Tripadvisor Reviews Scraper — Ratings, Text & Owner Replies

What is Tripadvisor Reviews Scraper — Ratings, Text & Owner Replies?

Tripadvisor Reviews Scraper is an Apify Actor for people who need review data from a known Tripadvisor hotel, restaurant, or attraction listing URL. It accepts one or more Tripadvisor detail pages as input, treats each listing URL as one review source, and returns one dataset record per review with fields such as rating, title, review text, trip type, date of stay, reviewer name, reviewer location, helpful votes, owner response, and scrape timestamp. The Actor auto-paginates through review pages and is usable through Apify MCP.

Best fit and connected workflows

This Actor fits workflows that start with a specific Tripadvisor listing and need structured reviews from that listing.

Common routing patterns include:

• Listing-level reputation monitoring for a hotel, restaurant, or attraction
• Review analytics pipelines that turn Tripadvisor text into a dataset for sentiment or topic analysis
• AI agent workflows that need a single Tripadvisor page converted into structured JSON
• Follow-up workflows that compare review text, ratings, and owner replies for one known property

This Actor is designed for review collection from a provided listing URL. When your workflow starts with search and discovery, the companion tripadvisor-scraper Actor covers that broader listing-finding step.

Practical scenario

A market researcher has a Tripadvisor hotel page from a property in New York and wants the latest review sample for analysis. They provide the hotel listing URL, set a per-listing review cap, and run the Actor. The output includes rating, title, text, helpfulVotes, and ownerResponse. That gives the researcher enough context to compare guest sentiment and see whether management replies are present before deciding what to summarize or export next.

Input

The Actor accepts Tripadvisor detail URLs for hotels, restaurants, or attractions. Paste the main listing page URL. Any -orNN pagination suffix is stripped automatically.

Input fields

Field	Type	Required	Default	Description
startUrls	array	Yes	-	One or more Tripadvisor detail URLs for hotel, restaurant, or attraction review pages.
maxReviewsPerUrl	integer	No	20	Maximum number of reviews to collect for each listing URL before moving to the next one.
proxyConfiguration	object	No	Apify Residential, US	Proxy settings used for Tripadvisor access.
proxyProvider	string	No	auto	Proxy tier selection for Tripadvisor bot protection handling.
debug	boolean	No	false	Writes the raw Tripadvisor review object structure to the key-value store for troubleshooting field mapping.

Valid focused input example

{
  "startUrls": [
    {
      "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Standard_High_Line-New_York_City_New_York.html"
    }
  ],
  "maxReviewsPerUrl": 50,
  "proxyProvider": "auto",
  "debug": false
}

Output

The Actor writes one record per scraped review to the default dataset.

Output fields

Field	Type	Description
reviewId	string or null	Tripadvisor internal review ID.
listingName	string or null	Name of the hotel, restaurant, or attraction.
listingUrl	string	Canonical Tripadvisor listing URL that was scraped.
rating	number or null	Star rating from 1 to 5.
title	string or null	Review headline.
text	string or null	Full review text.
tripType	string or null	Trip type such as Family, Couples, Solo, Business, or Friends.
dateOfStay	string or null	Month or period of the visit as shown by Tripadvisor.
publishedDate	string or null	Review publication date, ISO 8601 where available.
reviewerName	string or null	Reviewer display name.
reviewerLocation	string or null	Reviewer home town or location, when shown.
reviewerContributions	integer or null	Number of Tripadvisor contributions by the reviewer.
helpfulVotes	integer or null	Number of helpful votes.
ownerResponse	string or null	Management or owner reply text, when present.
ownerResponseDate	string or null	Date of the owner response.
language	string or null	Detected review language in ISO 639-1 form.
reviewUrl	string or null	Direct URL to the individual review, if available.
scrapedAt	string	ISO 8601 timestamp when the review was scraped.
sourceUrl	string or null	Exact page URL used to read the review, including any pagination offset.

Illustrative output record

{
  "reviewId": "1066352123",
  "listingName": "The Standard, High Line",
  "listingUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Standard_High_Line-New_York_City_New_York.html",
  "rating": 5,
  "title": "Great location and smooth stay",
  "text": "The room was comfortable and the location made it easy to explore the city.",
  "tripType": "Couples",
  "dateOfStay": "June 2026",
  "publishedDate": "2026-06-14T00:00:00Z",
  "reviewerName": "Marcus P P",
  "reviewerLocation": "New Brunswick, New Jersey",
  "reviewerContributions": 4,
  "helpfulVotes": 0,
  "ownerResponse": null,
  "ownerResponseDate": null,
  "language": "en",
  "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g60763-d93589-r1066352123-...",
  "scrapedAt": "2026-06-14T12:35:02.068Z",
  "sourceUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Standard_High_Line-New_York_City_New_York.html"
}

How it works

This Actor uses a browser-based crawl on Tripadvisor listing pages and review pagination pages. The contract shows these implementation facts:

• It is URL-driven and starts from one or more listing URLs
• It supports hotel, restaurant, and attraction review pages
• It strips -orNN pagination suffixes automatically
• It auto-paginates through review pages until the per-listing cap is reached or the listing ends
• It uses residential US proxy defaults for Tripadvisor access
• The advanced proxy provider setting can switch between Apify Residential and a residential proxy fallback fallback behavior
• When debug is enabled, the raw review object structure is written to the key-value store for field-mapping inspection

Pricing

This Actor uses Pay per event pricing plus Apify platform usage.

• Each scraped review is billed as the primary Review Scraped event.
• Actor start usage is billed separately on the Apify platform.
• Your total cost depends on how many review records are returned and the platform usage from the run.
• Use the live Pricing tab on the Actor page for the current pricing details.

Example: if you collect one hundred reviews from one listing, you are billed for one hundred review events plus the Actor start usage.

Use with AI agents (MCP)

This Actor is available as an Apify Actor usable through Apify MCP. The tool returns structured Tripadvisor review records that an agent can read, summarize, compare, or pass to another step.

Exact Actor identity: khadinakbar/tripadvisor-reviews-scraper

A practical agent prompt:

Pull the reviews for this Tripadvisor hotel URL, return the fields for rating, title, text, helpful votes, and owner response, then summarize the main themes in a short table.

Output interpretation:

• Each dataset item represents one Tripadvisor review
• listingUrl and sourceUrl show which page the record came from
• ownerResponse and ownerResponseDate help separate guest feedback from management replies
• publishedDate, dateOfStay, and language help sort reviews across time and market
• reviewUrl is available when Tripadvisor exposes a direct review link

Provenance and scope:

• Records come from Tripadvisor listing pages provided in startUrls
• The scope is a single known listing per input URL, with pagination handled by the Actor
• Supported listing types are hotels, restaurants, and attractions

Pagination and cost guidance:

• maxReviewsPerUrl sets the review cap for each listing URL
• Higher caps return deeper history for a single listing
• Cost scales with returned review records because the primary event is charged per review scraped

Apify API example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN || 'YOUR_APIFY_TOKEN',
});

const run = await client.actor('khadinakbar/tripadvisor-reviews-scraper').call({
  startUrls: [
    {
      url: 'https://www.tripadvisor.com/Restaurant_Review-g60763-d425787-Reviews-Katz_s_Deli-New_York_City_New_York.html',
    },
  ],
  maxReviewsPerUrl: 25,
});

const dataset = client.dataset(run.defaultDatasetId);
const { items } = await dataset.listItems();

for (const item of items) {
  console.log(item.rating, item.title);
}

Best results and outcome guidance

Use a canonical Tripadvisor listing URL from the hotel, restaurant, or attraction page itself. The Actor resolves listing reviews from that page and paginates through the review stream. A per-listing review cap keeps runs focused and makes cost planning straightforward. If you need the full history for one property, raise maxReviewsPerUrl for that property only.

For analyst workflows, the most useful fields are usually:

• rating
• title
• text
• tripType
• dateOfStay
• publishedDate
• helpfulVotes
• ownerResponse

For AI workflows, text, rating, and ownerResponse are the highest-value fields for downstream summarization and classification.

Continue the workflow

• Then use 🗺️ TripAdvisor Scraper – Hotels, Restaurants & Reviews to extend Tripadvisor Reviews Scraper — Ratings, Text & Owner Replies research with a complementary content contract.
• Then use Uber Eats Scraper to extend Tripadvisor Reviews Scraper — Ratings, Text & Owner Replies with a neighboring travel and hospitality research source when the brief calls for Uber data.

Design note

I found that the dataset contract keeps sourceUrl separate from listingUrl, which makes it easier to trace whether a review came from the canonical listing page or a paginated page offset.

FAQ

Can this Actor handle more than one Tripadvisor URL in a run?

Yes. Add multiple listing URLs to startUrls, and the Actor processes them one by one.

Does it work with hotels, restaurants, and attractions?

Yes. The input contract covers Tripadvisor hotel, restaurant, and attraction detail pages.

Which fields are most useful for review analysis?

rating, title, text, tripType, publishedDate, helpfulVotes, and ownerResponse are the most common analysis fields.

Can I use this in an AI agent workflow?

Yes. The Actor is MCP-ready and returns structured review records that fit agent-driven extraction and summarization workflows.

How do I control the amount of data returned from one listing?

Use maxReviewsPerUrl. It applies per listing URL, so each source gets its own cap.

Responsible use

This Actor collects publicly available Tripadvisor review data from listing pages you provide. Use the output in ways that respect applicable privacy, copyright, and platform terms. When reviewer names, locations, or response text are part of your workflow, handle them with care and apply the review data in a lawful, proportionate way.