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Scraping Yellow Pages for An Up-to-Date Database

Scraping Yellow Pages for An Up-to-Date Database

Yellow pages directories are one of the most popular online directories that give great visibility for your online business and facilitate the process of finding new customers, as well as, boost sales engagements and generate leads. If you are looking for a business or a company your first instinct must be conducting a Google search instead of consulting online directories, if so, then why are yellow pages so popular if no one ever uses them? The thing is that Google uses yellow pages to “verify” businesses for local search.

Your local listing on Google Maps, Yahoo and Bing Local is used to indicate that you are who you claim to be. Now, it makes a lot of sense that companies pay to be listed in yellow pages. And because of that, it is not uncommon for web harvesters to be asked to crawl those pages and provide organized and useful information to clients.

But, first things first: let’s define what data scraping is and what it can achieve. As previously underlined, data or web scraping is a software technique designed to extract information from the Internet. This method locates and collects targeted, usually unstructured, data stored in HTML and transforms it into a manageable form. Data scraping simplifies the process of acquiring information at scale and allows you to take only what you need, without spending hours on checking each web page manually.

In other words, from Google Chrome extension to various applications, data scraping will be of use in any field, as comprehensive data collection is required in all kinds of research.

In this age of information explosion it is extremely difficult to stay on top of it all or organize channels of information for a specific target group. Information is everywhere – new, old, updated, relevant, and staggeringly irrelevant – all of it coexists in the Internet and without order it is going to be of little or no use for you. Getting the information is the first and easiest step: you need to be able to organize it in an accessible manner.   

When it comes to scraping yellow pages directories, the function of getting the information organized in a timely manner and having it at your disposal in a useable format is of utmost importance. Those who tried to collect information/content/analysis from various sources without using web harvesting techniques and later attempted to make sense of it by organizing it into a separate directory will understand what a colossal work it is, which besides being extremely time consuming is also quite tedious and prehistoric.

A simple example: If you try to perform a basic search for a company in yellow pages it will most likely display a list of the company’s name, phone, address, email and map directions, right? And now imagine, that each company has a separate directory page where that list is displayed and in order for you to get hold of that information, you need to endlessly go back and forth in the pages and copy/paste everything you see on the way! Now, wouldn’t it be just magical to have it all completed in a matter of a couple of hours in a format (like CSV, SQL & TXT, Excel, Google Spreadsheets, PDF, JPEG, MSCZ) that is easy to read and store? The answer is yes, and there is a name to that magic – web scraping.

Generally when a scraper extracts data from yellow pages (and if you are reading this article, chances are you are looking to do the same), they are looking for the following:

  1.   Business Name
  2.   Street Address (State, Postal Code)
  3.   Phone Number
  4.   Map Coordinates
  5.   Email Address
  6.   Website
  7.   Business Description (based on different commercial categories)
  8.   And more (depending what your objective is)

Key points that web harvesters target for, usually include:

  1.         Extracting Lead Information: The scraper will aim to get targeted business and contact information as per required specific location
  2.         Scraping keyword based information: Extracts information on the basis of search keywords
  3.         Email Scraping: Scraping emails and storing them in required formats
  4.         Filtering information: Filtering specific information from an unorganized and unstructured data
  5.         Scraping GEO Map coordinates: Scraping  Longitude & Latitude for perfect business location

One of the industries that benefits the most from scraping yellow pages directories is recruitment. More and more companies, nowadays, invest in specific tools and systems (analytics-driven) for talent recruitment processes as a key element in the product development stage. Big Data is already influencing this industry vastly and web scraping has become probably the strongest analytical tool for recruiters with its capability to get everything done quickly and on-point.

As a matter of fact, one of the advantages the recruitment business has nowadays is the availability of online job listing sites that capture heaps of data (including email addresses) and can give perfect insights into what is likely to provoke qualitative and quantitative response. Moreover, vast amount of data aggregated from different sources (especially social media) is available to them with limitless list of prospective candidates: it makes the job easier and more organized for them.

To sum it up – it is time to forget about tedious and repetitive copy/pasting and let the advantages of web scraping help you capture important data in no time at all. Scraping yellow pages directories will enable you to access specific web databases and develop a similar configuration for your business. Also, it can help you track down information from identified pages, extract lead information and deliver it in a filtered and usable manner. It must be the most cost-effective way to build an information database that will include: Business Name, Address, City, State, Country, Phone, Email, Website URL and much more.

Thinking about scraping yellow pages directories or having them scraped for you? Do you have a success story you would like to share with us? Feel free to comment down below!

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