Car Auction Intelligence System

Used Car Dealership, New York

Project overview

Full automation pipeline that scrapes live auction listings from Manheim MMR, BacklotCars, Autoniq, and ADESA daily. Compares each vehicle's auction price against its MMR market value, filters by profit margin, and sends formatted HTML email alerts to the dealer team every morning.

The challenge

The dealer's team was spending 3–4 hours every morning manually checking prices across multiple platforms and still missing profitable deals because competitors were faster.

My solution

Built a fully automated Python pipeline with cookie management, proxy rotation, and scheduled execution. The system runs at 6 AM daily, processes hundreds of listings, and delivers a prioritized deal list by email before the team starts work.

Result

Saves 8+ hours per week. Client finds 3x more profitable vehicles. Deals are spotted within minutes instead of hours.

Tech stack

Python, Selenium, Pandas, Gmail SMTP, Cookie Management, Scheduling

What was built