Tripadvisor Attractions Reviews Extractor

Our Tripadvisor extractor is here to streamline the process, focusing specifically on extracting attractions data from Tripadvisor category pages. With just a few simple steps, you can access valuable information about various attractions in your desired location

Why scrape Tripadvisor.com?

For travelers, it facilitates better trip planning with personalized recommendations and enhanced user experiences. Additionally, it offers opportunities for research and content creation. Scraping TripAdvisor attractions data serves as a crucial tool, providing valuable insights, informing decisions, and enriching experiences for all stakeholders involved.

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 Tripadvisor Attractions 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
• review score
• review heading
• profilfe contributions
• review body
• date of stay
• company responder
• company response
• company response date

Obtaining the Starter Link:

You can begin by using the search button to look up the destination you wish to visit. Once you've conducted your search, simply click on the "Things to Do" option to explore activities and attractions in that area. Once you've chosen an attraction and wish to view its reviews, copy the attraction's link and paste it into the extractor.

Cost

When you use Tripadvisor Attractions Reviews Extractor pre-defined web scraper, the cost will be 25 credits per row which equals to $1 for 40 rows.

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?

*** Data below was extracted on Jul 05, 2024 @23:01