🌍 Tripadvisor Reviews Scraper — Most Comprehensive

Scrape TripAdvisor reviews for any hotel, restaurant, or attraction — full review text, bubble rating, sub-ratings (Value / Service / Food / Atmosphere / Rooms…), date of stay, trip type, helpful votes, photos, language & translation flag, and the complete owner/management response — at $0.30 per 1,000 reviews. Then schedule it as a new-review monitor that pings Slack, email, or a webhook the moment a fresh review lands.

Why this one? (honest comparison)

	This actor	Leading TripAdvisor reviews scraper
Price per 1,000 reviews	$0.30 (pay-per-event)	$5.00 (pay per result)
Full review text	✅	✅
Sub-ratings (Value/Service/Rooms…)	✅	❌
Owner / management response (+date, responder role)	✅	✅ (text only)
Date of stay/visit + trip type	✅	✅
Helpful votes	✅	❌
Review photos	✅	✅
Language + machine-translation flag	✅	✅
Date-range filter with early-stop (stops paginating, stops billing)	✅	partial
Keyword / rating-band filters	✅	❌
New-review monitor + Slack/email/webhook alerts	✅	❌
GDPR stripPersonalData toggle (default ON)	✅	❌
Raw source object kept per review	✅	❌
Failure handling	per-page retry with fresh proxy session; one bad page never kills the run	—

Competitor capabilities/prices as listed on their store pages, June 2026 — verify current state there.

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What does Tripadvisor Reviews Scraper do?

It extracts every review of any TripAdvisor place — hotels (Hotel_Review-… URLs), restaurants (Restaurant_Review-…), attractions (Attraction_Review-…) — and returns clean, structured rows you can export to JSON, CSV, Excel, or pull via API:

• ⭐ Rating & sub-ratings — overall bubble rating plus per-category scores (Value, Service, Food, Atmosphere, Rooms, Cleanliness, Sleep Quality, Location…).
• 📝 Full review text + title — not truncated, HTML-clean.
• 📅 All three dates — published date, written date, and the actual date of stay/visit.
• 🧳 Trip type — FAMILY / COUPLES / SOLO / BUSINESS / FRIENDS.
• 💬 Owner & management responses — full response text, response date, and the responder's role (e.g. "Guest Services / Front Office").
• 👍 Helpful votes, 📷 review photos (full-size CDN URLs), 🌐 language + translated-or-not flag.
• 🏨 Place context on every row — place name, ID, type, overall rating, total review count.
• 🗃️ raw sub-object — the complete source record, so a TripAdvisor field we didn't flatten is still yours.
• 🔔 Monitor mode — run it on a schedule and get only the reviews that are new since last run, with Slack/email/webhook alerts.

Who is it for?

• 🏨 Hotel & restaurant operators tracking their own (and competitors') reputation — sub-ratings show what slipped, owner-response fields show who's answering.
• 📊 Hospitality analysts & revenue managers building review datasets across portfolios.
• 🤖 AI/NLP teams that need full-text review corpora with ratings and dates for sentiment models.
• 🛎️ Agencies running reputation dashboards — monitor mode + webhooks pipes new reviews straight into your stack.
• 🔎 Travelers & researchers pulling complaint patterns (minRating:1, maxRating:2) before booking.

How to use it (step by step)

1. Click Try for free.
2. Paste one or more TripAdvisor place URLs (the page you'd send a friend — hotel, restaurant, or attraction).
3. (Optional) set maxReviewsPerPlace (default 50; 0 = every review), date range, keyword, rating band, language.
4. Click Start, open the Dataset tab, export.
5. (Optional) turn on monitorMode, attach an Apify Schedule, add a Slack/webhook/email channel — get pinged on every new review.

Quick start

{
    "startUrls": ["https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_Hotel-New_York_City_New_York.html"],
    "maxReviewsPerPlace": 50
}

Pull every review since a date (early-stops = you stop paying)

{
    "startUrls": ["https://www.tripadvisor.com/Restaurant_Review-g31979-d477015-Reviews-R_Landry_s_New_Orleans_Cafe-Van_Buren_Arkansas.html"],
    "maxReviewsPerPlace": 0,
    "dateFrom": "2026-01-01"
}

Reputation monitor (the recurring play)

{
    "startUrls": ["https://www.tripadvisor.com/Hotel_Review-g45963-d91703-Reviews-Bellagio-Las_Vegas_Nevada.html"],
    "monitorMode": true,
    "slackWebhookUrl": "https://hooks.slack.com/services/…"
}

Output example (truncated)

{
    "review_id": "935650210",
    "review_url": "https://www.tripadvisor.com/ShowUserReviews-g31979-d477015-r935650210-R_Landry_s_New_Orleans_Cafe-Van_Buren_Arkansas.html",
    "place_id": "477015",
    "place_name": "R. Landry's New Orleans Cafe",
    "place_type": "EATERY",
    "place_rating": 4.5,
    "place_review_count": 146,
    "title": "Top Notch Cajun Cuisine!",
    "text": "My husband and I got the cajun trio tonight. We didn't realize it was a drive through establishment…",
    "rating": 5,
    "subratings": { "Value": 4, "Service": 5, "Food": 5, "Atmosphere": 2 },
    "published_date": "2024-01-27",
    "stay_date": "2024-01-31",
    "trip_type": "FAMILY",
    "helpful_votes": 0,
    "language": "en",
    "is_translated": false,
    "owner_response": {
        "text": "Every member of our team is smiling reading this…",
        "published_date": "2026-06-10",
        "responder": "Hotel Manager",
        "responder_role": "Guest Services / Front Office"
    },
    "photos": ["https://dynamic-media-cdn.tripadvisor.com/media/photo-o/26/d8/29/ce/caption.jpg?w=1200&h=-1&s=1"],
    "reviewer_hometown": "Van Buren, Arkansas",
    "reviewer_contributions": 685
}

With stripPersonalData: false you additionally get reviewer_name, reviewer_username, reviewer_profile_url, reviewer_avatar.

Input

Field	What it does
startUrls	TripAdvisor place URLs (hotel / restaurant / attraction)
maxReviewsPerPlace	cap per place (default 50; 0 = all)
stripPersonalData	default true — drop reviewer name/username/profile/avatar
dateFrom / dateTo	publish-date window; dateFrom early-stops pagination
keyword	only reviews containing this text
language	only reviews in this language code (client-side filter)
minRating / maxRating	bubble-rating band (e.g. 1–2 = complaints only)
sortOutput	newest · oldest · highest · lowest
monitorMode, alertOnNewReview	recurring new-review watcher
webhookUrl, slackWebhookUrl, emailRecipients	alert channels
proxyConfiguration	keep RESIDENTIAL (default) — TripAdvisor runs DataDome

How much does it cost?

Pay-per-event — you pay for what you pull, no subscription:

Event	What it covers	Price
lot-scraped	each review returned	$0.0003
monitor-run-completed	each scheduled watch run	$0.02
new-lot-detected	each new review found by the monitor	$0.002
alert-delivered	each Slack/email/webhook push	$0.005

That's $0.30 per 1,000 reviews — the same 1,000 reviews cost $5.00 on the leading per-result competitor. A daily monitor on one hotel costs ~$0.60/month plus a fraction of a cent per new review. (Plus standard Apify platform usage; final prices are set on the actor's pricing page.)

Is it legal? (read this)

• Review text, ratings, and owner responses are publicly visible without any login. This actor only reads public pages — no login, no API key, no paywall circumvention.
• Reviewer identities are personal data. That's why stripPersonalData defaults to ON, removing names, usernames, profile links and avatars. Only disable it if you have a lawful basis (GDPR/CCPA) to process reviewer identities, and expect to honor deletion requests.
• Scraping may conflict with TripAdvisor's Terms of Service. Republishing TripAdvisor content commercially is restricted by their terms. You are responsible for your use of the data — for most users that means internal analysis, not republication.

FAQ

Which TripAdvisor pages does it support? Hotels (Hotel_Review-…), restaurants (Restaurant_Review-…), attractions (Attraction_Review-…), and vacation rentals. Paste the normal page URL; redirects to the canonical page are followed automatically.

Do I need a TripAdvisor account or API key? No. The data is read from the public page itself.

How many reviews can I get per place? All of them — set maxReviewsPerPlace: 0. The actor reads TripAdvisor's own public review feed 20 reviews per call and walks it until your cap, your date floor, or the end. If that feed is ever unavailable it automatically falls back to reading the server-rendered pages (10 per page for hotels/attractions, 15 for restaurants), so a run never comes back empty because of a site change.

Does it return owner/management responses? Yes — full text, response date, responder display name and role, on every review that has one.

Does it return sub-ratings like Value, Service, Rooms? Yes, as a subratings object whenever the reviewer filled them in.

Can I get only negative reviews? Yes — minRating: 1, maxRating: 2 returns only 1–2-bubble reviews.

Can I get only new reviews on a schedule? Yes — monitorMode: true + an Apify Schedule. State is kept in a named key-value store, so each run emits only reviews it hasn't seen before, and can alert Slack/email/webhook per review.

What about non-English reviews and translations? Reviews are returned in every language the place has, not just the language of the page. Each row carries language, original_language, and is_translated — use the language filter if you want a single language.

Why residential proxies? TripAdvisor is protected by DataDome. The actor's browser-fingerprint HTTP client plus residential rotation gets through reliably; datacenter IPs get blocked much more often. Failed pages are retried with a fresh session and never kill the run.

How fast is it? Under a second per batch of 20 reviews — 1,000 reviews in about a minute.

Is the reviewer's name included? Only if you set stripPersonalData: false (see the legal section). By default the output is anonymized but keeps hometown and contribution count for weighting.

Can I export to Excel / CSV / my backend? Yes — Dataset tab exports JSON/CSV/Excel/HTML/RSS, or use the Apify API / webhooks to pipe rows anywhere.

A field I need isn't flattened — am I stuck? No. Every row carries the complete raw source object from TripAdvisor's own data layer.

You might also like

• 🛏️ Hotel price & availability scrapers
• 🍽️ Restaurant directory & menu scrapers
• ⭐ Google Maps / Yelp review scrapers

Feedback

Found a missing field or want a new filter? Open an issue on the actor — fast fixes and feature requests welcome.