing / attractions_listing	full SERP for the geo with filters applied
location	destination metadata (name, geoId, region, country, photos)

Error codes

error_code	Meaning
NOT_FOUND	TripAdvisor returned no payload for this URL (deleted listing, broken slug, regional removal)
UPSTREAM_BLOCKED	Anti-bot challenge wasn't bypassed - retry the run later
INVALID_URL	URL didn't match any known TripAdvisor pattern
INTERNAL_ERROR	Something else broke - see error_message

FAQ

Is it legal to scrape TripAdvisor? The actor reads publicly visible pages only - the same information any visitor sees. You are responsible for using the output in line with TripAdvisor's terms and applicable law (for example GDPR when review text contains personal data). Data Forge does not bypass logins or paywalls.

Which URL shapes are supported? 8 page types across 9 locale domains: hotel detail (URLs beginning Hotel_Review-), restaurant detail (Restaurant_Review-), attraction detail (Attraction_Review-), the 3 listing pages (Hotels-, Restaurants-, Attractions-), reviews pages (the -Reviews-orN- variant) and geo / destination landings (Tourism-). Paste them mixed into one urls array of up to 500 items.

How fresh is the data? Each run fetches live from TripAdvisor, so you get current ratings, prices and review text at run time - nothing is served from a stale cache.

Can I schedule recurring runs? Yes. Use the Apify Scheduler to run this actor on a cron (for example daily at 06:00, or weekly), and trigger downstream systems with webhooks or the Apify API. Pair it with reviewSort: "newest" to capture just the latest reviews each cycle.

How am I billed? Pay per result: a per-URL event for each parsed page, plus $0.001 per review row when maxReviewsPerEntity is above 0. A geo lookup that returns no reviews stays cheap; a 500-review deep pull bills 500 rows.

How many URLs can one run take? 1 to 500 URLs per run. Keep stopOnError: false (default) so one bad URL never sinks the batch - failures are recorded inline with an error_code and the run keeps going.

Related actors

Part of the Data Forge TripAdvisor suite - pick the actor that fits the job:

• TripAdvisor Hotels, Restaurants & Cruises Scraper - search a whole destination across 5 verticals (hotels, restaurants, things to do, vacation rentals, cruises).
• TripAdvisor Reviews Scraper - bulk-pull reviews at volume from a list of hotels, restaurants or attractions.

Support

I support customers directly - reach out on any channel for help, higher limits, or custom scraping: