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Overcoming data scraping challenges with Web Scraping API

ScrapingAnt Team

ScrapingAnt Team

ScrapingAnt

Overcoming data scraping challenges with Web Scraping API

Data scraping is a process by which data is extracted out of a website into a spreadsheet or a local file on your computer. Data scraping, which used to be quite a simple task, has become increasingly challenging to scale with time.

If you want to pull information from a website or you want to do this as a regular job, you will face many challenges while scraping data from a website. You will learn about those challenges in this article and also how to deal with them.

Scraping Software Management#

You can build your own software by hiring a software developer to write proprietary code for your data scraping needs. There are multiple packages available e.g. BeautifulSoup, Scrapy, Selenium, etc.

Alternatively, you can use a third-party vendor that offers specialized services in this field.

Build Your Own Data Collection Software#

Hiring a software developer to write proprietary code for you is not that easy. There are many challenges that you will face using these proprietary codes. One of the challenges is the high cost. The hundreds of hours required for coding will cost you a large investment. Plus expenses for the software and hardware licenses. Another expense will be the proxy infrastructure and bandwidth, which will also cost you a large sum of many. And not only that, even if the data collection fails, you will still have to pay this money.

3rd Party Tools#

Using a 3rd party vendor might be useful. ScrapingAnt's web scraping API is one of the 3rd party vendors that offer data scraping services. Much other software is also available, but most of them are old and outdated. Using ScrapingAnt API you can use a low-coding data collection tool, and you only pay if the data extraction was a success.

Website structure#

Websites often change their website structure, most of the time upgrading the user interface to improve the user experience and increase attractiveness. These changes occur in the HTML codes. Guess what else does HTML hold. The data that needs scraping. Web scrapers are built according to the HTML code and will also require an upgrade every time the website upgrades. The scraping code is only tailored to your current needs. Whenever the target website changes its structure which is very likely to happen, the code will become useless, and you will need to repair it again and again.

Bots and CAPTCHAs#

How often have you tried to access a website, and instead, the website challenges you with a puzzle to prove that you are a human? CAPTCHAs separate humans from bots by displaying logical problems that are easy for humans but difficult to pass for the bots. They are bots that tend to prevent data collection attempts by other bots. Thus if you are using basic scraping codes, they will most probably fail to enter the site protected by bots and CAPTCHASs.

Websites are free to choose whether they will allow data scraping bots or codes on their websites. Most of them do not allow data scraping because the intention of data scraping is mostly to gain a competitive advantage. Also, the bots drain the websites' server resources and affect the performance of the site.

The puzzle, however, must be solved very carefully as the technical difficulties increase with time. This is where ScrapingANT API comes in. Stepping carefully into this minefield of bots and crossing the field successfully is ScrapingAnt API's specialty.

IP blocking#

Many websites have set a threshold for receiving data scraping requests. If your scraping code or bot is sending more requests than that website's threshold, there is a good chance that you might get blocked from the website. Most websites use IP-based blocking i.e. they block your network's IP address. The chances of getting blocked are pretty high if you are sending many parallel requests.

Again, the problem here can easily be solved by using a proxy network which is also a part of ScrapingAnt API's data scraping techniques.

Speed and scaling#

Many a time, the scraping projects begin with a few thousand pages but then scale to millions in a very short period.

Also, most of the data scraping agents are very slow and send a very limited number of requests per second.

Both speed and scale are also affected by another factor which is the underlying proxy infrastructure which might allow your scraping tool to send more requests per second.

Data accuracy#

Many software is unavailable to retrieve data from a website very accurately. It may be due to many reasons, but particularly as we have discussed before, websites keep changing their page's structure which breaks the scraping tool's data collector, and hence the data collector does not collect accurate data from that website. This happens a lot as websites tend to change their structure a lot, and the scraping tools are built just for a specific page structure.

You must check the accuracy and completeness of the data as well as the format in which the data will be delivered to your computer. The data must be integrated seamlessly into your existing systems.

Anti-scraping technologies#

Many big websites, such as Linkedln, actively use anti-scraping technologies, which reduces any web scraping threats to almost zero. These websites disallow bots and implement IP blocking techniques for your web scraping bots.

Getting around these anti-scraping technologies is quite difficult. You will need to mimic human behavior to get around anti-scraping technologies.

Honeypot traps#

Web designers sometimes put honey traps on the website to prevent data scrappers from pulling data from their website. The honey trap is a link that normally you or other humans would not click, but the scrapping bot which goes through every link would click it. The IP address is blocked immediately as soon as the data scrapping bot clicks on the honey pot link.

You must design your Data Scraper very carefully to avoid such challenges. Or you can use ScrapingAnt API's crawlers, which are professional and specialize in dealing with such situations using an enormous amount of IPs to prevent such cases.

Real-time quality control#

Using scraping tools, it is highly unlikely that the quality of the data you are scraping will be maintained. If the records do not meet the quality guidelines, the overall integrity of the data that your bot is collecting will be compromised. This situation is very problematic as to deal with it, you will have to scrape the data in real-time. Constant and critical monitoring is required, and it needs to be checked against new cases and validated.

Legal risks#

Scraping at a huge scale might be illegal. Scraping at scale means sending more requests per second to a website than its threshold. When you are sending requests above the threshold level, the high crawl rates can harm the servers of the website being scraped. In court, it can be misconstrued as a DDoS attack. Although there is no such limit on the rate of web scraping, it should not overload the servers. Otherwise, you will be responsible for the damage.

Web Scraping Advantages#

Who needs web data? Everyone needs it. To survive in your respective market, you need to know what your competitors are offering. You need to know what costs they offer for the same products.

Data helps you understand what the consumer wants. How do you know what the consumer likes? By analyzing the data scraped from other successful or competitor websites.

Some advantages that can be obtained by using Data Scraping are as follows:

Price Intelligence#

You can make tons of profits by using this data as it allows you to know what your competitors are offering for the same products.

Market Research#

Data scraping allows you to monitor your competitors, analyze market trends, analyze market prices, determine the point of entry, and do other research. Market research is very crucial and must be of high quality and accurate.

Data-Driven Products#

Product data scraping can give you a huge edge in your market. It allows you to optimize pricing, monitor product trends, monitor your competitors, and lets you make timely investment decisions. Such information can give your business a huge boost in the respective market.

Data for Finance#

You can get product data, filing data, product reviews, company news, and sentiment analysis by scraping. Large companies are consuming scraped data on a larger scale because never before the decision-making process has been this well informed and easy.

Brand Monitoring#

Data scraping lets you know your position in the market. How much your products are priced and attractive. It gives you huge insights that you can use to improve your company.

MAP Compliance#

et us say you have multiple retailers selling your products in different areas. You will need to keep an eye on them so that they do not start to sell something at a price of their own. This will damage your business' growth and reputation. MAP compliance data will help you take immediate measures in case such a situation occurs.

Lead Generation#

You can build a lead database by defining your target customer and where they are on the internet by using data from social media platforms, business directories, and other events. Thus show your customer what he wants first. They don't need to be there to buy the product, but they will remember the website.

Recruitment#

With an automated web data feed to your recruitment toolkit, you can find the best recruitment and the best talent, boost employee retention and make better hiring decisions.

Business Automation#

It can help you obtain unlimited access to your own data, saving your team time and effort by automating the data reports and data aggregation.

How do companies use web data?#

Here are some examples of how companies use data scraping to their advantage:

  • E-Commerce companies such as Amazon, Walmart, Target, Flipkart, and AliExpress compare their products and prices with their competitor's products.
  • Business owners who need marketing for their product scrape social media websites such as Instagram, Tiktok and Youtube, etc. to find top influencers so they can reach out to them for PR-ship or other agreements by which they can do their marketing.
  • Real-estate businesses also use scraping tools to compile a database of listings.

Scraping decision checklist#

In short, if you want to extract data from a website using a scraping tool, you will have to consider:

  • If you want to develop and maintain your solution or if you want to go with a third-party vendor.
  • You need to check what kind of proxy network the company is offering. Is it reliable? Are they dependent on a third-party vendor?
  • Your software's ability to overcome site barriers (e.g., honeypot traps, anti-scraping technology, and captchas) and extract data
  • You need to know if the bandwidth charge depends on successful data collection.
  • You need to know the data privacy policies and do they comply with the data privacy law.

Additionally, if you want to add some more to your data scraping, consider looking for solutions that have the following features:

  • Proxy network quality and diversity
  • Web crawler maintenance
  • An account manager that will handle your day to day operations and business needs
  • 24/7 technical support

Summary#

Data scrapping in the old days was very simple. You would have to spend days collecting data from different sites manually. This was very time-consuming. Now with the advancement of technology, data scrapping has been digitilized. Codes and software and even websites have been established that offer data farming services, but these modern solutions also come with modern difficulties, e.g., website structural changes break the software, the website's defense needs to be bypassed, the threshold for data mining of the website itself, advanced proxy structure so that speed and scraping can be increased without being blocked.

You can build your software that deals with these problems, or you can use 3rd party vendors such as ScrapingAnt that offer these services.

Further reading#

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