Automobile and Real Estate Automation System

Project Description

Developed a custom web scraping and market automation system designed to monitor automobile, real estate, and job listing websites across multiple countries, providing actionable insights into market trends and activity.

Key Contributions & Features:

• Built scalable and efficient Python-based web scrapers capable of handling large volumes of data across multiple marketplaces.
• Implemented advanced filtering techniques and timestamp-based analysis to accurately track:
  • Daily and weekly listing counts
  • Newly added listings
  • Category-wise and region-wise market statistics
• Designed the system to support multi-country data collection, ensuring adaptability to different website structures and formats.
• Utilized Google BigQuery for robust data storage, enabling efficient querying, aggregation, and management of large datasets.
• Integrated processed data into Excel dashboards and reports for easy visualization and stakeholder consumption.
• Automated end-to-end data collection and reporting workflows, reducing manual effort and ensuring consistent, scheduled updates.

Impact:

Improved operational efficiency through automation and scalable architecture.

Enabled clients to monitor market trends, inventory fluctuations, and industry activity in near real-time.

Provided reliable, data-driven insights to support strategic decision-making and competitive analysis.

Project Specs

Project link	Private Project
Technology	Python, BigQuery, Headless Browser, Ubuntu