How Certain Site Designs Mess With Data Extraction

Why is getting the right data from certain websites so hard?

Part of the problem is with the sites themselves.

They’re either poorly designed, so homegrown web scrapers break trying to access their data, or they’re properly designed to keep you out – meaning that even the best scraper might have trouble pulling data.

Even your own website might not be fully optimized to collect the data you want.

Some sites just aren’t as user-friendly for web scraping as others, and it can be hard to know before you start the process whether or not it’s going to work.

Being aware of site design challenges that might interfere with your web scraping is a start.

But it’s also important to know how to overcome some of these challenges so that you can get the cleanest and most accurate data possible.

Here’s what to know about bad site design that can mess with your data extraction.

Free download: 6 More Site Design Challenges to Getting Good Data

Sites Do Not Always Follow Style Guides

With a homegrown web scraper, you need consistency in style and layout to pull information from a large number of sites.

If you want to pull data from 10 sites, for example, but each one has a different layout, you might not be able to extract data all at once.

If you have a site where code contains mistakes, or they’re using images for certain information, or their missing information in their metadata, or really any number of inconsistencies… it will be unreadable to your scraper.

The trouble is that between amateur and even pro developers, styles, tools, code and layouts can all fluctuate wildly, making it difficult to pull consistent, structured data without break a scraper.

To top it off, many newer sites are built with HTML5, which means that any element on the site can be unique.

While that’s good news for designers and the overall aesthetics and user-friendliness, it’s not great for data extraction.

They might also use multi-level layouts, JavaScript to render certain content, and other design features that make it very difficult to pull clean data the first time through.

Some sites frequently change their layout for whatever reason, which might make your job harder if you don’t expect it.

Endless Scrolling Can Mean Limited Access to Data

Endless scroll – also called infinite scroll – is a design trend that has grown in popularity over the past several years.

To be fair, it’s a good tool for making sites mobile friendly, which can aid in SEO and usability. So there’s a good reason that many designers are using it.

Not all crawlers interact with sites to retrieve data or get links that appear when a page is scrolled. Typically, you will only get links that are available on initial page load.

There are workarounds for this, of course.

You can always find related links on individual post or product pages, use search filters or pull from the sitemap file (sitemap.xml) to find items, or write a custom script.

But unless your web scraper already has the ability to handle a process like that, you’re doing all of that work yourself.

Or you’re simply resigned to getting only the initial data from an endless scrolling page, which could mean missing out on some valuable information.

Some Sites Use Proxies to Keep You Out

Some of the most popular sites out there use proxies to protect their data or to limit access to their location, which isn’t necessarily a bad thing. You might even do that on your own site.

They will sometimes even offer APIs to give you access to some of their data.

But not all sites offer APIs, or some offer very limited APIs. If you need more data, you’re often out of luck.

This can be true when pulling data from your own site, especially if you use a proxy to hide your location or to change the language of your site based on a visitor’s location.

Many sites use proxies to determine site language, which, again, is great for the end-user but not helpful for data extraction.

At Diffbot we offer two levels of proxy IPs as a workaround for this, but a homegrown scraper may not be able to get through proxy settings to get the data they actually need, especially if there’s no API already available.

We also scrape from sites in multiple languages, which might not always be possible with a homegrown scraper.

Other Issues That Might Prevent Data Extraction

There are numerous other design reasons that might prevent you from getting complete data with a homegrown scraper that you might never think about.

For example, having an abundance of ads or spam comments might convolute the data you pull. You might get a lot of data, but it’s messy and unusable.

Even smaller design elements that might be overlooked by a developer – like linking to the same image but in different sizes (e.g. image preview) – can impact the quality of the data you get.

Small tweaks to coding, or some encoding methods, can throw off or even break a scraper if you don’t know what to look for.

All of these small factors can significantly impact the quality, and sometimes quantity, of the data you get from your extractions.

And if you want to pull data from thousands of sites at once, all of these challenges are compounded.

How to Get Around These Design Issues

So what can you do if you want to ensure that you have the best data?

It boils down to two options. You can:

  • Write your own scraper for each website you want to extract data from and customize it according to that site’s design and specifications
  • Use a more complex and robust scraping tool that already handles those challenges and that can be customized on a case-by-case basis if necessary

In either case, your data extraction will be good, but one is significantly more work than the other.

In all honesty, if you have a very small number of sites, you might be able to get away with building a scraper.

But if you need to extract data on a regular basis from a decent number of sites, or even thousands of sites (or even if you have a large site yourself that you’re pulling from), it’s best to use a web scraper tool that can handle the job.

It’s really the only way to ensure you will get clean, accurate data the first time around.

Here are 6 more design challenges that might impact your web scraping

Final Thoughts

Getting data from a multitude of sites with different designs and specifications is always going to be a challenge for a homegrown scraper.

Not all designers and developers think about data when they build sites, and not all layouts, designs, and user-friendly elements have the web scraper in mind.

That’s why it’s essential to use a web scraper that can handle the various needs of each and every site and can pull data that’s clean and accurate without a lot of fuss.

If you know what you’re looking for, you can build your own. But in all reality, it will be much faster and easier to use a tool designed to do the job.