What data fields can I scrape from Trustpilot reviews?

Trustpilot reviews contain various data fields that you might be interested in scraping for analysis or to aggregate customer feedback. However, before scraping any data from Trustpilot or any other website, it's crucial to check the site's terms of service and ensure that you're not violating any rules or laws. Many websites, including Trustpilot, have strict policies against scraping, and they may provide an API to access their data in a legal and controlled manner.

That said, if you have determined that it is legal and within the terms of service to scrape data from Trustpilot reviews, here are some common data fields you might consider extracting:

  1. Reviewer Information:

    • Reviewer's name or username
    • Reviewer's location (if available)
    • Number of reviews posted by the reviewer
    • Reviewer's star rating
  2. Review Content:

    • Review title
    • Review body/text
    • Date of the review
    • Star rating for the review
    • Any images or videos attached to the review (URLs)
    • Number of likes or useful votes for the review
  3. Company Response:

    • Response from the company (if any)
    • Date of the company's response
  4. Review Metadata:

    • Review ID or URL
    • Verified order badge (indicating whether the review comes from a verified purchase)

Here's a hypothetical example of how you might use Python with Beautiful Soup to scrape some of these data fields from a Trustpilot review page (assuming it's allowed):

import requests
from bs4 import BeautifulSoup

# Replace with the actual URL of the Trustpilot review page
url = "https://www.trustpilot.com/review/example.com"

# Fetch the page content
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')

# Find all review containers on the page (adjust the class as needed)
review_containers = soup.find_all('article', class_='review')

# Iterate through each review container to extract data
for review in review_containers:
    reviewer_name = review.find('div', class_='consumerName').get_text(strip=True)
    review_title = review.find('a', class_='link link--large link--dark').get_text(strip=True)
    review_body = review.find('p', class_='review-content__text').get_text(strip=True)
    review_date = review.find('div', class_='review-content-header__dates').get_text(strip=True)  # Needs further parsing
    review_rating = review.find('div', class_='star-rating star-rating--medium').get('alt')  # e.g., "5 stars: Excellent"

    print(f"Reviewer Name: {reviewer_name}")
    print(f"Review Title: {review_title}")
    print(f"Review Body: {review_body}")
    print(f"Review Date: {review_date}")
    print(f"Review Rating: {review_rating}")

# Note: The above code is hypothetical and may not work with the actual Trustpilot website structure

Remember, websites frequently change their structure, and the provided code may not work if Trustpilot's HTML structure changes. Always use respectful scraping practices such as not overwhelming the server with requests and following the robots.txt file guidelines for the website.

In the case of JavaScript, you would typically use Node.js along with libraries like axios to make requests and cheerio to parse the HTML. However, scraping with client-side JavaScript in the browser is generally not possible due to CORS (Cross-Origin Resource Sharing) policies and is not recommended.

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