Web scraping challenges, ranging from IP bans and data accuracy to legal compliance issues, can trip up businesses trying to use web data to fuel machine learning and to make better decisions. 

But there’s good news: if you understand these challenges, and know the available solutions, you can overcome most if not all of them. And this is exactly what we're going to help you achieve today.

Understanding the challenges of data scraping

The most common web scraping challenges can be divided into three categories: technical, legal, and ethical. Let’s start with technical since it tends to contain the biggest hurdles for web scrapers. 

Technical web scraping challenges 

Difficult website structures (and when they change)

Many web scraping challenges stem from difficult website structures, such as those found in dynamic or large websites. 

Dynamic refers to sites that use a lot of Javascript, AJAX, or a similar language to load dynamic content — e.g., interactive quizzes on an e-commerce website. 

Compared to simple HTML-code web pages, these are much more difficult to extract data from without access to advanced scrapers and specialized libraries. 

As for large websites, they take longer to scrape than the average site. Unfortunately, it's often these behemoths that house data you need in real-time, like prices or currency rates. 

Another challenge of scraping data occurs when the target website owner changes their site's structure for any reason — e.g., to improve user interface. 

Web scrapers are built according to a site’s structure, so when that structure changes they lose their ability to scrape it until they’re updated. 

Anti-scraping technologies

Some websites deploy technologies designed to catch non-human visitors and block them from extracting data. 

One example of this type of technology is bot prevention software, which analyzes website visitor behavior to separate humans from web scraping bots.

This can make it hard to scrape data from such websites without using advanced tools and techniques.

IP-based bans 

When a website owner or their anti-scraping technology identifies you as an unwanted scraper, they can ban your IP address from accessing their website. 

It’s sort of like being reprimanded at a food court for taking more than the socially acceptable amount of free samples from a single restaurant. 

IP bans usually happen when:

• You send the same request to a server multiple times per second (aka many parallel requests). 

• You make too many requests from the same IP address over a short period of time. 

It’s frustrating to have your IP banned because it means you can no longer collect data from the website. To make matters more brain-splitting, the owner doesn’t explain why you were banned. 

Scrapers bypass IP bans using various techniques, from delaying their requests to using proxy services. We'll go over other tactics in the solutions section.

Robots.txt issues

A website you’re trying to scrape may use a robots.txt file. This file instructs you on which parts of their site your bots are allowed to crawl, and which are off limits. 

For example, a website’s file might be the following:

User-agent: *

Disallow: /cgi-bin/

In this example, the website owner is recommending that no bots crawl their CGI Bin directory. 

The file may also include instructions for how to scrape the site, suggesting a specific crawl delay time, page visit time, simultaneous request rates, and more. 

Following the instructions of the robots.txt file will give your bots the greatest chance of avoiding bans. Failing to do so could result in being blocked from scraping the website. 

Honeypot traps

Who knew that thinking about web scraping challenges could summon images of Indiana Jones swinging over some crevice or sinkhole? 

Honeypot traps are essentially booby traps that the site owner has placed on their website to detect web scrapers, capture their IP addresses, and block them.  

A common example of a honeypot trap is a URL that’s hidden from human visitors but clickable to spiders, which unknowingly follow it and reveal your IP address to the site.  

Data quality assurance 

Generally, the more websites you scrape manually the harder it becomes to maintain data quality assurance.

For instance, if you're scraping thousands of web pages, it quickly becomes a tedious process to compare the extracted data with its source for inconsistencies. 

Maintaining quality data becomes even more difficult when you’re scraping sites that are constantly changing their content.

For example, an e-commerce site is going to adjust its product prices regularly, meaning you could be using outdated data if you aren’t scraping it frequently.

Sometimes scrapers also have trouble understanding the meaning of the textual information you’re scraping, which can lead to subpar output. 

Legal web scraping challenges 

Web scraping public data is generally legal, but the laws and regulations that will apply to you and your will defer based on what you are scraping. 

Avoiding copyright infringement

The majority of content you scrape on the web is going to be protected by copyright law. However, there are some exceptions that may still allow you to scrape and use copyrighted data. In the US, for example, there is the fair use doctrine that allows limited use of copyrighted material for certain purposes. The EU also has a defined list of copyright exceptions.Therefore, when scraping a website, you need to determine if your use is compliant with the applicable copyright law or if it falls within one of the exceptions. 

Following data protection laws

When web scraping, it’s also critical that you figure out if you’re scraping personal data (e.g. names, addresses, phone numbers) and/or sensitive data (e.g. biometric information, bank details, SSNs) 

Most countries have a data protection law and you need to identify which ones are relevant to your business. For example, if you are based in the US but are scraping personal data in the EU, you may be subject to the EU’s General Data Protection Regulation (GDPR). If you are based in California or scrape a significant amount of personal data from California residents, the California Consumer Privacy Act (CCPA) may apply to you.

Failure to follow the relevant data protection laws could cause your business to incur legal penalties and heavy fines. 

Unless you really need to collect personal data, consider descoping or anonymizing personal data if possible. 

Unfortunately, laws around data scraping can be complex for the layperson. Investing in legal guidance and working with an expert third-party data scraping company can help ensure that your scraping is compliant with the laws that apply to your specific use case. 

Ethical web scraping challenges 

In addition to complying with web scraping regulations, you also need to follow an ethical code of web scraping. 

For example, although it’s not necessarily illegal to design a web scraper that sends thousands of requests per second to a website’s server, it is ethically wrong, as it can slow down their website. 

Therefore, it’s crucial to limit your rate of requests. You have to take measures like this to ensure that you’re treating the website owner with respect, keeping your scrapers from unintentionally harming their site or their users’ experiences on the site. 

Strategies for overcoming data scraping challenges

Now that we’ve covered the major web scraping challenges, let’s look at how to solve them. 

Technical solutions 

Follow ban-prevention best practices

Getting blocked from a site is often the result of failing to effectively manage the technical web scraping challenges. 

Below are some techniques that’ll help you avoid these bans:

• Have your scrapers act “casual”: Set up your scrapers to seem like they aren’t actually scrapers. For instance, you can make them do random mouse movements or send requests at a slower rate (1 request per second). This way you avoid detection. 

• Adhere to the robots.txt rules: These files give you instructions on how to scrape and what you can scrape. Follow them to avoid bans.

• Avoid scraping during peak hours: Websites, like restaurants, have times when they’re usually receiving a lot of visits. A scrape at that time could overwhelm the site. 

• Set random delays between requests: Send your requests at a frequency that is allowed by the robots.txt file to avoid crashing the site. To go a step further, make the gap between them random, so as to look less like a bot. 

• Use proxy rotation: A proxy network allows you to dress up as a new IP address every time you visit a site. Rotate your proxies to avoid ip blocking. 

Doing all of this might be manageable if you're scraping just a handful of websites. But when your extraction needs grow, you want a tool that’ll help you keep good form. 

Use a web scraping tool

Scraping multiple websites with varying structures all the while maintaining data quality and avoiding bans is a serious challenge for even the best developer teams. 

Fortunately, there are lean web scraping APIs out there that can help you do all of this in a cost-efficient manner. 

For example, Zyte API is an automated scraping tool that makes it easy to scrape websites of all levels of complexity, at scale. 

It also gives you all the anti-ban tools you need to retrieve data without getting blocked, from smart ban protection to automatic proxy rotation.  

Plus, Zyte API will automatically capture screenshots for you, making it easier for you to assess the quality of the data you collect. 

Using a tool will help your team spend more time interpreting and making decisions from data and less time collecting it. 

Outsource data extraction projects to a trusted third-party

If you’re doing large data extraction projects that entail the scraping of hundreds or even thousands of websites, it becomes even harder to maintain legal compliance. 

That’s why many businesses turn to third-party data extraction services like Zyte. These companies find, clean, scrape, and format the data for you, so that you don’t have to worry about legal compliance. 

Ethical solutions 

Using scraped data for pricing intelligence or any kind of research is one thing. Using it to rip off a business or to copy their content is another. 

Use the data responsibly: 

• Limit request ratios and set second-long intervals between them.

• Save only the data your company actually needs. 

• Establish a formal collection policy for your company. 

• Hold your data security to a high standard. 

• Document how you gather and use data. Be transparent.

If you follow these rules, you won’t just get better results from web scraping. You’ll also sleep better at night 🙂

Best practices for mastering data scraping

Below are three best practices of web scraping that’ll help you avoid many of the web scraping challenges altogether, and gradually march towards optimizing your approach.

Research and prepare before scraping 

It’s critical that you follow a data scraping process, and that your process begins with doing research to identify three key things:

• The questions you want answered

• The data points that will help you answer those questions

• And the websites that will provide that data

The last thing you want is to spend time and resources on a data scraper that returns a bunch of data you don’t actually need, and not much of the information that matters. 

Test and refine your scraping techniques

Testing and refining your web scraping tactics consistently over the long term will ensure that you’re working towards an optimized data extraction process.

According to Justin Kennedy, Software Engineering Manager at Disney, refining your techniques also helps you adjust to changes in web structure:

“Websites are changing all the time, both when websites change ‘naturally’ during the development process and when they change specifically to try to prevent scraping. This means constant refinement of scraping strategy is needed to ensure you can continually gather updated data sources.” — Justin Kennedy, Machine Learning at Disney Streaming

Continue learning and adapting to changes in technology and regulations 

The legal and technical landscape around web scraping is anything but fixed. 

New web scraping tools continue to pop up, and established companies continue adding new features and upgrading current ones. 

With all this activity, it can be hard to keep up. But there are resources to help — Zyte’s blog, for example. 

We have a team of experienced data scientists and developers that is eager to share the latest developments in the space.

Learning about new approaches and tools, then mastering them, will help you stay on the cutting edge and overcome new and old challenges of data scraping. 

Conclusion

Whether it's for market research or pricing intelligence, data scraping can help your business fuel its data drive decision making and gain a competitive advantage.

Knowledge is, after all, a source of power.

Of course, like anything worthwhile, it presents many challenges – IP-based blocking, legal compliance, quality assurance. But, with the right approach, you can overcome them. 

Use the above strategies, tools, and best practices outlined in today’s article and you’ll get the results you’re expecting from web scraping, without the headaches.