{FindDataLab}
Turn any website into data
Our service to gather data fit any company size
We collect any data
Surprise us
By clicking Submit, you agree to our Privacy Policy
How the business use data gathered by web scraping
Wiki Scraper +
Google Search API
Collected information from Wikipedia on accidents and incidents of the 20th century.

Wу used web scraper tool, manual collection of the part of information & Google search API to to establish coordinates.
Feedback & Mentions Scraper
Monitor web for access all media mention about your brand.
Sources: Google/Bing/ Yahoo SERP, Twitter, Facebook & Instagram, updates from websites, blogs, and forums.

We made a spider to collect weekly mentions of a company on the Internet (Google search, social media) and to collect feedback about using the services of this company.
Booking.com
Scraper
Extract address, reviews, phone numbers, websites and other available information.

We gather data from any databases or sources available in order to prepare an exhaustive list of Family Offices are based
in Europe or that have their main activity and client base in Europe.
Amazon Scraper
The information that we collect includes the following about:
  • Title
  • Price, Sale price
  • Fit
  • Colour
  • Image URL
  • Reviews
Format: XLS and XLSX Files
TripAdvisor
Scraper
Scrape list of hotels and restaurants, reviews and prices. Choose the format you need (CSV, JSON, XML, TXT, etc.) and get your data.




We extracted data about restaurants in Dubai from TripAdvisor.
Web Scraping
for Surveys
Related data for your surveys.

We collected data sets of dantists, swiss companies for research projects: Company name, Country, Address, Phone number, Email, Website, Staff, Treatments available.
Maps Scraper
Extract information such as business names, address, phone numbers, rating, websites, opening hours, emails and reviews from maps.

We use our few proxy IPs to avoid blocking.
Your case..
Here might be the story about your task!

Let's continue these stories with your case. We're ready to achieve your creative case.
Wiki scraper + Google search API
List of incidents and crashes from Wikipedia
For this task, we have collected information from Wikipedia on accidents and incidents of the 20th century - plane crashes, train incidents, bus incidents, etc.

We performed this task in a semi-automatic format - some of the information we got with our web-scraper tool, another part we collected manually. Required data included information about the location, transport vehicle, date, short description of the incident.

For us, this was an interesting use case of collecting information from a Wiki - a resource with a large amount of data that helps to conduct research, analytics, and the growth of the product.
1-to-1 live consultation with our expert
Write Close
Close
We will send you a link to schedule an online meeting to talk about your case
I agree the Terms of Service
Feedback & Mentions Scraper
How we help to collect feedback data, mentions
IT-specialists uses our tool to accelerate its work and the quality of order fulfillment.

We recently worked with a developer and made a spider to collect weekly mentions of a company on the Internet (Google search) and to collect feedback about using the services of this company.

Another example is setting up a daily extract of data from a website offering cruise tours. The website structure contained complex pagination or endless scrolling, a multi-level page structure. IT-specialist used our proxy to get this data.
Hotels Scraper
Once we collected data about Family Offices
We could gather data from any databases or sources available in order to prepare an exhaustive list of Family Offices are based in Europe or that have their main activity and client base in Europe.

It was such an unusual order. And we decided to write to you about it. There are many types of family offices typically formed after the sale of a family business or a realization of significant wealth. Many functions as private wealth management firms that service ultra-high net worth investors. The classification includes Single Family Offices and Multi-Family Offices.