3 Challenges Web Scraping Faces in Getting Ecommerce Data

4 min read


Data is the new oil. Business owners use data to spot lucrative opportunities in the market, better exploit potential customers and maintain the current. As online business prospers, turning a blind eye to ecommerce data can put you into a vulnerable place.

Ecommerce data can be used in various ways:

  1. price and stock monitoring
  2. MAP compliance
  3. marketing activity tracking
  4. customer sentiment analysis
  5. SERP tracking for SEO marketers

Web scraping is the most efficient way to get web data. However, you are likely to encounter tricky problems during web scraping. This article aims to give you early alarms of what challenges you may meet and instructions of how to deal with them.

Data Timeliness

Data on web pages are changing constantly and outdated data may lose its value. How frequent should you update your data? This depends on what data you are using and for what purpose. If you are scraping from ecommerce websites to monitor the stock number of certain products, you may want daily updates to see how the product sells each day. When it comes to data scraping for MAP monitoring purposes, frequent updates are required in order to guarantee the effectiveness.

In many different scenarios, you have to get timely data to make value out of it. The problem is, if you are scraping from dozens of different sites, without a functional scraping tool, you have to manually start your crawlers repeatedly, which can be a time-consuming chore and drag down your working efficiency. Fortunately, to avoid these repetitive jobs, you don’t need to be a master in coding now. Web scraping tools such as Octoparse offer automated scheduled scraping that can free you from such trouble.

Data Cleaning

Many ecommerce business owners use web scraping tools to get data and guide their decision-making. However, scraped data does not equal business insights. You can only dig the value out of your data when it is well organized and thoroughly analyzed. In most cases, raw data presented on ecommerce pages is not well prepared for analysis. 

For example, if you are calculating the average ratings of a series of products, you would expect all data presented in numbers only. However, raw data scraped from web pages may not be that satisfactory – the number could be wrapped in a bunch of words. Read along and you will learn how a web scraping tool helps organize you data as you wish.

Voluminous Scraping

Most of our eCommerce clients scrape data on a large scale due to the large number of online marketplaces and the diversity of products in each store. Just take one single ecommerce marketplace, Amazon, as an example. There are 20,000 results for “earphones”and 30,000 records for “couches”. The number may be cut down when you enter a more narrow-down query. While if you are scraping the information of a bunch of products on multiple ecommerce platforms, the volume still would be considerable.

The challenge of voluminous scraping is that your tasks would take a long time to complete and frequent visits of a site can trigger its anti-scraping mechanism, causing prolonged waiting, heavy system workload and IP bans.

Web Scraping Solutions 

There are many different web scraping tools capable of scraping ecommerce data. I will take Octoparse as an example to see how web scraping tools tackle challenges mentioned above.

  • In order to meet users’ demand of timely data, Octoparse developed the feature of scheduled scraping by which you can set your crawlers to run at intervals – hourly, daily, weekly and more customized settings. Together with API connection, you can get the updated data regularly, directly in your system and leave alone the tasks to do their own scraping jobs.
  • When the data is scraped and saved in your system, to clean and restructure the data afterwards would take a long time. In order to get well-structured data in the first place and skip the irritating data processing step, Octoparse offers the Regular Expression Tool for users to configure the crawler so that it can clean the data during its scraping.  
  • For now, anti-scraping techniques are widely used among different websites. If you are trying to get a tremendous amount of data across hundreds of web pages, you are likely to get banned by the site at some point. The solution to this problem is IP rotation and anti-blocking settings which can you help get around the site’s monitoring system and keep your tasks going. In addition, cloud service is the biggest plus for users scraping a great number of data. Running your tasks on the cloud server, you are not only freeing your computer from heavy workload, but also gaining speed in the scraping process.

Closing Thoughts

Most of your problems met in scraping ecommerce data can be solved if you choose a highly functional web scraping tool. Cling to the data, dig the value out, the efforts will definitely pay off. If you have any problems in web data scraping, please feel free to contact our support. The Octoparse team is happy to help.

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