This is like hiring thousands of secret shoppers to check competitor prices every few minutes before and during Black Friday/Cyber Monday—then feeding that intel into a smart spreadsheet so you can automatically adjust your own prices to stay attractive and profitable.
Retailers struggle to set the right price during Black Friday/Cyber Monday because competitor prices change rapidly, promo windows are short, and manual tracking is impossible at scale. Automated web scraping and analytics provide up‑to‑date market prices, discounts, and stock signals so ecommerce teams can optimize promotions and margins in near real time.
Sustainable advantage comes from breadth/quality of scraped coverage (sites, geos, SKUs), robust anti-blocking infrastructure, and proprietary historical price datasets that improve pricing rules and elasticity models over time.
Classical-ML (Scikit/XGBoost)
Structured SQL
Medium (Integration logic)
Keeping large-scale web scraping reliable during peak promo seasons without being blocked (IP rotation, captchas), and ensuring timely processing of scraped data into pricing systems.
Early Majority
Positioned specifically around Black Friday/Cyber Monday ecommerce pricing, emphasizing turnkey large-scale web scraping for competitor price and product data rather than full-stack dynamic pricing optimization. Strength is in data collection at scale, which can plug into a retailer’s existing pricing engines or BI stack.