A lead list that stays fresh
Companies that fit the ideal customer, found in public data, verified, and delivered straight into the CRM.
8,000 qualified companies a quarter, bounce rate under 3%
The sales team was buying lead lists that went stale within weeks and bounced on the first send. I built a pipeline that starts from public business directories and company websites, finds firms that match the ideal customer profile, and reads each site for company size, services and published contact routes. Every email address is verified before it is saved, duplicates are merged, and a language model writes one line on why the company fits. Records land in the CRM with the source of every field kept. Result: 8,000 qualified companies a quarter, a bounce rate under 3%, and no bought list since.
- Client
- B2B software company, United Kingdom
- Role
- Design and build
- Stack
- Python, Playwright, PostgreSQL, Claude for classification, email verification service, HubSpot API
