🧳🌍 Tripadvisor Review Scraper

📌 Introduction

Tripadvisor Review Scraper is a powerful and easy-to-use Apify Actor designed to collect structured review data from Tripadvisor product pages. Whether you're analyzing customer sentiment, monitoring traveler feedback, or enriching your travel content, this Actor helps you extract data at scale — pricing is pay-per-result.

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🎯 What is this Review Scraper?

This Actor automatically scrapes reviews from a given Tripadvisor product URL and produces structured dataset output that you can download or integrate via API. It's perfect for travel market research, competitive analysis, sentiment tracking, and more.

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🔍 Features

• ⭐ Structured Review Data — Extract ratings, review text, reviewer info, photos, dates, and more.
• 🔁 Flexible Pagination — Easily scrape multiple pages of reviews.
• 🚀 Efficient Extraction — Designed to handle a large number of reviews.
• 🧹 Clean Output — Produces organized dataset entries ready for analysis.
• 🔌 Easy Integration — Use with Apify API or workflow automation tools.

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🧰 Input Parameters

The Actor's input schema allows you to specify what pages you want to scrape. (Exact fields may vary — based on the generic structure of similar review scrapers on Apify and this Actor's description.)

Parameter	Type	Required	Description
product_url	String	✅	The Tripadvisor product page URL to scrape reviews from.
page_size	Number	❌	Maximum number of reviews per page (default: 100).
page	Number	❌	Start page number; will skip (page – 1) * page_size reviews from the beginning (default: 1).

⚠️ Note: The exact input fields are based on typical review scrapers' schema (e.g., startUrls + limits), as detailed input docs aren't fully public for this Actor.

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📥 Example Input

{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g154998-d23988190-Niagara_Falls_Boat_Ride_VIP_Boarding_Journey_Behind_the_Falls-Niagara_Falls_Ontari.html",
  "page_size": 100,
  "page": 1
}

This configuration will scrape up to 100 reviews starting from the first page of the specified Tripadvisor product.

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🗃️ Output Data

Each review returned by this Actor includes the following structured fields:

Field	Description
id	Unique review identifier.
reviewId	Original Tripadvisor review ID.
productId	Tripadvisor product identifier.
rating	Review rating (1–5 stars).
title	Review title.
content	Full review text.
authorName	Reviewer's name.
authorLocation	Reviewer's location.
reviewDate	Date when the review was published.
helpfulVotes	Number of helpful votes.
photos	Array of photo URLs (if any).
ownerResponse	Business owner response (if any).
travelDate	Travel date mentioned in review.
travelType	Type of travel (solo, couple, family, etc.).

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🧠 How It Works

1. Input Acceptance — Takes a list of Tripadvisor page URLs from the user.
2. Web Scraping — Visits each URL and parses visible review data from the page DOM.
3. Data Structuring — Normalizes extracted fields into structured records.
4. Dataset Storage — Saves results in the Apify dataset for retrieval via UI or API.

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⚙️ Usage Examples

📦 Basic Usage

{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g154998-d23988190-Niagara_Falls_Boat_Ride_VIP_Boarding_Journey_Behind_the_Falls-Niagara_Falls_Ontari.html"
}

📈 With Pagination

{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g154998-d23988190-Niagara_Falls_Boat_Ride_VIP_Boarding_Journey_Behind_the_Falls-Niagara_Falls_Ontari.html",
  "page_size": 200,
  "page": 2
}

Attempts to extract up to 200 reviews from the specified restaurant page.

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💰 Pricing & Limits

This Actor is priced at $1.00 per 1,000 results, and includes a free trial for testing.

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📡 API / CLI Integration

You can run this Actor programmatically via the Apify API. Example (curl):

curl "https://api.apify.com/v2/acts/louvre~tripadvisor-review-scraper/runs?token=<YOUR_API_TOKEN>" \
  -X POST \
  -H "Content-Type: application/json" \
  -d @input.json

Replace <YOUR_API_TOKEN> with your Apify token and input.json with your JSON input.

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🔗 Related Links

• 🌐 Actor page: https://apify.com/louvre/tripadvisor-review-scraper
• 📜 API docs: https://apify.com/louvre/tripadvisor-review-scraper/api