Business phase
A RevOps team was running lead imports into their CRM on a recurring basis and needed those uploads to be dependable.
The bottleneck
Before every CRM import, someone was cleaning lead CSVs by hand in chat tools. That ad hoc cleanup was unreliable and had to be redone each time.
The operating drag
Inconsistent formatting meant lead data didn't line up with the CRM's expected fields, so imports either needed manual rework or failed outright.
What we saw
The problem wasn't the people doing the cleanup, it was the lack of a repeatable process. The same normalization and validation steps were being reinvented on every upload.
What we built
We built a repeatable formatter repo with validation rules for CRM upload, using Python for CSV normalization and a documented field mapping. It applies consistent normalization and validation against that mapping every time.
Handoff
The documented field mapping and the formatter repo gave the team a reusable tool to run imports themselves, with the rules written down rather than held in someone's head.
The win
Lead imports stay consistent, without manual rework or import failures.
What came next
With a documented mapping in place, the formatter can extend to new fields or validation rules as the CRM and lead sources evolve.