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Tripadvisor Reviews Scraper — Tripadvisor | Lagic

Built For

Extract customer reviews and ratings for any hotel, restaurant, or attraction on Tripadvisor.

Curated by Lagic·Verified working

Configure Agent

TripAdvisor URL, numeric ID, or location name. Examples: 126260, Lotte New York Palace

Number of reviews to scrape per place. If 'Parse all reviews' is checked, this will be ignored.

If checked, the scraper will attempt to scrape all reviews, ignoring the 'Reviews per place' limit.

Sort order for reviews.

Restrict results to reviews with specific star ratings.

Filter by reviewer's traveler type.

Filter reviews based on the month(s) when the traveler visited.

Keyword to search for in review title or body.

Results to deliver

400 credits

This agent actively searches live listings — results may vary. You are only charged for what is delivered, up to this number.

Lagic Proxy

Country auto-rotated. Need a specific region? Contact support.

Pricing

4 credits per result
✓ 30 free credits on signup✓ Refund if 0 results✓ No card required

Sample Data Preview

The star rating (1-5) for each review.The full text of the review and its title.The date the review was published and the date of the traveler's visit.Information about the reviewer, including their username, profile link, hometown, and total contribution count.Details about the trip, such as the traveler type (e.g., family, couple, solo).The business owner's response to the review, if one was provided.
Value...Sample Text...2026-04-05https://...Value...10094
Value...Sample Text...2026-04-05https://...Value...10097
..................
Exports as:CSVXLSXJSON

Overview

Get detailed customer feedback from Tripadvisor, including review text, ratings, traveler type, and owner responses, to analyze sentiment and track competitor performance.

This tool extracts public reviews from any Tripadvisor business page, giving you direct access to customer feedback. It's designed for hospitality managers, restaurant owners, marketing agencies, and market researchers who need to understand customer sentiment without manually copying and pasting reviews. ### Understand Customer Experience at Scale Instead of reading reviews one-by-one, you can download thousands into a single dataset. The tool can grab the full review text, the title, the star rating (from 1 to 5), and any photos the reviewer uploaded. It also captures details about the traveler, such as whether they were traveling as a family, a couple, or solo, and the date of their visit. This structured data is ideal for spotting trends, identifying common complaints, and seeing what customers love most. ### Filter for the Feedback That Matters You can narrow your data collection to only the most relevant reviews. For instance, you can choose to only extract 5-star reviews, or only reviews from a specific traveler type like 'Family'. You can also search for a specific keyword within the review text, such as "front desk" or "room service," to investigate a particular aspect of your business. The tool also lets you filter by the language of the review and the country-specific version of the Tripadvisor site. ### Analyze Competitor Strengths and Weaknesses Beyond your own properties, you can use this tool to analyze your competitors. By providing a list of Tripadvisor URLs for competing hotels or restaurants, you can build a dataset of their customer feedback. This allows you to benchmark your performance, identify service gaps in the market, and learn from their successes and failures. The output also includes the business owner's response to each review, showing you how your competitors handle customer feedback.

Key Capabilities

  • ✓ The star rating (1-5) for each review.
  • ✓ The full text of the review and its title.
  • ✓ The date the review was published and the date of the traveler's visit.
  • ✓ Information about the reviewer, including their username, profile link, hometown, and total contribution count.
  • ✓ Details about the trip, such as the traveler type (e.g., family, couple, solo).
  • ✓ The business owner's response to the review, if one was provided.
  • ✓ The number of 'helpful' votes (likes) the review received.
  • ✓ Links to any images uploaded by the reviewer.
  • ✓ The original language of the review.
  • ✓ Reputation Management for a Hotel Chain: A hotel group's marketing team scrapes reviews for all their locations to identify recurring issues and track guest satisfaction over time.
  • ✓ Competitor Analysis for a New Restaurant: An entrepreneur planning to open a new restaurant extracts all reviews from the top 5 competitors in the area to understand their strengths, weaknesses, and pricing perception.
  • ✓ Client Reporting for a Marketing Agency: An agency downloads monthly review data for their hospitality clients to include in performance reports, highlighting sentiment trends and the impact of marketing campaigns.
  • ✓ Market Research on Travel Trends: A market research firm analyzes reviews filtered by 'Family' traveler type across a specific region to understand what amenities and services are most important to this demographic.
  • ✓ Operational Improvement for an Attraction: A theme park manager searches for reviews containing the keyword 'wait times' to gauge customer feedback on queue management and staffing levels.
  • ✓ Sentiment Analysis for Product Development: A tour operator scrapes reviews of their packages to identify which aspects are most and least popular, informing the design of future travel offerings.
  • ✓ Academic Research on Hospitality: A university researcher gathers a large dataset of reviews to study the correlation between owner responses and subsequent review ratings.

Field Dictionary

How To Run This Extractor

1

Enter one or more Tripadvisor URLs, place IDs, or place names into the 'Place ID or URL' field.

2

Set the maximum number of reviews to get per place, or check the 'Parse all reviews' box to get everything.

3

Optionally, add filters for star rating, traveler type, month of visit, or specific keywords.

4

Select the desired language and country version of the Tripadvisor website from the 'Locale' dropdown.

5

Click 'Run' and wait for the extraction to finish.

6

Download the collected reviews as a CSV, JSON, or Excel file.

Frequently Asked Questions

Do I need to be a developer to use this?
No, you don't need any coding skills. You just need the Tripadvisor URL for the place you want to analyze.
What formats can I export the data in?
Is it legal to scrape Tripadvisor reviews?
How many reviews can I extract at once?
Can I use this for client work?
How is this different from just reading reviews on the site?
How reliable is the data?
Can I schedule this tool to run automatically?
How can I find the 'Place ID'?
Can I get reviews that mention a specific word, like 'pool' or 'breakfast'?
Is the 'Since' date filter guaranteed to work?
How much will it cost to run?