Leads Processing Automation
A Python automation that turned a three-hour manual lead-cleaning task into a job that finishes in minutes, with no recurring cost.
The challenge
A client reached out to us through one of our channels with a recurring headache. Every week he received a large leads spreadsheet and had to clean it by hand: normalising company names, pulling the client's first name out of their full name, standardising city spellings, and splitting the list by email provider. It took roughly three hours each time and mistakes slipped through.
Our solution
After understanding his exact workflow, we built a dedicated Python application that ingests the raw CSV, normalises company names, extracts first names, standardises city names, and exports two clean files: one for contacts on Microsoft email and one for everyone else. We tested it against his real data until the output matched what he would have produced by hand, only faster.
Results & impact
- Three hours of manual work reduced to a few minutes
- Consistent, accurate output with no human slips
- Runs locally for life with no per-task limits or subscription
Technology
Related work
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