Automated E-Commerce Ranker

Automating Product Ranking Activities Across Multiple European E-Commerce Platforms

PROBLEM

STATEMENT

The client needed an automated system to improve the ranking of several products listed on different e-commerce stores in Europe. They were doing the activities (add to cart, add to wishlist, etc.) manually and it was taking hours and hours of work to achieve the desired results. All these sites are well-protected, and it was a challenge to develop a scalable solution that can handle an ever-increasing number of products.

SOLUTION

I implemented customized bots for each E-commerce store including Bol, Otto, Cdiscount, and Kaufland to replicate the manual work and incorporated Bright Data proxy services to ensure a blocking-free experience. I also utilized other techniques, like mimicking human behavior, adding delays, setting up an undetected chrome driver, and user agent rotation to avoid blocking issues. In order to provide better coverage, the scripts were scheduled to run at different times of the day through cronjobs. Each bot was run in a different docker container.

Input

Products and keywords for each platform (in a Google Sheet)

 

Tutorial for the desired activity on every website

Output

The products on all the E-commerce websites were ranked at desired spots

Tools &
Technologies

Automated E-Commerce Ranker

Python

Automated E-Commerce Ranker

Selenium

Google_Chrome_icon_(February_2022).svg

Undetected chrome

cronjob.png

Cronjob

Automated E-Commerce Ranker

Bright Data

Google_Sheets

Google Sheets

GCP Compute Engine VM

Linux

Linux

Wikipedia Scraping

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