The e-commerce industry is becoming increasingly data-driven. Product data scraping from Amazon and other large e-commerce websites is indeed an important piece of competitor analysis. Amazon alone has a huge amount of data (120+ million as of today!). Extracting this data regularly is a massive undertaking. We work with many customers at iWeb Scraping to help them gain data access. However, for a variety of reasons, some people require the formation of an in-house team to extract data. This blog post is for those who have to know how to set up and scale an in-house team. These suppositions will give us an idea of the scale, hard work, and challenges we will face. You Want To Extract Information About The Product From 20 Large E-Commerce Internet Sites, Including Amazon. Data From A Website Is Required For 20 – 25 Subcategories Within The Electronics Category. The Overall Number Of Subcategories Is Around 450. The Refresh Frequency Varies Depending On The Subcategory. 10 Of The 20 Subcategories Require Daily Refresh, 5 Require Data Every 2 Days, 3 Require Data Every 3 Days, And 2 Require Data Once A Week. Four Internet Sites That Use Anti-Scraping Technologies. Depending On The Day Of The Week, The Amount Of Data Ranges From 3 Million To 7 Million Per Day. Learning E-Commerce Data fields
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