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Automated E-commerce Data Collector — Images, SKUs, Details Extraction

· 2 min read
CCLEE
CCLEE

TL;DR​

Developed an automated data collection tool for an e-commerce client. Used browser-executed JavaScript to capture product images, review images, SKUs, prices, descriptions, and customer reviews in real-time. Python scripts handled data cleaning, deduplication, and export to structured CSV/JSON/PDF formats. Extracted thousands of records to support inventory management and competitive analysis.

Background​

The client operates an e-commerce platform and needed to collect competitive and internal product data for operational decision-making. Manual data entry was slow, error-prone, and couldn't scale to meet their data volume requirements.

Solution​

We used browser-executed JavaScript for data scraping, running scripts via DevTools/Console to capture product images, review images, SKUs, prices, descriptions, and customer reviews in real-time. The scripts supported auto-pagination to ensure complete extraction.

Collected data was processed through Python scripts for cleaning, including deduplication and format standardization. Final output was exported to CSV, JSON, or PDF formats based on the client's use case.

Results​

After deployment, the client went from hours of manual work per session to a single click execution. Each run extracts thousands of records with accuracy levels suitable for direct analysis. Collection frequency increased from weekly to daily, improving the timeliness of inventory management and competitive analysis.

Why Us​

Frontend scraping and backend data processing capabilities combined. We tailor collection strategies to target website characteristics and deliver automation tools ready for immediate use.

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