Semalt: The Most Commonly Used Data Scraping Requests

The demand for online scraping is increasing day after day because a lot of companies use a vast amount of data for different purposes. Different organizations and individuals have various web scraping needs. In fact, right now, there are infinite types of data extraction needs. To illustrate the importance of information gathering, 7 the most commonly used data extraction requests are outlined right below.

1. Data Collection from PDF files

This data scraping request is for collecting certain data from PDF files and converting it to excel files. Each of the target data files has about 15 to 20 data points in about 5 to 15 pages.

2. Extracting information through search engines and online directories

This is a common data extraction need. It requires gathering data from search engines and online directories and entering it into a specified database.

3. Email Lists organization and verification

This data extraction request requires an email address, company name, phone number, state, and the city where this or that company is located. This kind of information is usually needed for the marketing purposes. The information must be verified and organized for ease of use. A complete list of companies can be scraped easily from directories, but more information can be gotten from the official website of each company.

4. Email list compilation

This task is for gathering email addresses of people who have YouTube channels. It could be used to partner with them or market certain products/services to them. It could also be used to carry out an important survey.

5. List of all property rentals in a specific location

This web extraction request is used to get the list of property rentals on a particular website. Although the target website has lists of property rentals in several locations, only the ones in a particular location are needed for this request. Since about 1400 to 1650 property rentals are listed on the website, the required ones have to be filtered and scraped out. For each rental company, the details required are property id, name, and renters' details. All the extracted data should be exported into an excel spreadsheet as specified by the requester.

6. Contact details of finance professors in the United States

This data extraction request is for searching through the websites of all the universities in the United States to fetch the email addresses and phone numbers of finance professors.

7. Database of UK motor dealers

This web scraping task is for the compilation of UK motor dealers that specialize in Audi and Nissan brands. For each of the dealers, the required details are phone number, email address, postal address, business name, and manager's name.

In conclusion, there are hundreds of web scraping requests. The ones outlined above were just randomly chosen for the purpose of illustration.

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