eCommerce websites contain very valuable data like prices, reviews, and images harvested properly could give an advantage. This article will show you how to web scrape data from eCommerce websites
By Admin @August, 3 2022
THE NEED FOR SCRAPING E-COMMERCE WEBSITES
There will be a lot of reasons to scrape e-commerce websites, one of the fastest ways of making money is commerce and that means a lot of people invest in it. And the websites where commerce activities take place are called e-commerce.
Statistics
This means there are many online shop owners and they will need to build a lot of automation around e-commerce websites because they will want to stand out among competitors. Shop owner in their plan to improve their products and have better sales and conversions will need:
Being able to scrape e-commerce websites will be a valuable skill to learn. This guide teaches you how to go about it.
WHY SCRAPE ECOMMERCE WEBSITES?
Staying competitive while running an online business is imperative and using data publicly available online can give you an advantage.
These are the most popular use-cases of e-Commerce web scraping
- Competitor monitoring
- Price Monitoring
- Monitor reviews
- Collect product descriptions / images
- Product research
- Data for dropshipping website
WebScraping for eCommerce webinar
UNDERSTANDING ECOMMERCE SITE STRUCTURE
Product page: Product details page and would contain one single product and all associated information like price, description, name along with a picture of the product. As ecommerce sites use this product page as a template, all products listed on the same site will have the same product page design.
Listings / category Page: This is a page on a website which displays a list of all identically structured items. For eCommerce a product listing page lists all products based on a category or search query. It can also be referred to as “category pages,”
CREATING A STRATEGY TO WEB SCRAPE E-COMMERCE WEBSITES
Scraping any website requires a mode of operation and they depend on your aim, the same applies to e-commerce websites. The first step is
1. Knowing what you want.
If you want to extract product data for instance, you will want to know all the categories you want the product data from, all the kinds of data you need. It might be as simple as just the product names, images, categories, and images. And you might want to include average ratings, each customer's rating and review. It could even be a more complex market research where you also need to make some comparisons, get the available data from the seller, and maybe customers.
You might want to build a scraper that uploads products to one or more e-shops. And you might want to extract data and still carry out some other web activities like adjusting products' prices.
2. Researching the e-commerce website
You also need to know the e-commerce website you want these data from. You want to know:
If they have the data you require
After knowing what you want, you will want to check out the e-commerce website you want to get the data from. You will want to know if they have all the data you require, good if they do and if not, you want to know how to get the other data. You might want the sellers 'and customers' email addresses and phone numbers and not see it on the e-shop, you will want to check whether they have websites or social media info where you can get these data from.
The architecture used
The next step will be to determine if a regular scraper will work on the website or if it is javascript-dependent and only a scraper that uses a headless browser will succeed in getting the data. You can do this by viewing the html source and checking if all the data is present, if it is, you can be more sure a regular scraper works and if not, a headless browser will be needed. If there is a lot of buttons to click, popup dialogues, and other kinds of dynamic responsive, it is likely you will need a headless browser.
Most e-commerce websites require a headless browser
How to get the data
Here is the stage where you explore the website with the aim of knowing where the data are displayed, some data will be on the products' pages while to get some data, you will need to click on some buttons, visit other pages. For instance, the name, description, average ratings and price might be on a product's page while you have to click a button to see the customers 'reviews, click to see the sellers' info, click to see other data you need.
While clicking captchas might be present, if so, you have to equip the scraper with the ability to solve captchas. As you explore, be on the lookout for other barriers the scraper might encounter and make it go in fully prepared.
Captchas are mostly required to be solved before being able to view contact information like email addresses and phone numbers
How to extract data from Amazon in minutes using Ready to Go extractors
3. Create a scraper
At this stage, you know the data you want and how to get them. You are qualified to use the flow of how you manually got the data to create a web scraper to automate what you did manually on a product on a lot of other products - as many as you want.
Create a scraper without writing code
You can easily create a web scraper with WebAutomation.io without having to write code, there is a visual interface for you to create a full-fledged scraper by using the flow you got in step 2. You can simply use the interface of WebAutomation to get a good flow and make the scraper use the flow to extract the data you want. And you can skip step 2 by just telling an expert at WebAutomation your needs and have your scraper created for you. Depending on your needs, you could get a dashboard where you manage the crawler.
How to easily create an Amazon Scraper with WebAutomation
Using the Ready to go web scrapers:
WebAutomation has a library of ready to go scrapers already built for the most popular e-commerce sites follow thes below steps to get data from one of these. See Article: Introducing Pre-Defined Ready to go extractors
Writing code
You should first check out if there is an (official) API, APIs make getting the data relatively easy for you unlike creating a regular scraper or a headless browser, you only have to call the API endpoints and get the data you need. While using official APIs, you might not be able to get all the data you need
If there are no APIs or the data you require are not present in the API, you can then create a regular scraper or a headless browser based on the architecture used by the website which you discovered at step 2, you should check out our guide to scraping a regular website and how to web scrape javascript contents to make a headless browser if the website is javascript-dependent. It as well contains a guide on how to select product’s attributes (like name, brand, price, and description) by the attributes of their DOM elements
FINALLY
After creating your scraper, the next step is scheduling your web scraper to auto run and the final step is maintaining your web scraper. E-commerce websites are known for changing html formats and using anti-scraping techniques and algorithms to detect web scrapers and block them.
If you created your web scraper with WebAutomation , you do not have to worry about scheduling your scraper and anti-bot techniques being used to block the scraper. Experts do this for you so that your web scraper is always up and running. And there are high-end machines where scrapers are comfortable to work well
If you have chosen to write your own codes, then refer to How to avoid getting blocked while web scraping
REFERENCE
Linkedin