A digital analytics initiative focused on extracting insights from TikTok eCommerce approached Oodles to build a scalable backend data intelligence system. The client required a robust platform capable of scraping TikTok Shop and product data to analyze revenue performance, category trends, creator influence, and Shop metrics to inform business decisions.

The client sought Oodles to build a backend scraping infrastructure to collect and process product, shop, and category-level insights from TikTok. They required a scalable pipeline capable of performing stealth browsing, extracting dynamic data, processing metrics, and exposing APIs for analytics such as revenue trends, shop performance tracking, and product-level insights.

The solution focused on extracting dynamic product and shop information while maintaining stealth browsing and system stability.

Key features implemented are:

• Containerized Puppeteer Scraper: Developed a Dockerized Puppeteer scraper to navigate dynamic TikTok pages and reliably extract product, shop, and category data.
• Stealth Headless Browsing: Configured the scraper environment to mimic human browsing behavior. 
• Analytics API Layer: Developed backend APIs to provide structured access to insights, revenue growth trends, product performance, etc. 
• Telegram Bot Integration: Implemented a Telegram-based interface for user registration.
• Data Storage and Processing: Integrated MongoDB to store scraped datasets. 
• Scalable Architecture: Designed the system with containerized services to support future scalability.