Web scraping is a process that takes place in every field of business as its importance cannot be overemphasized. Depending on the company’s objectives and use cases at that time, they can decide what data is necessary and extract it.
For example, a company that is searching for potential leads can get the contact information of businesses in yellow pages. You would need to build your own yellow pages scraper to do this but how do you go about the process? What are the benefits of data extraction from yellow pages, and how do you extract data from yellow pages?
In this article, all the above questions would be answered, and we would also discuss the basics you need to know in building a scraper for yellow pages.
What Are Yellow Pages?
Yellow pages are the print directory of telephone numbers and ads for companies and organizations in an industry. The information contained in yellow pages is according to the type of business and services the companies offer.
Yellow pages publishers attempted to make online copies of their directories when the internet started to take over the market. The online versions that were made available were referred to as internet yellow pages (IYP).
Compared to the printed versions, internet yellow pages can be updated in real-time so every information present there is current.
The Kind of Information You Can Get from Yellow Pages
For your business to grow and for you to achieve your sales goals, you will need leads. Yellow pages will provide you with information like business name, contact number, email address, state, postal code, website, and it’s sometimes accompanied by a business description.
All of this information is necessary and would be required if you need to contact a potential client to make sales.
You will find a yellow pages website for every country and if you are interested in a company that is located in that country, you can find the information you need on its yellow pages.
What Is a Yellow Pages Scraper?
To begin with, a web scraper itself is a tool that is used to gather data from different websites. It is used to identify the HTML data as it is available on the website, and then convert it to a readable format for further analysis.
This analysis is what would provide results that serve as pointers to guide the business in making informed decisions. Data extraction can be done manually but it is a stressful and time-consuming process.
There is also the possibility of making numerous mistakes and so an automated process is used that would not only provide accurate data but also do it fast despite the volume of data that is required.
Yellow pages scraper is therefore a tool that is built specifically to scrape yellow pages. This tool is meant to search for and extract specific data from yellow pages such as name, contact information, and location amongst others.
Building A Yellow Pages Scraper
When a web scraper is used to extract data from a target website, it contains a workflow that is made up of some elements. They include:
- Developing data extraction scripts. This is the first step in building a web scraper and it needs good knowledge in programming and familiarity with a specific coding language. The most popularly used among software developers for data extraction is Python language.
- You will also need an additional tool; a headless browser as they give you automated control over web pages. With headless browsers, you can have access to a web page and extract the content to another program, click on links, and do so much more. Nothing appears for users, so they won’t be any trigger for internet activity.
- After the required data has been extracted, data parsing makes it readable and suitable for use. Data on the web isn’t easy to understand but once it is parsed, it makes sense and allows for further analysis.
- In the web scraping building process to scrape yellow pages, data storage comes in last. Here you can store the extracted and processed data for use and reference purposes.
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Web Scraping Path
Data scraping path is part of the preparations you have to do before you begin scraping. You will need to have your list of URLs to the target sites you want to scrape from and this is the scraping path. The scraping path is your library of URLs where the information you need is stored.
Proxies for Web Scraping Yellow Pages
Proxies are necessary when web scraping is involved as they help prevent IP blocks from the target website’s server. If you require a lot of information from a site, you would send multiple requests and if done from a single IP, it would be detected as bot activity and blocked as humans don’t send so many requests at that rate.
Your real IP can also be detected as that of a rival and you will be fed false data which would ruin the whole idea of web scraping. So you can’t separate proxies from web scraping.
There are two main types of proxies you can use for your web scraping tasks and both can be used to keep you highly anonymous. There are residential proxies and datacenter proxies.
You can get different IP addresses from different locations around the world so you can collect data for various markets without being present there. A difference however exists between them both.
Residential IPs are real addresses related to a physical location, and they are issued by the internet service provider. With residential proxies, you will have a low back rate and can extract as much data as you need with low chances of getting caught. They are however very expensive.
Datacenter proxies are from cloud service providers and are not associated with any internet service provider. So the major difference between both proxies is their origin.
Residential proxies are less likely to get blocked among the two as they are tied to a physical location and won’t be detected as from a bot. They also leave no footprints and trigger no anti-bot features in websites unlike with datacenter proxies.
However, not all datacenter proxies get blocked as some are made to get through a website’s security and scrape without being detected. So it also depends on your proxy service provider.
How to Scrape Yellow Pages Data
Yellow pages hold a large number of entries that are relevant in making contacts and it prides itself as one of the largest business directories that exist. As stated earlier, they used to exist as big yellow books, but now everything can be accessed online and business information can be gotten from any location with internet access.
It’s not easy to extract all that data from yellow pages to your spreadsheet as it contains numerous data like name, phone number, email address, and a lot more. And so you would need a web scraper to extract the data you need and relay it to you in a readable format.
In this guide, we would make use of ParseHub as it's free but powerful nonetheless. Download and install ParseHub for free so we can get started on scraping yellow pages data for coffee shops in LA.
Scraping Data from Yellow Pages
- After installing ParseHub, open it and click on “New Project”. Enter the URL you want to scrape which in our case is that of all coffee shops in LA.
- Select the first business name on the list. Doing this will make it to be highlighted in green, showing that it has been selected. The other business names would be highlighted in yellow showing they weren’t selected. On the left sidebar, change the name of your selection to Business.
- Now click on the second business name on the list and select them all. All of them would now be highlighted in green.
- By this, ParseHub would start extracting the name and link to yellow pages of all the businesses on the list. To extract more data, click on the Plus (+) sign beside your selected business and then click on “Relative select” command.
- Click on the first business on the page and then click on the phone number beside it. An arrow will appear to let you know the association you are creating. Rename your selection to “phone” on the left sidebar.
- To extract more data from this page, repeat the above processes from 4 and 5.
Scraping Detailed Data
If you find yourself in a situation where you want to scrape business data that you can’t find on the search results page, you can set ParseHub up so that it clicks on each listing and extracts more data.
- Begin by clicking on the Plus (+) sign next to your “Business” selection and then click on the ”Click” command
- You will get a pop up asking if this is a next page button. Select “No” and name your template “Product Template”
- The first business on the list would now open inside the app and a new command would be created automatically
- With this new command, click on the “Email Business” button to extract the email. Rename your selection from the sidebar to “Email”
- You can add additional “Select” commands by clicking on the Plus (+) sign that’s next to your page selection so you can extract any other data you have in mind
At this point, ParseHub would be extracting every data from your selected businesses on the first page of search results. So let’s set it up to extract even more data from more search result pages.
- Go back to your main template and search results page using the browser tabs and tabs on the left side of the app
- Click on the (+) sign beside your page selection and click on the “Select” command
- Scroll to the bottom of the page and click on “Next page”. Rename your selection to “pagination”
- Next to your “pagination”, you will see an icon. Click on it to expand it
- Delete the extract commands under “pagination” with the delete icons next to them
- Click on the (+) icon next to your “pagination” selection and select “Click”
- You will get a popup asking if this is a “next page” link. Click “Yes” and input the number of additional pages you want to scrape.
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Run Your Scrape
At this point, you are ready to begin scraping.
Click on the “Get data” button on the left sidebar to get started. You can also test, begin the scraping process, or schedule your scrape from here.
Choosing Yellow Pages Scraper
It’s not an easy process to build your own yellow pages scraper as a lot of things are involved. You would need to be patient, and have some coding skills.
The resources that would be needed to extract a large amount of data can be overwhelming for small companies, but it can be outsourced to reliable scraping service providers.
Real-Time Crawler is a data collection tool that can be used to extract large data from search engines and eCommerce websites effectively.