A Comprehensive Walkthrough: Scraping and Cleansing eBay Product Data in Simple Steps
Originally published as https://reurl.cc/0E7gY6
Today, we’ll show you step by step how to build your own no-code eBay web scraper to collect eBay product data in bulk. And then we’ll conduct a quick research using the extracted data (price, sold number, product specification, availabilities, and more) to analyze if one kind of product sells better than the other kinds of product. If you are in the eCommerce business or are looking to run a similar analysis, definitely read on.
Table of Contents
- Why scrape eBay product data
- Define a goal for the study
- Collect data — Scrape product data using Octoparse
- Clean data — turn data into usable formats using QuickTable
- Analyze data — visualize the data using charts and graphs
Why scrape eBay product data
As a globally popular C2C e-commerce platform, there are more than 1.7 billion product listings on eBay, making it an irreplaceable data source for all kinds of business analysis. It enables you to gather a variety of data, such as product categories, price specifications, prices, availabilities, top sellers, sales, etc. This data can be valuable for finding the perfect marketing niche for your business, setting the right prices for the products you’re selling, monitoring how your customers are liking your products, sneaking around your competitors, and much more.
Define a goal for the study
The purpose of this study is to find out if there is a relationship between the prices, sold numbers and scales of the toy vehicles that are selling on eBay. For our source data, we’ll run a quick search on eBay using the keyword “toy car”. What we’ve got in the search results is the product data we need for the research, especially, this is the URL to the search results: https://www.ebay.com/sch/i.html?_from=R40&_nkw=toy+car&_sacat=0&_pgn=35