MC Lead Scraper — Automated Carrier Lead Extraction Tool

Problem

Truck dispatching companies rely on cold callers to reach out to trucking companies (MCs) and pitch dispatch services. The standard workflow was entirely manual: cold callers had to go to the FMCSA and SAFER websites, look up MC numbers one by one, manually check each company’s details to figure out if it was actually a good lead, copy the phone number, and enter it into the dialer by hand — then repeat that hundreds of times a day.

On top of the sheer time cost, a large chunk of the MCs in those databases weren’t even usable leads: freight brokers, freight forwarders, dump truck companies, car wash businesses, and other non-trucking-carrier entries were mixed in with real owner-operators and fleet carriers. Cold callers had no way to filter these out ahead of time, so they’d waste calls — and time — reaching irrelevant companies. With this manual process, a caller could only get through around 250 dial attempts a day, and out of those, only about 50 actual calls connected. Everything else was lost to lookup time, bad numbers, and irrelevant leads.

How I solved it / What I built

I designed and built this as an internal automation tool aimed at solving a very specific, repetitive bottleneck I saw firsthand while working in the industry as a cold caller myself in 2025 — I understood the pain point from the inside before building the fix.

The tool pulls MC and carrier data directly from FMCSA and SAFER, then automatically filters out everything that isn’t a usable lead — freight brokers, freight forwarders, dump truck operators, car washes, and other non-carrier business types — so cold callers only ever see genuine trucking companies worth calling. The core engineering challenge was building reliable extraction and classification logic that could tell a real trucking carrier apart from adjacent but irrelevant business types, since the raw government data doesn’t come pre-sorted for that.

Once the filtering logic was reliable, the tool generates thousands of clean leads per day, with phone numbers ready to feed straight into the dialer — removing the manual lookup step entirely.

Screenshots

Result

The impact was immediate and measurable. Callers went from 250 raw dials a day to 500 dials a day, because they were no longer burning time on manual lookups. Because the leads were pre-filtered instead of random, the pickup/connect rate improved by roughly 70%, and the company saw about a 50% increase in sales as a direct result of callers spending their time actually talking to prospects instead of hunting for them — more dials, more connects, more sales, all from the same headcount.