Hotels Reviews Scraper for Tripadvisor

The TripAdvisor Reviews Scraper is an efficient tool tailored to extract data from TripAdvisor.com hotel pages, allowing users to gather reviews from numerous travelers. With this tool, users can effortlessly collect reviews from a diverse array of guests, enabling comprehensive insights into hotel reputations and guest satisfaction levels.

Easy to Use and Free to Try

A few mouse clicks and copy/paste is all that it takes!

* to use you will need to sign up for a  FREE TRIAL account

Steps to use:

Step 1: Click on "use for Free"

Step 2: Activate the Pre-Defined extractor by clicking the "Activate button"

Step 3: Enter your starter URLs

Enter a List of search URLs to start the web scraping. It must be a Booking hotel search URL including query strings for filters.

Step 4: Click "Run now" 

Using this extractor, you can get:

• name
• address
• geo id
• hotel id
• rating
• url
• profile image
• profile name
• review date
• review score
• profile contributions
• review
• date of stay
• company responder
• company response
• hotel url
• review heading

 

Obtaining Starter Links

Use the search bar on Tripadvisor to look for the hotel you're interested in. Enter the hotel's name or any relevant keywords related to the hotel. Once you've found the hotel you're interested in, click on its name to access its dedicated page on Tripadvisor. You can put the URL displayed in the address bar as a starter link for your extractor.

The output file can be exported as csv, xml, xlsx, json formats.

Below is a screenshot of what data fields we will be web scraping from Tripadvisor.com.

What does the output data look like?

When it is available this data will have rows which represent a single page's information such as its name, address, geo_id, hotel_id, rating, url, profile_image, profile_name, review_date, review_score, profile_contr, review_body, date_of_stay, company_responder, company_response, hotel_url, timestamp, review_heading, etc from tripadvisor.com.

*** Data below was extracted on Apr 17, 2024 @00:22

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