What you Need to Scrape Etsy Product Data: Methods, Services, and Challenges

When you are considering e-commerce giants, Etsy might not come to mind. Even so, don’t underestimate it. In Etsy’s marketplace, there are more than 2.1 million registered sellers presenting over 60 million items.

That’s why, when you are planning to scrape product data from Amazon, eBay, or Alibaba, the Etsy website should be also shortlisted. In this article, we’ll look through what methods can be used to scrape Etsy data, what challenges you may face, and what solutions are offered in the market.

Etsy.com is an e-commerce platform where millions of people all over the world buy and sell unique goods from handcrafted masterpieces to vintage stuff.

The mission of Etsy is to help people to turn their creative ideas into successful businesses. On Etsy.com, you can scrape and download data related to the following products:

• Arts
• Crafts
• Jewelry
• Food
• Paper goods
• Housewares
• Batch and beauty items
• Handmade personal care items
• Clothing and accessories

Before getting deep into scraping methods, let’s check out what products-related data you can scrape and download from Etsy. For example, you can scrape Etsy sales data, Etsy price history, Etsy seller's name, or just download Etsy reviews, and many other valuable data for further analysis. This could be very helpful to identify your target audience, make competitor research, or develop your sales strategy.

In order to build a web scraper on your own, you need to have some basic programming skills. So, this method is reasonable for those enthusiasts who are ready to accept challenges, go deep into programming, and learn something new. To retrieve product data from Etsy you can use the following languages:

• Node.js
• R
• Ruby
• Python and the BeautifulSoup

Now let’s review a simple Etsy scraper built with Python and the BeautifulSoup. In this example, it is planned to scrape just price data for a specific product type. So, first, it is needed to import the BeautifulSoup, Pyperclip, and Requests modules.

The next part of the code is showing that it created an HTTP request to the Etsy product list.

As it was planned to scrape just the price, the corresponding parameters were taken from Chrome’s inspector tool.

Not let’s get back to the Python program and paste in the code line:

And here it is, how the entire code looks like:

For those interested persons who are ready to pay for scraping tools, there are many options on the market. These tools are specially designed to make data scraping an easy process without any coding. You just need to know your requests and the tools will scrape them for you. With the help of these tools, you can easily scrape product descriptions, images, prices, and sellers’ lists as well as products’ rankings and reviews.

When it comes to data scraping, most business owners are still confused between purchasing a data scraping tool or outsourcing this job to web scraping companies that are experts in delivering data the way it is needed. Web scraping companies like DataOx are more reliable and experienced.

Let’s go through some advantages that you might have by choosing outsourcing Etsy data scraping:

• Ready to use data
• Completely managed process
• Unbroken data flow
• No maintenance required
• Different format for data delivery

In scraping e-commerce data there are some obstacles that might block you from getting quality product data. Especially, this should be taken into account, when you’re scraping data by yourself.

As a rule e-commerce data extraction implies large-scale scrapping which can be a real challenge for business owners. Anyhow, scraping an enormous amount of data from e-commerce websites like 50+ subcategories under several main categories isn’t an easygoing task. So, all the related measures should be taken for successful data scraping, and only true scraping experts can handle it faster by avoiding lower data quality.

Another challenge is getting blocked. The most common reason is IP addresses. When you send many requests for data within a certain period of time, the web server understands that it is a bot and blocks the corresponding IP address.

There are many techniques that reduce the chance of being blocked, like:

• Using IP proxies,
• Clearing cookies,
• Adjusting scraping speed,
• Switching scraping agents.

One more challenge that you may face is the Captcha issue – one of the most popular anti-scraping techniques. It is used not to overload the server by sending too many requests. Simple Captchas like for login can be resolved by a specially designed web scraper, but there are many anti-Captcha providers who solve advanced mathematical Captchas or image-based Captcha.

You can scrape Etsy and retrieve product data using R, Ruby, Python and BeautifulSoup, or ProxyCrawl platform for anonymous web scraping. However, most businesses that need precise data and don’t have in-house developers use the services of outsourcing web scraping experts like DataOx. Moreover, only professionals can extract sensitive data like sales quantity and revenue.

Etsy has documentation for different API operations, one of them is getListing. It retrieves the listing and product details by listing ID (a numeric integer mentioned on the page and URL after the /listing/).

Some online scrapers allow getting image URLs from Etsy. The shop has an open-source API with a ListingImage element. It is a resource for Etsy sale images in 5 available sizes.

At DataOx we offer the best Etsy web scraping services, as we know that extracting data from e-commerce websites requires high technical expertise. With our dedicated web scraping team, you’ll get the required data in your preferred format without facing any challenges and issues associated with scraping Etsy.

Schedule a free consultation with our expert to reveal the whole list of our web scraping services and find out how our services can be a better way than scraper tools or developing your own scraper.