3 Main Challenges of Web Scraping
Data is now considered the most valuable possession any online business can own. Brands with regular access to relevant user data collected in real-time generally have better edges and extra advantages over brands that do not.
Some of these advantages include making informed business insights and correct business decisions. Hence, the need to gather data from all over the internet is rising at an exponential rate.
However, harvesting a large amount of data is not an easy feat as the process can easily get hindered by many challenges and problems. Some of these challenges can make web scraping a little difficult, while others are capable of inhibiting the process entirely.
In this article, we will consider the most common challenges and how proxies can be used to mitigate them.
What is Web Scraping?
Web scraping is defined as a collection of practices used for gathering a large amount of user data from different sources. It involves interacting with several data sources at once and extracting information from them repeatedly.
The information is usually extracted in an HTML format and later parsed and converted into more readable formats such as Spreadsheets, JSON, or CSV.
Even though the process can be carried out manually, it is best to perform it automatically to make it easier and faster to collect more user data in real-time. And once gathered, these data can then be used for several important business operations such as:
- Improving overall customer experience
- Monitoring and protecting the brand and its assets
- Establishing smart strategies such as price intelligence and dynamic pricing
- Conducting intensive market research and monitoring price and competitors
- Generating quality leads for proper marketing
How Does Web Scraping Work?
Collecting structured web data available for public use from multiple sources can be explained in a straightforward process as described below:
- The search is initiated by typing in a URL
- A web crawler, also generally called a web ‘spider’, uses that URL to browse the internet, searching and indexing contents by following all connected links
- The indexed contents are then passed to a web scraper which begins to accurately and quickly extract data from each webpage
- The web scraper usually uses a data locator to identify what part of the HTML file to extract
- Next, the extracted data is parsed and converted to other formats that are easier to read before being saved in a storage system
- The process, which is usually automated, is repeated every time there is an update on the already visited website or server
Main Challenges of Web Scraping
There are several challenges surrounding web scraping; however, we will consider the most common 3 experienced by most businesses.
- Constant Web Changes
Generally, nothing remains constant on websites for a very long time. The need to improve dictates that businesses make regular changes to the websites frequently. However, these changes can pose a solid challenge to web scraping. For instance, a scraper designed to interact with a website specifically can become useless when the structure of such a website changes.
Also, data changes as more information is added every minute, and this can prove challenging for brands as it implies that extracted data will need to be regularly updated. This is usually not a problem until the process is no longer automated.
- Anti-scraping Measures
Some websites have applied anti-bot measures to fight bad bot attacks and while they do not distinguish those from ethical web crawlers, such measures may dissuade the process. Some of these measures include CAPTCHA tests and can hinder web scraping to varying degrees, with some even completely stopping it.
Websites that contain relevant data can also use restrictions and blocking to limit access to their data, and this can become a very troublesome challenge. These restrictions usually target the client’s IP address, and once they have been banned, the client will no longer be able to scrape data.
One of these restrictions, known as geo-blocking, can be directed towards businesses from certain physical locations and once in place, any company from such a region will find it impossible to access these websites.
Note: it is important to note that before engaging in any web scraping activity, one should not breach any laws and regulations and collect only publicly available data.
How Proxies Help To Overcome These Challenges
The challenges highlighted above are very common and difficult to overcome except with the use of proxies. Proxies, amongst other things, also ensure that brands are allowed access to whatever data they need and whenever they need it.
Proper proxies are designed to automatically and accurately detect changes to websites and adjust accordingly to accommodate these changes. This means that whether it is the structure or data that changes, web scraping will continue, nonetheless, with the aid of a proxy.
Also, proxies help switch and allocate real IP addresses and locations to scrapers, thereby helping to circumvent the different anti-scraping measures.
Lastly, proxies can be used to regularly change location to make a client appear from a different geo-location or access contents from a forbidden location. For instance, a brand residing in a place restricted from accessing data from websites in Japan can use a Japanese proxy to bypass these restrictions and collect the necessary data.
Data has no substitute, and even though a brand may encounter routine website changes, battle anti-scraping technologies, or require a Japanese proxy to access contents in Japan, data still needs to be collected. If you need a reliable proxy server, visit the website of one of the market-leading proxy providers and learn more about their proxy pool.
Luckily, proxies have been helping businesses overcome different challenges and continue to do so.