extracto.cloud
tripadvisor-reviews-scraper
Tripadvisor Reviews Scraper
Collect Tripadvisor hotel, restaurant and attraction reviews with ratings, publication dates and place details.
Current pricing: $0.000489 / 1 Per review · minimum 10 credits/run. Review the estimate before running.
Endpoint
Method
POST
URL
https://extracto.cloud/api/v1/parsers/tripadvisor-reviews-scraper
Result delivery
Add
webhook_url and optional webhook_secret to receive the saved result. Webhook setup and signatures →
Auth
X-API-KEY: ext_...Response
{
"success": true,
"tool": "tripadvisor-reviews-scraper",
"parser": "tripadvisor-reviews-scraper",
"count": 0,
"data": []
}
Documentation
# Tripadvisor Reviews Scraper — Most Comprehensive (`scrapersdelight/tripadvisor-reviews-scraper`) parser
From $0.30 per 1,000 reviews — 16x cheaper than $5/1k incumbents. Scrape TripAdvisor hotel, restaurant & attraction reviews: full text, ratings, sub-ratings, dates, trip type, owner responses, photos. New-review monitor with Slack/email/webhook alerts. No login or API key.
- **URL**: https://extracto.cloud/docs/api/parsers/tripadvisor-reviews-scraper
- **Developed by:** [Scrapers Delight](https://Extracto.com/scrapersdelight) (community)
- **Categories:** AI, E-commerce, Automation
- **Stats:** 25 total users, 8 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.30 / 1,000 per reviews
This parser is paid per event. You are not charged for the Extracto platform usage, but only a fixed price for specific events.
Learn more: https://docs.Extracto.com/parsers/running/parsers-in-store.md#pay-per-event
## What's an Extracto parser?
An parser is a serverless cloud program that runs on the Extracto platform. It has two run modes.
In Batch mode, an parser accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an parser provides a web server which can be used as a website, API, or an MCP server.
Extracto vocabulary and the platform model are defined once, in the agent quickstart at https://Extracto.com/agents.md.
## How to integrate an parser?
If asked about integration, you help developers integrate parsers into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
Do not guess an integration path. Every one of them is in the agent quickstart at https://Extracto.com/agents.md: the Extracto MCP server, Agent Skills with the Extracto CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.
For examples already wired to this parser's own input schema, see the [API](#api) section below.
Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.Extracto.com/api/client/js/docs.md) (`npm install Extracto-client`) and [Python](https://docs.Extracto.com/api/client/python/docs.md) (`pip install Extracto-client`).
# README
## 🌍 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 parser** | 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.*
***
### 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 Extracto **Schedule**, add a Slack/webhook/email channel — get pinged on every new review.
#### Quick start
```json
{
"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)
```json
{
"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)
```json
{
"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)
```json
{
"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 (uses TripAdvisor's own review search, on the original text) |
| `language` | only reviews in this language (code like `de` or a name like `German`; uses TripAdvisor's own language 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 Extracto platform usage; final prices are set on the parser's pricing page.)*
### Is it legal? (read this)
- Review text, ratings, and owner responses are **publicly visible without any login**. This parser 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 parser 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 Extracto 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. It uses TripAdvisor's own language filter, so `de` returns reviews written in German plus reviews TripAdvisor machine-translated into German; keep `is_translated: false` rows for originals only.
**Why residential proxies?**
TripAdvisor is protected by DataDome. The parser'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 Extracto 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 parser — fast fixes and feature requests welcome.
# parser input Schema
## `startUrls` (type: `array`):
One or more TripAdvisor place URLs — hotels (Hotel_Review-…), restaurants (Restaurant_Review-…), or attractions (Attraction_Review-…). Any tripadvisor.com page URL of the place works; the parser follows redirects to the canonical page.
## `maxReviewsPerPlace` (type: `integer`):
Hard cap on reviews scraped per place (cost/safety guard). Defaults to 50 for a fast first run — set 0 to pull EVERY review of the place.
## `stripPersonalData` (type: `boolean`):
ON by default: drops reviewer display name, username, profile URL, and avatar from the output (coarse hometown + contribution count are kept). Turn OFF only if you have a lawful basis to process reviewer identities.
## `keyword` (type: `string`):
Only keep reviews whose title or text contains this keyword (case-insensitive). Sent to TripAdvisor's own review search, which matches the review's original text.
## `language` (type: `string`):
Only keep reviews in this language code (e.g. 'en', 'de', 'es'; a name like 'German' also works). Uses TripAdvisor's own language filter: reviews written in that language plus reviews TripAdvisor machine-translated into it (see is_translated / original_language).
## `dateFrom` (type: `string`):
Only reviews published on/after this date. Reviews come newest-first, so the parser STOPS paginating once a whole page is older than this — big cost saver for incremental pulls.
## `dateTo` (type: `string`):
Only reviews published on/before this date.
## `minRating` (type: `integer`):
Only reviews with at least this bubble rating. 0 = no floor. E.g. 1 + maxRating 2 isolates complaints.
## `maxRating` (type: `integer`):
Only reviews with at most this bubble rating. 5 = no cap.
## `sortOutput` (type: `string`):
Ordering of the final dataset (collection itself always walks the site's newest-first pages).
## `monitorMode` (type: `boolean`):
Recurring watcher: diff against the prior run's seen reviews (per place) and output/alert ONLY new reviews. Pair with an Extracto Schedule (e.g. daily) for review-reputation alerting.
## `alertOnNewReview` (type: `boolean`):
In monitor mode, deliver an alert for each new review via the channels below.
## `webhookUrl` (type: `string`):
POST endpoint for new-review alert payloads (Make / Zapier / n8n / custom). One JSON body per alert.
## `slackWebhookUrl` (type: `string`):
Slack incoming-webhook URL for formatted new-review cards (rating, title, excerpt, link).
## `emailRecipients` (type: `array`):
Email addresses for the new-review digest (sent via Extracto/send-mail).
## `proxyConfiguration` (type: `object`):
TripAdvisor sits behind DataDome — keep RESIDENTIAL proxies (the default). Datacenter IPs get blocked far more often.
## `diagnose` (type: `boolean`):
Dev only. Fetches page 1 of the first place, dumps the decoded review JSON to the key-value store (DEBUG_REVIEW_LIST) and logs the parsed first record, then exits.
## parser input object example
```json
{
"startUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_Hotel-New_York_City_New_York.html"
],
"maxReviewsPerPlace": 50,
"stripPersonalData": true,
"minRating": 0,
"maxRating": 5,
"sortOutput": "newest",
"monitorMode": false,
"alertOnNewReview": true,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
},
"diagnose": false
}
```
# parser output Schema
## `items` (type: `string`):
The dataset of scraped TripAdvisor reviews (one review per row).
# API
You can run this parser programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'Extracto-client';
// Initialize the ApifyClient with your Extracto API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
token: '<YOUR_API_TOKEN>',
});
// Prepare parser input
const input = {
"startUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_Hotel-New_York_City_New_York.html"
],
"maxReviewsPerPlace": 50
};
// Run the parser and wait for it to finish
const run = await client.parser("scrapersdelight/tripadvisor-reviews-scraper").call(input);
// Fetch and print parser results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.Extracto.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.Extracto.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Extracto API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")
# Prepare the parser input
run_input = {
"startUrls": ["https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_Hotel-New_York_City_New_York.html"],
"maxReviewsPerPlace": 50,
}
# Run the parser and wait for it to finish
run = client.parser("scrapersdelight/tripadvisor-reviews-scraper").call(run_input=run_input)
# Fetch and print parser results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.Extracto.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.Extracto.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"startUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_Hotel-New_York_City_New_York.html"
],
"maxReviewsPerPlace": 50
}' |
Extracto call scrapersdelight/tripadvisor-reviews-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"Extracto": {
"type": "http",
"url": "https://mcp.Extracto.com/?tools=fetch-parser-details,scrapersdelight/tripadvisor-reviews-scraper"
}
}
}
```
The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Extracto Console (https://console.Extracto.com/settings/integrations).
## OpenAPI specification
Download the OpenAPI definition: https://api.Extracto.com/v2/parsers/Hs1If8A9bMecB2uHI/builds/4xdLwDiiX7EZRORIh/openapi.json
Request Body
{
"input": {
"startUrls": [
"https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_Hotel-New_York_City_New_York.html"
],
"maxReviewsPerPlace": 50
}
}
cURL
curl -X POST https://extracto.cloud/api/v1/parsers/tripadvisor-reviews-scraper \
-H "X-API-KEY: ext_your_api_key" \
-H "Content-Type: application/json" \
-d '{"input":{"startUrls":["https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_Hotel-New_York_City_New_York.html"],"maxReviewsPerPlace":50}}'