The Ecommerce Data-Driven System is intended to track the pricing comparison across 100 different e-commerce websites for a given product.
Stages
1st Step: This system’s first step is to gather the products from 100 e-commerce websites, like amazon.com, ebay.com, walmart.com, shopee.com, and so on. The critical data points are:
- Product name
- Product URL
- Description
- UPC
- Category
- Brand
- Image, and
- Price
Since there are several products, the scrapers gather them one category at a time.
2nd Step: This step is database management. The scraped products are kept in the PostgreSQL database. The database needs to be duplicate-free and updated daily or weekly.
3rd Step: Once the products have been added to the database; the ML model begins to select the same product from several sources. The model also sorts the same products into categories and adds them to the database.
4th Step: In this final phase, the website displays the product together with current price comparisons from various sources and real-time pricing changes. The website assists you in doing product searches, tracking pricing changes, and making comparisons between 100 sources.
Project Details
- Category: E-commerce Industry
- Client: Jeremy
- Location: Singapore
- Manager: Wilson Chan
- Year Completed: 2021
- Project Value: 90k