Our client operates across more than 40 countries, helping businesses make informed strategic decisions through comprehensive market research and data analysis. Their expertise lies in developing and providing practical solutions for sustainable growth and business expansion to Fortune 500 companies, non-profit organizations, and government institutions.
The client sought our website data scraping services to extract detailed business listings for approximately 150 prominent brands across multiple geographic locations from a prominent business directory. Their goal was to build a reliable and extensive business intelligence database to support their strategic market research initiatives, competitive analysis, and client advisory services.
The requested dataset included:
While executing this large-scale data extraction project, our team encountered multiple technical obstacles that required careful handling:
To overcome the technical limitations and ensure seamless data collection at scale, we developed a customized end-to-end web data scraping solution optimized for the business directory’s ecosystem.
To capture both static fields (e.g., business name, address) and JavaScript-rendered content (e.g., reviews, extended details), we deployed a hybrid stack that combined Scrapy for high-speed crawling and Selenium in headless Chrome mode for pages that required rendering.
We bypassed the platform’s anti-bot scraping measures by rotating residential proxies, randomizing request headers, utilizing adaptive crawling speeds, and implementing intelligent retry logic. This approach mimicked natural browsing patterns while distributing requests to avoid IP-based blocking and rate limiting.
Additionally, we implemented CAPTCHA detection and automatic re-queuing, ensuring smooth data collection despite platform security features.
We standardized the extracted information across all listings, ensuring consistency and accuracy. Key data points like addresses, contact details, and reviews were cleaned and validated to eliminate duplicates and inconsistencies. Inconsistent formats (such as varying phone number styles, address abbreviations, and rating scales) were normalized into a unified structure, enabling seamless integration with the client's existing systems and analysis tools.
Leveraging a custom dictionary in Python, we built a mapping system that translated codes into real phone digits. This allowed us to accurately reconstruct complete phone numbers from the coded patterns.
Additionally, we developed custom scraping logic to automatically detect whether search results spanned a single page or multiple pages, then systematically navigated through all available pages using adaptive "Next" button detection and URL parameter analysis. This ensured complete data capture regardless of whether a brand had 10 listings or 500+ listings across dozens of pages.
We implemented error-handling mechanisms, such as retry logic with exponential backoff (to manage temporary network issues, timeouts, or site-imposed restrictions) and real-time data validation. Instead of relying solely on automation, we also employed our data specialists for QA and manual data validation. They verified extraction accuracy and intervened to fine-tune scraping parameters or resolve complex edge cases. This hybrid approach minimized data loss and maximized the reliability of the information extracted.
The web scraping solution was deployed on a secure VPS (virtual private server) and designed for scalability, supporting parallel scraping across multiple brand-location combinations. The scraper was automated to run on demand or via scheduled tasks, ensuring timely data extraction without manual intervention. The system also provided detailed run logs and reporting to track the progress of each scraping cycle.
Our team securely and successfully scraped relevant information (over 50,000 records) for the required brands with 99% accuracy. This ready-to-use dataset empowered the client’s market intelligence strategies and helped them achieve measurable growth, such as:
50,000+ business listings extracted across 150 global brands and multiple locations
99% data accuracy maintained through automated web scraping & human data validation workflows
Time-to-insight reduced by 45%, enabling faster client advisory and market research outputs.
We provide support for web research and data management powering strategic decision-making and faster business intelligence for enterprises. Schedule a free consultation to know more about our web scraping and data collection services.