3 Most Practical Uses of eCommerce Data Scraping Tools
by Octoparse 2020 Turn web pages into structured spreadsheets within
In today’s eCommerce world, eCommerce data scraping tools gain great popularity all over the world as the competition among eCommerce business owners gets more fierce year by year. Data scraping tools become the new technique and tool to help them improve their performance.
A lot of store owners find using an eCommerce data scraping tool to monitor competitors’ activities and customers’ behaviors can help them maintain their competitiveness and improve sales. If you have no idea how to make full use of eCommerce data scraping tools, stay with me and we will look into 3 most practical uses of a scraping tool and how the tool helps grow your business.
Three Practical Uses of Ecommerce Data
Price is one of the most critical aspects that affect customers’ buying interest. 87% of online shoppers indicate that price is the most important factor that affects buying behaviors, followed by shipping cost and speed. That research suggests that a potential customer won’t hesitate to leave your store if your price doesn’t match his expectation.
In addition, according to a study from AYTM, 78 percent of shoppers compare prices between two or more brands, then opt for the lowest price. With easy access to many free online price comparison tools, online shoppers can easily see the price of a specific item across dozens of brands and marketplaces.
It is necessary for online business owners to have an eCommerce data scraping tool to scrape price information from competitors’ web pages or from price comparison Apps. If not, it’s likely that you will have trouble attracting new customers to your store or maintaining your current customer base, because you don’t know when and how to adjust your price to cater to those price-sensitive customers.
We’re aware that improving the shipping service is another solution to increase sales. 56% online sellers offer free shipping (and easy returns) regardless of the purchase price or the product type.
Lots of online sellers use free shipping as a marketing strategy to nudge people to buy from them or even buy more from them. For example, it’s quite common that customers are more willing to spend $100 on a product with free shipping rather than buy a $90 product that takes $10 for the shipping. Besides, it’s common for customers to buy more items in order to get a free shipping offer.
You can use an eCommerce data scraping tool to find out how many of your competitors are offering a free shipping service. Using a data scraping tool, you can easily scrape and collect the data in real-time. In this case, if they don’t provide a free shipping service, you can attract their customers by offering it.
Knowing how your competitors’ audiences feel about the products or brands can help you evaluate your marketing strategy and customer experience management. ECommerce data scraping tools can help you gather such information.
The voices of customers that you gather from your competitors will help you understand what customers value and how you can better serve them. Their voices are mostly scattered among comments and conversation under your competitors’ stores and posts and interactions on their social media. With such information at hand, you will know what customers want from the product – what they like or dislike.
To outcompete your competitors, it is necessary for you to gain all those information, look into it and draw conclusions. Therefore you can adjust your marketing strategy or your products/services accordingly.
Now you are probably wondering what scraping tools can be used for these purposes. Here, I would like to share with you this shortlist of the most popular eCommerce data scraping tools. You should try them out!
3 popular eCommerce data scraping tools
Octoparse is a free and powerful eCommerce data scraping tool with a user-friendly point-and-click interface. Both Windows and Mac users will find it easy-to-use for extracting almost all kinds of data you need from a website. With its brand new auto-detect algorithm, users with/without coding knowledge are able to extract tons of data within seconds.
Pros: Octoparse provides over 50 pre-built templates for all users, covering big websites such as Amazon, Facebook, Twitter, Instagram, Walmart, etc. All you need to do is to enter the keywords and URL, then wait for the data result. In addition, it provides a free version for all people. For premium users, they can use features such as crawler scheduling and cloud extraction to make the process less time-consuming.
Cons: Octoparse cannot scrape data from PDF files. It can’t download files automatically, while it allows you to extract the URLs of images, PDFs and other types of files. You can use automatic download software to down these files in bulk with the URL scraped by Octoparse.
Pros: Parsehub supports both Windows and Mac OS systems. It provides a free version for people with eCommerce data scraping needs.
Cons: The free version is quite limited with only 5 projects and 200 pages per run. It didn’t support documentation extraction. And some advanced functions are tricky to use sometimes.
80legs is a web data extraction tool that allows users to create and run web crawlers through its software as a service platform. It’s built on top of a distributed grid computing network. This grid consists of approximately 50,000 individual computers distributed across the world and uses bandwidth monitoring technology to prevent bandwidth cap overages.
Pros: 80legs is more suitable for small companies and individuals. It offers unique service plans so that customers pay only for what they crawl.
Cons: 80legs is not able to help to get a huge amount of data, you must choose between custom set crawled data, pre-built API, and crawl application to be developed.
Once you know how to use eCommerce data scraping tools to help you get the needed data, what insights you can gain from the data is another story. Try to do some data analysis and find ways to visualize the data. Put your data into use.
You can try the simple analysis methods mentioned in this article to get to know your users through data analysis.
Created on Oct 28th 2020 02:40. Viewed 141 times.