The demand for big data is growing at an overwhelming pace nowadays. The increasing number of businesses is hectic to gather data from multiple sites to optimize and develop their business. Data helps them get insights into their market, its trends, customer behavior and preferences, competitors’ strategies, and activities. 

Thus, data scraping is today an essential business tactic, but the World Wide Web is extremely extensive, complex, and continuously changing. 

That is why pulling out the necessary data can be difficult. It is essential to know how a site works before you try to obtain its data. 

Common Mistakes

There are a few common mistakes inexperienced scrapers can make. Let’s see into them.

When you send the same user agent, proxy, or header your requests generate the same footprint and make the site notice your scraping bot.

The same happens, if your requests do many redirects, especially if they are running at 404 pages or those never existed. Your crawler should stay anonymous, that’s the key to successful scraping.

You haven’t enabled JavaScript. Nowadays the chances to succeed with a CURL request without it are really low if not close to failure.

Besides the common mistakes you can avoid, there are the most usual challenges you may face as a scraper. They are also worth our attention.

Key challenges of web scraping

The “unconventional” users, who try to grab data, are not welcome and sites use various tools and create obstacles to prevent it.

You can find out the “dos and don’ts” of each site in the “robot.txt” file. This file defines the rules for the site users, and data scrapers as well. So, what are the challenges of web data scraping?

Bot access

Check if the site allows for data scraping and consider asking for permission if it does not. If you have received a rejection, then try to find alternative web resources with similar data.

Login requirement

Certain protected data may require users’ login. As soon as you’ve done it, the site is able to identify you with the help of cookies.

Complex and unstable web page structures

The common HTML pages structures are divergent, that’s why different sites will require specific scrapers each. Besides, you may face the necessity to adjust your scarping bot every time they update their content, web page, or add features.

Dynamic content

Many sites have dynamic content and update it. For the automatic crawlers, it’s challenging to overtake infinite scrolling, show more buttons or lazy loading images.

IP blocking

Commonly, it happens after a site has detected multiple requests from the same IP. It can either ban it totally or restrict its access. IP proxy services save scrapers from such a problem.

CAPTCHA

To separate genuine people from bots, sites offer to solve CAPTCHAS. There are technologies to overcome it, but they may slow down the web scraping itself.

Unstable load/speed

In response to an inordinate amount of requests, sites may slow down or even fail. Then scraping fails as well, because bots and tools do not know how to handle such an emergency.

Honeypots

Honeypots are traps put on pages intentionally to catch crawlers, they may be in the form of a link that gathers the scraper’s information once they catch it.

Real-time data scraping

Scraping in real-time is vital when you need to compare prices, deal with financial, or check inventory. Still, there is always some delay since the data requests and delivery take time. 

Final thought

The challenges exist, and they will always be. But, the key principle of web scraping is the same: “treat the sites nicely and choose professional data scraping tools or services to effectively cope with challenges”.