Web Scraping & Data Collection

Teams spend hours browsing websites to track competitors’ prices, monitor product rankings on marketplaces, or compile industry data. This manual data collection is both time-consuming and inconsistent — a different person looks each day, notices different things, and produces a different table. When reliable data is needed to make decisions, the process of collecting that data must also be reliable.

Our Solution Approach

Reliability and sustainability are our priorities in web scraping projects. The agents we develop run periodically, convert data into a structured format, and transfer it to a central system. When the site design changes, the agent sends an alert rather than silently failing; the problem is identified and corrected. The infrastructure is designed within this framework to keep data current and reliable.

Scope & Features

• Competitor price tracking — Daily or hourly monitoring of price, stock status, and campaign information at specified product URLs; accumulation of historical data
• Marketplace ranking tracking — Periodic reporting of product positions in search results on appropriate and permitted sources
• Content and news collection — Keyword-based content compilation and summarization from industry publications, news sites, or blog platforms
• Job listing and opportunity scanning — Automatic detection and notification of opportunities matching specific criteria from LinkedIn, career sites, or tender platforms
• Public data collection — Regular structured data extraction from sources such as open data portals, municipal announcements, and tender listings
• Dynamic site scraping with headless browser — Playwright-supported scraping covering sites built with React or Angular that require JavaScript rendering
• Proxy rotation and rate limit management — Proxy pool to handle IP-based restrictions; respectful request rate toward the target site
• Data cleaning and standardization — Cleaning messy data extracted from raw HTML, formatting it, and converting it to a consistent structure

Technical Standards

Python is used with Playwright, Scrapy, or BeautifulSoup; the choice is made based on project requirements. Playwright is preferred for pages requiring dynamic JavaScript content. Collected data is transferred to PostgreSQL, Google Sheets, or a custom API endpoint. Periodic runs via Cron Job or APScheduler; email or Telegram notification on failed runs.

Who Is It For?

• E-commerce businesses and pricing teams that want to track competitor prices and campaign information on a daily basis
• Firms needing external data feeds such as industry content, job listings, or tender data
• Analyst and consulting teams that conduct source-based data compilation for market research

Expected Outcomes

• Hours of manual data collection are eliminated; teams spend time analyzing data rather than searching for it
• Consistent, current, and reliable data puts pricing and product decisions on solid ground
• Faster responses to competitor moves; price changes or campaigns are noticed within a few hours
• Accumulation of historical data becomes a valuable asset for analytical modeling and trend detection