🏨 TripAdvisor Scraper — Booking.com, Expedia & TripAdvisor Content API Alternative

Scrape TripAdvisor hotels, restaurants, attractions, and reviews — names, ratings, review counts, prices, amenities, photo URLs, traveler reviews with text + rating + date. Built as a pay-per-result alternative to TripAdvisor Content API (enterprise-only), Booking.com Partner API, Expedia EPS API, and manual review-copy workflows for hospitality, OTA aggregators, and consumer-insights teams.

Why TripAdvisor Scraper Beats TripAdvisor Content API, Expedia EPS & Manual Browsing

Feature	NexGenData TripAdvisor Scraper	TripAdvisor Content API	Booking.com Partner	Expedia EPS	Manual browser scrape
Cost	Pay-per-record, no seats	Enterprise contract only	Partner contract only	Partner contract only	Free (slow, breaks)
Hotels + restaurants + attractions	All three verticals	Yes (enterprise)	Hotels only	Hotels only	DIY
Full review text + photos	Yes	Plan-gated	Limited	Limited	Manual
Rating breakdown + bubble scores	Yes	Yes	Limited	Limited	Visible
Bulk export	JSON / CSV / Excel	Enterprise SLA	Partner-only feed	Partner-only feed	Manual
Filters	Location + category + price + rating	Yes	Hotels-only filters	Hotels-only filters	None
API access	Apify REST + SDKs	Enterprise	Partner contract	Partner contract	None
Auth required	Apify token	Enterprise contract	Partner contract + sign-off	Partner contract + sign-off	TripAdvisor login
Monthly minimum	None	$$$$	Affiliate-volume gate	Affiliate-volume gate	None

Most hospitality + consumer-insights teams pick this actor instead of the TripAdvisor Content API because Content API requires an enterprise contract and a use-case approval that excludes most independents; this actor returns the same surface fields with no contract. Cheaper than stacking Booking.com Partner + Expedia EPS feeds for review-text use cases, and a drop-in alternative to maintaining your own TripAdvisor headless scraper against ongoing anti-bot updates.

What You Get

Each dataset item is a flat JSON record:

Hotel / restaurant / attraction:

• name, category (hotel / restaurant / attraction), address, city, country, lat, lng
• rating, review_count, rank_in_city
• price_range, price_per_night (hotels)
• amenities — pool / wifi / parking / etc.
• cuisine, meal_types, dietary_options (restaurants)
• photo_urls, tripadvisor_url
• phone, website, hours

Review:

• review_id, traveler_name, traveler_location
• review_title, review_text, review_rating (1-5)
• review_date, stay_date, trip_type (business / couples / family / solo / friends)
• helpful_votes, language, translated
• response_from_management (when present)

Use Cases

• Hospitality operators — benchmark a property against competitors in the same market
• Revenue managers — track competitor pricing + occupancy signals across a portfolio
• OTA aggregators / metasearch — ingest TripAdvisor inventory into discovery flows
• Consumer-insights teams — sentiment + theme extraction from review text
• Tourism boards + DMOs — track destination perception over time
• Restaurant chains — multi-location review monitoring without a per-seat Reputation.com contract
• Travel-tech builders — train recommenders on rating + review-text data

Quick Start (Python)

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/tripadvisor-scraper").call(run_input={
    "search_urls": ["https://www.tripadvisor.com/Hotels-g60713-San_Francisco_California-Hotels.html"],
    "max_items": 100,
    "include_reviews": True,
    "max_reviews_per_property": 50
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["name"], item["rating"], item["review_count"])

Pricing — Pay Per Record

• Actor start: $0.01
• Property / review record: $0.01

A 100-property + 50-reviews-each pull (5,100 records) = $51.01. A 1,000-property city audit (no reviews) = $10.01. No monthly minimum, no seats.

Related NexGenData Travel + Hospitality Actors

Use case	Actor
Booking.com scraper (hotel prices + reviews)	booking-com-scraper
Airbnb scraper (STR listings + reviews)	airbnb-scraper
Zillow scraper (US property prices)	zillow-scraper
Apartments.com scraper (US rentals)	apartments-com-scraper
Redfin real-estate scraper	redfin-real-estate-scraper
Real-estate MCP server (AI / Claude / GPT)	real-estate-mcp-server
Google Maps MCP server (POI + reviews)	google-maps-mcp-server
Premium data MCP server (multi-source travel)	premium-data-mcp-server

FAQ

Q: Geographic coverage? A: Global — TripAdvisor indexes 8M+ properties across 200+ countries.

Q: Review-text language? A: TripAdvisor returns reviews in their original language plus an English-translated copy when available. Both are captured.

Q: How fresh is the data? A: Each run pulls live. Hotel prices update intra-day; review counts update as reviews are submitted.

Q: Schema stability? A: Versioned schema; breaking changes are announced via the actor changelog.

Q: Legal status? A: Public listing + review content from public pages. You are the data controller for downstream use — follow your jurisdiction's data-use rules.

Q: Output formats? A: JSON, CSV, Excel via Apify dataset export. Webhooks supported on dataset write.

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How NexGenData Pricing Works

Every NexGenData actor uses pay-per-event pricing — you only pay for results that actually land in your dataset. No monthly minimum, no seat fees, no surprise overage bills.

• Actor Start: a single-event charge each time you spin the actor up (scaled to memory size)
• Result / item: charged per item written to the default dataset
• No charge for retries, internal proxy rotation, or failed sub-requests — those are absorbed by the platform

Apify Platform Bonus

New to Apify? Sign up with the NexGenData referral link — you get free platform credits on signup (enough for several thousand free results) and you help fund the maintenance of this actor fleet.

Integration Surface

Every actor in the NexGenData catalog can be triggered from:

• Apify console — point-and-click run
• Apify API — REST + webhooks
• Apify Python / JS SDKs — programmatic batch
• Zapier, Make.com, n8n — official integrations
• MCP — many actors are exposed as MCP tools for Claude / ChatGPT / Cursor agents
• Schedules — built-in cron for daily / weekly / monthly runs
• Webhooks — POST results to any HTTPS endpoint on dataset write

Support

NexGenData maintains 260+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get a response within 24 hours. Roadmap requests are welcome — high-demand features ship in the next version.

Home: thenextgennexus.com Full catalog: apify.com/nexgendata