Data is crucial in the corporate world for understanding rivals, consumer needs, and industry dynamics. As a result, web scraping is becoming increasingly popular. Businesses gain a strategic edge in the industry by using web scraping solutions. Customer behaviour analysis, price and commodity management, lead production, and competitor detection are only a few of the examples.
Here are some of the commonly faced challenges by scrapers while scraping any website:
1. Proxy services
A proxy server is a device that is located in another location and has its own IP address. If you collect a lot of data or collect it on a daily basis from one site, the site would most likely block you based on your IP address. You'll need hundreds or thousands of unique IP addresses to avoid this issue.
Proxy servers can be used to solve this problem. There are hundreds of proxy services that offer proxy server access, each with its own set of advantages and disadvantages. This is a popular way for web scraping startups to get started. There are many approaches to using proxy servers, and I will not go into depth about them here.
2. CAPTCHA protection
Another difficulty to data scraping is captcha security. This security feature is probably something you've seen on a few websites. A captcha is a unique image that only humans can identify, but not data scraping apps. To access a web page, the user must react to the image in some way.
Some special services work around this by sending the captcha to a person, who enters the response and sends it back, stopping the website from refusing the bot access (e.g. a web scraper).
3. Unstable load speed
When a website receives too many access requests, it can react slowly or even fail to load. When humans browse the site, this is not a concern since they just need to refresh the page and wait for it to recover. Scraping, on the other hand, could be disrupted because the scraper is unprepared to deal with such a situation.
4. Professionally protected sites
When a website is professionally secured with services like Akamai or Imperva Bot Management, data scraping becomes more difficult. Only companies that specialize in data scraping would be able to solve this issue. LinkedIn, Glassdoor, and even British Airways are only a few examples of business websites that have been protected in this way. This security is multifaceted and nuanced, and it employs artificial intelligence. You must choose your own collection of tools for such resources and modify them over time.
5. Real-time data scraping
When it comes to price comparison, inventory monitoring, and other activities, real-time data scraping is important. The data can shift in the blink of an eye, resulting in massive capital gains for a company. The scraper must constantly track the websites and scrape data. Even so, there is some lag due to the time it takes to request and receive data. Obtaining a large volume of data in real-time is also a significant challenge.
There will undoubtedly be more problems in web scraping in the future, but the universal scraping concept remains the same: treat websites with respect. Don't try to cram too much into it. Furthermore, you can always use a web scraping service like https://www.smartscrapers.com/ to assist you with your scraping project as mentioned on their website they work with 1000+ companies and also provide data in different formats which makes it easy for you to use data how you want.
6. Data Quality Challenge
Data precision is also critical in web scraping. For example, collected data may not follow a predefined template, or texting fields may be incorrectly filled. Until saving, run a quality assurance test and check each area and expression to ensure data quality. Some of these measurements are performed automatically, but there are times when a manual inspection is needed.
There might be more challenges you will face depending on the website. Let us know about it in the comments section.