TripAdvisor Reviews Scraper — $0.40 per 1,000 Reviews 💰

The cheapest TripAdvisor reviews scraper on Apify. Extract hotel, restaurant, and attraction reviews, including full review text, star ratings, trip type, stay date, reviewer profiles, owner responses and photos — for $0.40 per 1,000 reviews. Built for hotel review monitoring, reputation management, guest feedback analysis, and travel market research.

Main Use Cases

• Hotel review monitoring — track every new review for the properties you manage, own, or invest in.
• Hotel reputation monitoring & competitive analysis — compare your place against competitors across cities and chains.
• Guest feedback analysis — understand what drives 1-star vs 5-star sentiment for your property.
• Travel market research — build structured TripAdvisor review datasets for pricing, positioning, and market-entry decisions.
• Restaurant reputation management — monitor reviews across all your food & beverage locations.
• AI & LLM training data — package clean, structured review datasets for sentiment models and travel chatbots.

How It Works

Paste one or more TripAdvisor review page URLs (hotels, restaurants, attractions, or vacation rentals) into startUrls, set how many reviews you want per place with maxReviews, and run. The actor fetches each place's public review page, then reads the remaining review pages through the same internal TripAdvisor data endpoint the public page itself uses — so you get complete pagination (up to 5,000 reviews per place) without getting blocked.

Each review is returned as structured JSON: rating, full text, publication date, trip type, stay date, helpful votes, reviewer profile, owners' responses, and photos — plus the place header with rank, address, overall rating, sub-ratings, and amenities.

Input

All input fields, straight from the input schema:

Field	Type	Required	Default	Notes
startUrls	Array of { url } request sources	✅ Yes	—	One or more TripAdvisor review page URLs (hotel, restaurant, attraction, vacation rental). The run fails if this is empty.
maxReviews	Integer	No	50	Maximum number of reviews to extract per place. Range 1–5,000.
maxRequestsPerCrawl	Integer	No	100	Cap on HTML page fetches. Each place page is fetched once; deeper pagination is handled by TripAdvisor's internal data endpoint and is not limited by this field.
proxyConfiguration	Object	No	—	Apify proxy configuration for the HTML fetch phase (helps when TripAdvisor rate-limits).

Output

The actor stores every review as a dataset item. The main output fields:

Field	Description
reviewId	Unique review ID on TripAdvisor
placeName, placeUrl	The place the review belongs to, with its TripAdvisor URL
rating	Star rating (1–5)
title, text, language	Review title, full review text, and detected language
publishedDate, createdDate	Publication date and creation date
helpfulVotes	Number of helpful votes the review received
tripType	Trip type (Business, Couples, Family, Solo, Friends)
stayDate	Stay / visit date (month)
connectionToSubject	Filter tag (e.g. Business)
reviewer	Reviewer profile: username, display name, profile URL, hometown, contribution count, helpful votes, avatar, verified badge
ownerResponse	Owner/management response with responder name and date (if one exists)
photos	Review photo URLs and captions (if present)
placeHeader	Place metadata: rank, address, overall rating, review count, sub-ratings, amenities, star rating, style rankings

Example Input

A minimal run for one hotel:

{
  "startUrls": [
    {
      "url": "https://www.tripadvisor.com/Hotel_Review-g39299-d92889-Reviews-Cincinnati_Marriott_at_RiverCenter-Covington_Kentucky.html"
    }
  ],
  "maxReviews": 100
}

A multi-place run mixing hotels, restaurants, and attractions:

{
  "startUrls": [
    { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93361-Reviews-The_Plaza-New_York_City_New_York.html" },
    { "url": "https://www.tripadvisor.com/Restaurant_Review-g60763-d425787-Reviews-Katz_s_Deli-New_York_City_New_York.html" },
    { "url": "https://www.tripadvisor.com/Attraction_Review-g187147-d188151-Reviews-Eiffel_Tower-Paris_Ile_de_France.html" }
  ],
  "maxReviews": 200
}

Example Output

One dataset item per review:

{
  "reviewId": "R123456789",
  "placeName": "Cincinnati Marriott at RiverCenter",
  "placeUrl": "https://www.tripadvisor.com/Hotel_Review-g39299-d92889-Reviews-Cincinnati_Marriott_at_RiverCenter-Covington_Kentucky.html",
  "rating": 5,
  "title": "Great river view and friendly staff",
  "text": "We stayed here for a conference weekend and loved the view over the Ohio river...",
  "language": "en",
  "publishedDate": "2025-09-14T00:00:00.000Z",
  "createdDate": "2025-09-14T00:00:00.000Z",
  "helpfulVotes": 3,
  "tripType": "Business",
  "stayDate": "2025-09",
  "connectionToSubject": "Business",
  "reviewer": {
    "username": "TravelBug88",
    "displayName": "TravelBug88",
    "profileUrl": "https://www.tripadvisor.com/Profile/TravelBug88",
    "hometown": "Columbus, Ohio",
    "contributionCount": 23,
    "helpfulVotes": 41,
    "isVerified": false
  },
  "ownerResponse": {
    "text": "Thank you for the kind words — we hope to welcome you back!",
    "publishedDate": "2025-09-16T00:00:00.000Z",
    "responderName": "General Manager"
  },
  "photos": [
    {
      "id": "P340012",
      "url": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/12/ab/34/cd/...",
      "caption": "Hotel lobby"
    }
  ],
  "placeHeader": {
    "name": "Cincinnati Marriott at RiverCenter",
    "rank": "#12 of 49 hotels in Covington",
    "address": "#10 West RiverCenter Blvd, Covington, KY 41011",
    "rating": 4.3,
    "reviewCount": 3812,
    "subRatings": { "Location": 4.5, "Cleanliness": 4.4, "Service": 4.2, "Value": 4.0 },
    "starRating": 4
  }
}

Extract TripAdvisor Review Data for Downtime-Free Dashboards

The actor runs serverless on Apify's cloud, so monitoring dashboards and reputation tools keep running even when your machine is off. Reviews are written to an Apify dataset, ready to pull over the API or export as JSON, CSV, or Excel.

Integrations & Automation

• Apify API — trigger runs and pull review data programmatically.
• Webhooks — notify your team the moment a run finishes and new reviews arrive.
• Zapier / Make — pipe new reviews into Slack, Sheets, or your CRM.
• Scheduling — run this actor on a schedule. For reputation dashboards, a weekly run is the standard cadence (a typical hotel receives 1–10 new reviews per week); use daily runs during launches, events, or crisis monitoring.

Related Actors

• maxcopell/tripadvisor — the broad TripAdvisor data toolkit
• maxcopell/tripadvisor-reviews — TripAdvisor review extraction, Apify's official actor
• h_reviews/hotel-review-aggregator — multi-platform hotel review aggregation
• memo23/booking-reviews-scraper — Booking.com reviews for cross-OTA comparison
• tri_angle/restaurant-review-aggregator — restaurant ratings from multiple platforms

FAQ

Why use this actor instead of the official TripAdvisor API?

The official TripAdvisor Content API exists, but it is gated — you must apply and be approved — and it returns only around 3 reviews per location, only for properties you manage, and without owner responses, sub-ratings, or reviewer profiles. This actor returns up to 5,000 full reviews per place, with owner responses, photos, and place metadata, from public pages — no approval required, at $0.40 per 1,000 reviews.

Is scraping TripAdvisor legal?

Scraping publicly available TripAdvisor review pages for research and reputation management is generally accepted practice, but TripAdvisor's Terms of Service prohibit automated scraping, and reviewer profiles can contain personal data under GDPR/CCPA. You are responsible for using the data in compliance with TripAdvisor's ToS and applicable law (see the disclaimer below).

What are the alternatives to this actor / TripAdvisor API alternatives?

For direct scraping: this actor is the cheapest verified option on Apify (see the comparison table below). Managed review-data providers that offer TripAdvisor coverage include Repuso, DataForSEO, SocialCrawl, StayAPI, and Olery — if you prefer an out-of-the-box SaaS API over running scrapers yourself. For cross-platform hotel feedback, pair this actor with a Booking.com reviews scraper (see Related Actors).

TripAdvisor vs Google reviews — which should you analyze?

TripAdvisor reviews are typically longer, richer, and travel-intent-focused (trip type, stay date, sub-ratings), which makes them ideal for guest feedback and reputation research. Google reviews have higher raw volume. The common recommendation is to analyze both — TripAdvisor for structured travel feedback, Google for overall volume and local SEO signals.

How often should I monitor TripAdvisor reviews?

Weekly is the standard cadence for hotels and restaurants; a typical property gains 1–10 new reviews a week. During peak seasons, launches, or reputation crises, switch to daily runs. Scheduling is built into Apify and costs nothing extra.

How do I export TripAdvisor reviews to CSV or Excel?

Every run writes to an Apify dataset, which you can download as JSON, CSV, XLSX, or HTML directly from the run page or via the API. No additional transformation step is needed.

Can I scrape TripAdvisor reviews in languages other than English?

Yes. TripAdvisor serves localized content per domain — paste review URLs from tripadvisor.de, .fr, .it, .es, .mx, .br, .co.uk, .jp, .kr, .in, and other domains and the reviews are returned in that language.

Competitive Positioning

Verified pricing on Apify Store as of September 2026 — the cheapest TripAdvisor reviews scraper on the platform at its lowest tier:

Capability	Other TripAdvisor review scrapers	This actor
Price per 1,000 reviews (lowest tier)	$0.50 (api-ninja, theagents, thewolves) · $1.90 (maxcopell/tripadvisor-reviews) · $3.60 (h_reviews aggregator)	$0.40
Hosting / startup posture	CDN-backed instant starts advertised (api-ninja, thewolves)	Serverless on Apify cloud — no server hosting to manage
Reviews per place (paid runs)	Model-specific	Up to 5,000 with full pagination

Why switch: it is the same public-data extraction job at roughly 20–25% of the cost of the closest mid-tier competitor per 1,000 reviews, with no server to manage and full review pagination.

SEO Keywords

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For AI Agents & LLM Apps

Purpose: returns structured TripAdvisor reviews (full text, rating, trip type, stay date, profile, owner response, photos) plus place metadata, as JSON dataset items.

Minimal working input:

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

Variant input — across place types: add multiple startUrls entries (hotels, restaurants, attractions, vacation rentals); each entry gets up to maxReviews reviews.

Output fields: reviewId, placeName, placeUrl, rating, title, text, language, publishedDate, createdDate, helpfulVotes, tripType, stayDate, connectionToSubject, reviewer (profile object), ownerResponse (nullable), photos (array), placeHeader (rank, address, rating, reviewCount, subRatings, amenities, starRating).

Behaviors an agent should know:

• startUrls is required — an empty array fails the run.
• On free (non-paying) accounts, the scraper is capped at 10 reviews per place regardless of maxReviews; paying runs honor the full maxReviews (up to 5,000).
• maxReviews is the cost lever — it caps billed result items. maxRequestsPerCrawl only caps HTML fetches (1 per place) and does not limit review pagination; do not raise it to get more reviews.
• Review language follows the TripAdvisor domain in the URL (e.g. .de → German reviews).
• If TripAdvisor blocks the HTML page (DataDome), the actor automatically falls back to the page's internal data endpoint — reviews remain complete, but placeHeader is reduced to the place name.

Billing: pay-per-result — $0.0004 per review at the Free tier ($0.40 per 1,000 reviews), as low as $0.00037 at Diamond tier, plus a per-GB start charge. Bound a run with maxReviews × number of places.

Legal & Compliance Disclaimer

This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by TripAdvisor LLC. It accesses only publicly available TripAdvisor review pages and the internal data endpoint that those public pages load themselves — there is no login bypass, no CAPTCHA solving, and no access to non-public data. You are responsible for complying with TripAdvisor's Terms of Service and applicable data-protection law (including GDPR and CCPA where reviewer data may be personal data) when using scraped data, and for not using reviewer contact or profile data for unsolicited commercial outreach. This disclaimer is not legal advice.