Crazi Co, a growing eCommerce analytics platform delivering market intelligence and competitive insights sought to enhance its data capabilities for product and shop-level performance tracking. The platform required advanced scraping, metric computation, and API-driven filters to deliver actionable insights like revenue trends, shop ratios, and creator analytics.

The client sought Oodles to enable accurate product intelligence by extracting category-level data, calculating revenue-based shop ratios, and deriving creator metrics. It covered data scraping optimization, multi-threading implementation, and building API filters across category, shop, and product pages to improve analytics accessibility and performance tracking.

The solution enhanced the platform’s data intelligence by combining structured scraping, scalable processing, and advanced analytics logic to deliver meaningful insights across products, shops, and creators.

• Category-Level Data Extraction: Implemented breadcrumb-based parsing to accurately identify and classify products into hierarchical categories. 
• Revenue & Shop Ratio Computation: Developed grouped data processing logic to calculate revenue per shop along with top 3 and top 10 shop contribution ratios.
• Revenue Growth Analytics:  Extended the existing scraping framework to compute revenue growth rates and exposed this data for trend analysis.
• Creator Insights Mapping: Enabled creator-level analytics by mapping unique creator identifiers to product data, allowing accurate calculation of creator count and supporting further analysis.
• Multi-threaded Scraping Architecture: Implemented multi-threading workers to handle large-scale product scraping efficiently.