PricePulse_
An automated competitor price tracking platform enabling real-time market intelligence for e-commerce businesses with daily scraping, price alerts, and exportable reports.
Entity_Client
Retail Insights Co.
Primary_Role
Backend
Duration_Log
2 months
Resource_Team
2 developers
Project_Overview
Retail Insights Co. manually tracked 200+ competitor prices weekly, spending 15+ hours per week on research. PricePulse automates this process, scraping Amazon, eBay, Walmart, and other platforms daily, providing instant market insights for pricing strategy.
Operational_Process
Built scalable scraping workers using Puppeteer, scheduled jobs with cron, implemented failure recovery, and created a dashboard for visualizing price trends and competitor activity.
Core_Capabilities
Performance_Metrics
Manual Research
DATA_POINT: 100% elimination
Scraping Success
DATA_POINT: <2% missing
Product Coverage
DATA_POINT: real-time updates
Scraping Cycle
DATA_POINT: for all competitors
Alert Speed
DATA_POINT: of price changes
Revenue Impact
DATA_POINT: pricing optimized
Conflict_Resolution
Implemented rotating proxies, randomized user agents, added request throttling, and used headless browser (Puppeteer) to mimic human behavior. Success rate improved to 94%.
Built modular scraper architecture with fallback selectors, added automated failure detection, and created alerts for selector failures. Recovery time reduced to <2 hours.
Implemented parallel scraping with 20 concurrent workers, optimized database queries, and added smart scheduling (high-priority products more frequently). Cycle time reduced to 45 minutes.
Added out-of-stock detection, implemented data validation rules, created duplicate detection, and added manual review queue for anomalies. Data completeness improved to 99.2%.