Table of Contents
- 3 Reasons to Scrape Alibaba.com
- How to Create Alibaba Crawler
- Extracting Product Data from Alibaba
- Final Thoughts
IntroductionWhen you collect product data from huge e-commerce websites like Alibaba you get a great opportunity to do comprehensive competitive research, market analysis, and price comparison. It is one of the leading e-commerce portals with an enormous product catalog. However, extracting the required Alibaba data is a real challenge if you are not familiar with web scraping. But if you know the stuff and have some coding skills go through this article to find out how to extract Alibaba products’ data through Scrapy – one of the most widely used open-source frameworks for web scraping.
3 Reasons to Scrape AlibabaData extracted from e-commerce websites is a potential help to businesses that are in e-commerce and not only. Keep reading to learn three main reasons why you need to scrape data from Alibaba.
Cataloging and listingFor any e-commerce business listing and cataloging competitors’ products are the most important thing. Without an up-to-date and comprehensive product list, it is impossible to compete in the e-commerce market. So, using Alibaba extractor, you can easily get Alibaba info and build your own product list based on your target audience’s demands and preferences or even create a new category of products.
Analyzing dataTo do complete market research companies strive to get insights from the buyers’ feedbacks like ratings and reviews. This user-generated content will give you a clear sign of a particular product or brand. This kind of data might be used to improving your current products or offer a new one as well as build a positive brand reputation.
Comparing pricesToday Alibaba is well known for its affordable prices, that’s why it is crucial to extract its prices for further price comparison and optimization. Almost all e-commerce users are tracking product prices, and Alibaba may be the most popular source to track in the first turn. So, if you want to know prices in the market to optimize your price strategy, start with Alibaba scraping!
How to Create an Alibaba CrawlerWritten in Python, Scrapy is one of the most efficient free frameworks for web scraping that enables users to extract, manage, and store information in a structured data format. It is perfectly adapted for web crawlers extracting details from various pages. Let’s move forward to learn how to scrape data from the leading marketplace.
Scrape Alibaba – Getting startedTo create an Alibaba crawler you need to have Python 3 and PIP. Follow the links to download them:
Creating Alibaba Scrapy projectThe next step is to create a Scrapy project for Alibaba with the scrapy_alibaba folder name containing all necessary files. The command is the following:
Creating the crawlerThere is a built-in command in Scrapy called genspider that is responsible for generating the primary crawling template. To generate our crawler that will create spiders/scrapy_alibaba.py file it should be: The complete code should look like:
Extracting Product Data from AlibabaIn this example, we’re going to extract the following fields for the earphones: https://www.alibaba.com/trade/search?fsb=y&IndexArea=product_en&CatId=&SearchText=earphones&viewtype=G</a >
- Name of the product
- Link to the product
- Minimum number of orders
- Name of the seller
- The response rate of the seller
- Number of years as a seller on Alibaba
- Create a Selectorlib library
- Create a keyword file
- Export data in the required format