Visual web scraping tools are great. They allow people with little to no technical know-how to extract data from websites with only a couple of hours of upskilling, making them great for simple lead generation, market intelligence, and competitor monitoring projects. Removing countless hours of manual entry work for sales and marketing teams, researchers, and business intelligence teams in the process.

However, no matter how sophisticated the creators of these tools say their visual web scraping tools are, users often run into issues when trying to scrape mission-critical data from complex websites or when scraping the web at scale.

In this article, we’re going to talk about the biggest issues companies face when using visual web scraping tools like Mozenda, Import.io, and Dexi.io, and what they should do when they are no longer fit for purpose.

First, let’s use a commonly known comparison to help explain the pros and cons of visual web scraping tools versus manually coding your own web crawlers.

The visual website builders of web scraping

If you have any experience in developing a website for your own business, hobby, or client projects, odds are you have come across one of the many online tools that say you can create visually stunning and fully featured websites using a simple-to-use visual interface.

When we see their promotional videos and the example websites their users have “created” on their platforms we believe we have hit the jackpot. With a few clicks of a button, we can design a beautiful website ourselves at a fraction of the cost of hiring a web developer to do it for us. Unfortunately, in most cases, these tools never meet our expectations.

No matter how much they try, visual point and click website builders can never replicate the functionality, design, and performance of a custom website created by a web developer. Websites created by visual website builder tools are often slow, inefficient, have poor SEO, and severely limit the translation of design requirements into the desired website. As a result, outside of very small business websites and rapid prototyping of marketing landing pages, companies overwhelmingly have professional web developers design and develop custom websites for their businesses.

The same is true of visual point and click web scraping tools. Although the promotional material of many of these tools makes it look like you can extract any data from any website at any scale, in reality, this is often never true.

Like visual website builder tools, visual web scraping tools are great for small and simple data extraction projects where lapses in data quality or delivery aren’t critical, however, when scraping mission-critical data from complex websites at scale then they quickly suffer some serious issues often making them a bottleneck in companies data extraction pipelines and a burden on their teams.

With that in mind, we will look at some of these performance issues in a bit more detail...

Efficiency when scraping at scale

Visual point and click web scraping tools suffer from similar issues that visual website builders encounter. Because the crawler design needs to be able to handle a huge variety of website types/formats and isn’t being custom developed by an experienced developer, the underlying code can sometimes be clunky and inefficient. Impacting the speed at which visual crawlers can extract the target data and make them more prone to breaking.

Oftentimes, these crawlers make additional requests that aren’t required, render JavaScript when there is no need, and increase the footprint of the crawler increasing the likelihood of your crawlers being detected by anti-bot countermeasures.

These issues often have a little noticeable impact on a small scale and infrequent web scraping projects, however, as the volume of data being extracted increases, users of visual web scrapers often notice significant performance issues in comparison to custom-developed crawlers.

Unnecessarily, putting more strain on the target websites servers, increasing the load on your web scraping infrastructure, and make extracting data within tight time windows unviable.

Increased data quality & reliability issues

Visual web scraping tools also suffer from increased data quality and reliability issues due to the technical limitations described above along with their inherent rigidity, lack of quality assurance layers, and the fact their opaque nature makes it harder to identify and fix the root causes of data quality issues.

• Flexibility - Due to the automated and rigid nature of visual web scraping tools, the crawlers they develop may be overly specific in extracting data from a website. This means that if there is even a small change in the website's structure, the crawler could break. In comparison, experienced crawl engineers can design their crawlers from the outset to be much more flexible to website changes, etc. making them much more reliable.
• Limited Visibility of Crawlers Inner Workings - With visual web scraping tools you have limited visibility of precisely how it is crawling the target website making it harder to identify and fix the root causes of data quality issues.
• Quality Assurance Layers - With visual web scraping tools you have less control over how your crawlers and data feeds are being monitored and checked for data quality issues. Making it harder to maintain data quality and troubleshoot any issues that inevitably will arise.

These issues combine to reduce the overall data quality and reliability of data extracted with visual web scraping tools and increase the maintenance burden.

Complex websites

Another drawback of visual web scraping tools is the fact that they often struggle to handle modern websites that make extensive use of JavaScript and AJAX. These limitations can make it difficult to extract all the data you need and simulate user behavior adequately.

It can often also be complex to next to impossible to extract data from certain types of fields on websites, for example, hidden elements, XHR requests, and other non-HTML elements (for example PDF or XLS files embedded on the page).

For simple web scraping projects, these drawbacks might not be an issue, but for certain use cases and sites, they can make extracting the data you need virtually impossible.

Anti-bot countermeasures

Oftentimes, the technical issues described above aren’t that evident for smaller-scale web scraping projects, however, they can quickly become debilitating as you scale up your crawls. Not only do they make your web scraping processes more inefficient and buggy, but they can also stop you from extracting your target data entirely.

Increasingly, large websites are using anti-bot countermeasures to control the way automated bots access their websites. However, due to the inefficiency of their code, web crawlers designed by visual web scraping tools are often easier to detect than properly optimized custom spiders.

Custom spiders can be designed to better simulate user behavior, minimize their digital footprint and counteract the detection methods of anti-bot countermeasures to avoid any disruption to their data feeds.

In contrast, the same degree of customization is often impossible to replicate with crawlers built using visual web scraping tools without getting access to and modifying the underlying source code of the crawlers. Which can be difficult to do as it is often proprietary to the visual website builder.

As a result, often the only step you can take is to increase the size of your proxy pool to cope with the increasing frequency of bans, etc. as you scale.

Experiencing issues with your visual web scraping tool?

If you are using a visual web scraping tool with zero issues and have no plans to scale your web scraping projects then you might as well just keep using your current web scraping tool. You likely won’t get any performance boost from switching to custom-designed tools.

Although current visual web scraping tools have come along way, currently they often can’t replicate the accuracy and performance of custom-designed crawlers, especially when scraping at scale.

In the coming years, with the continued advancements in artificial intelligence, these crawlers may be able to match their performance. However for the time being, if your web scraping projects are suffering from poor data quality, crawlers breaking, difficulties scaling, or want to cut your reliance on your current provider's support team then you should seriously consider building a custom web scraping infrastructure for your data extraction requirements.

In cases like these, it is very common for companies to contact Zyte to migrate their web scraping projects from a visual web scraping tool to a custom web scraping infrastructure.

Not only are they able to significantly increase the scale and performance of your web scraping projects, they no longer have to rely on proprietary technologies, have no vendor lock-in, and have more flexibility to get the exact data they need with no data quality or reliability issues.

Removing all of the bottlenecks and headaches companies normally face when using visual web scraping tools.

If you think it is time for you to take this approach with your web scraping, then you have two options:

1. Build it yourself; or,
2. Partner with an experienced web scraping provider

At Zyte, we can help you with both options. We have a comprehensive suite of web scraping tools to help development teams build, scale, and manage their spiders without all the headaches of managing the underlying infrastructure. Along with a range of data extraction services where we develop and manage your custom high-performance web scraping infrastructure for you.

If you have a need to start or scale your web scraping projects then our Solution Architecture team is available for a free consultation, where we will evaluate and develop the architecture for a data extraction solution to meet your data and compliance requirements.

At Zyte we always love to hear what our readers think of our content and would be more than interested in any questions you may have. So please, leave a comment below with your thoughts and perhaps consider sharing what you are working on right now!