Automated Global Catalog Audit System

The Problem

The team's bi-weekly global catalog audit was a grueling 16-hour manual process. An analyst had to verify thousands of SKUs across 12 countries, checking every attribute — titles, descriptions, images, pricing, and keywords — against strict business rules. The process was slow, error-prone, and consumed valuable human hours.

The Solution

I engineered a comprehensive Python script that completely automates the entire audit pipeline:

• Multi-Country Data Ingestion — Reads and normalizes catalog data across 12 different country formats
• Rule-Based Validation — Validates every attribute against configurable business rules (title length, image requirements, required fields, pricing logic)
• Automated Issue Detection — Flags discrepancies, missing data, suppressed listings, and compliance violations
• Pre-Formatted Error Reports — Auto-generates country-specific issue files ready for the operations team to act on
• Summary Dashboard — Produces an audit summary showing pass/fail rates per country and issue categories

The Impact

What once took 16 hours now takes under 5 minutes. The script processes thousands of SKUs with zero human error, freeing up the team for strategic work. This single automation paid for itself on day one and continues to save the company significant time every cycle.