34 dental clinics, 9 emails, 1 A-tier: the honest math of a $0 lead-gen run

Description and use

The author replaced a paid lead‑gen stack with five open‑source Python scripts, scraped 34 dental clinics in Tucson, found 9 emails (1 verified, 7 guesses), graded them into tiers, and sent only the A‑tier lead. With a 3–8 % reply rate, a single batch yields zero‑one replies, so weekly runs and strict verification are essential.

Problem

Lead‑generation stacks cost money and produce many dead or guessed emails, making outreach ineffective and damaging domain reputation.

Outcome

The run produced 34 scraped clinics, 12 enriched, 9 emails, with tier distribution A:1, B:2, C:5, D:4. Only one email was verified from a website; the rest were guesses. The expected reply rate (3–8%) yields zero to one reply per batch, emphasizing the need for weekly runs and strict grading before sending.

Workflow

• scrape_maps.py – build list from OpenStreetMap
• enrich_emails.py – find and tag email sources
• dedupe_score.py – dedupe and grade tiers
• write_opener.py – draft first line from a real fact
• send_track.py – send via own SMTP with tracking

Evidence

I replaced a $49–$299-a-month lead-gen stack with five small Python scripts I own outright.

Source

Thirty-four businesses went in. Nine email addresses came out. One of them was worth writing to today.

Source

The scrape is the easy 10%. The list you send to is the other 90%.

Source

A tier-A lead is a verified address, a decision-maker, and one real fact found in two minutes of looking.

Source