Success Story – Scrape Job Listings from Job Sites

Case Informations

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  • Practice : Domestic Violence
  • Time : 3 Months
  • Lawyer : Christine Judge
  • Location : X-Byte House, Near Shantmani Apartment, Bodakdev, Ahmedabad - 380054, India

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  • X-Byte House, Near Shantmani Apartment, Bodakdev, Ahmedabad - 380054, India
  • sales@xbyte.io
  • +91 6353484269

Find Web Crawling Jobs With Quality Job Listing Scraping

Client

A well-known Job portal from the USA was searching to automate job listings using jobs web crawling across
different job boards as well as the company’s job listings.

Challenge

The client required job listings to get scraped from 20 job websites including Monster, Indeed, and CareerBuilder. Different data points that the client wanted include Job postings like job titles, wages, location, Job descriptions, company profiles, as well as candidate resumes.

Solution

The listing of source sites as well as data points was given by this client. They required this data to get scraped on an everyday basis meaning that the latest data needs to be given daily. We had completed web crawling jobs for scraping the necessary data fields from a website list given by this client. These requirements come under website crawling services that are given by us as the crawlers need to set specifically for every website in the listing. The client needed data in the CSV format as well as got uploaded in their Dropbox. When the primary setup was completed, our web crawlers started providing the data that was openly fed into this client’s Dropbox. We had delivered nearly 2 million jobs listed during the initial data crawling as well as around 200K records of well-structured and clean data on an everyday basis.

Advantages

  • All the difficult technical aspects of web scraping were considered by us
  • It took merely a few days to get the early set up after which the data started coming consistently
  • Our progressive tech stack controlled a huge amount of data naturally
  • The client had improved their job portal using a massive number of listings in the shorter time
  • The data scraped was 20 times more affordable than what an in-house setup might have cost to the client.