We’ve all benefited from reliable data over the internet. But stumbling across bogus and low-quality information isn’t uncommon for us either. So, while the web unveils hidden jewels, it opens trash can lids, too.
Of course, no one wants to consume substandard data.
Essentially, if you run a business and rely on big data to make critical business decisions, nothing can wreak havoc on your company more than depending on low-quality data.
So, before you search for how to extract data from a website, it is crucial to understand how to harvest QUALITY data from websites. However, if you feel unfamiliar with the web scraping process, definitely check it out.
Say you run a clothing company and just launched a new T-shirt collection. Because your competitors are selling similar T-shirts for $10, you labeled it $11 to make up for a competitive price tag.
But how did you discover competitor pricing? Through the last web scraping project – your marketing team held.
After a few weeks, you notice that competitor T-shirts are all sold out, and you sold only a single item. At this point, you may discover you ran into the wrong data when scraping for prices, and the actual competitor pricing was $17.
That’s precisely how unreliable data affects your business.
Although web scraping is an excellent way to gain valuable business insights, relying on false data can negatively impact your business, from increased email churn to getting blocklisted and providing wrong content to customers and prospects.
Data reveals that poor quality data costs companies between 10-30% of revenue. So, sub-par data also wastes business resources and reduces profits, apart from harming your business reputation.
The internet has over 44 zettabytes of data. The reason behind tons of internet data is that it costs nothing to generate and distribute.
Anyone can produce a content piece and upload it – there is no quality barrier. Besides, no one enforces a minimum standard for online data.
The result? We consume all sorts of data – low and high quality – and regrettably, most of it is low-quality data.
A few reasons that contribute to the questionable quality of data include not updating the data regularly and human error. Unfortunately, however, a few people choose to upload substandard data on purpose.
Good thing you know how to extract data from a website, but understanding how to extract quality data is imperative if you want to make the most out of it.
You must find reliable websites with authentic data to begin your scraping projects. So, the reliability of your data drastically depends on the authenticity of the websites. If a site is trustworthy, it’ll naturally have credible information.
Here are a few tips to keep in mind when choosing websites for your scraping tasks.
Experts believe that a website with numerous broken links isn’t an ideal source to extract the data. Broken links depict the website administrator’s negligence, and indeed you cannot rely on the data quality.
So, apart from unreliable data, your web scraper will also encounter issues when interacting with broken links, affecting your entire web scraping plan.
As a rule of thumb, avoid harvesting data from websites that do not allow bots.
When you set up a crawler to extract data from sites, you may experience frequent blocks. Although you can avoid this problem by setting up rotating proxies, pros recommend not to keep such sites on your list to begin with.
Why? Because you may lose the data when these sites would implement enhanced blocking functionalities. So you’ll not only put additional effort during scraping, you may struggle with unreliable and incomplete data later.
Not everyone talks about website design when it comes to scraping because web scrapers do not care about a site’s design. Regardless of how the website looks, a scraper can extract the data.
Nonetheless, pros believe that websites with a clutter-free, simple, and navigable interface are trustable. On the flip side, an unclear and low-quality user interface signifies compromised information quality. Therefore, it is always better to choose the former.
Data relevancy is of the most important considerations during web scraping. Anyone can upload content on sites, but not everyone keeps it up to date.
Outdated information is no longer relevant and thus unreliable. Extracting such data will only risk your business and negatively impact your revenue. Make sure you pick the websites that update their content regularly to include the latest data.
While too much information on the web is a plus, it comes with a risk. Extracting and depending on low-quality data can be detrimental to your business.
Telling apart reliable information from inauthentic information is an art, and you must learn it before performing web scraping.
Otherwise, there’ll be no point in setting up a scraper and using reliable tools for scraping.
Make sure you make the most out of your scraping tasks by following the tips shared above.