Cleaning Up 10,000+ Products for Seamless BigCommerce & MYOB Integration

The Hidden Problem

A national wholesaler operating across medical, mining, and air systems was preparing a major overhaul of its online catalogue. But like many growing businesses, the product data was a mess.

• Scattered across multiple spreadsheets
• Inconsistent naming conventions
• Duplicate records and broken variant logic
• Key details missing or misaligned between systems

The team was burning hours trying to align product records between BigCommerce and MYOB, but manual fixes kept falling short. Every upload risked new errors, and every clean-up pass created more rework.

The Practical Fix

• Standardised raw product data
  Cleaned specifications, grouped filter types, mapped brands, and corrected inconsistent naming to create a usable master list.
• Consolidated variants and removed duplicates
  Merged OEM and housing fields, preserved variant logic, and eliminated redundancies without breaking category or SKU structure.
• Built SEO-ready BigCommerce listings
  Created import-ready rows with product names, HTML descriptions, meta titles, meta descriptions, image URLs, and required weight fields.
• Mapped images for bulk upload
  Generated a dynamic PythonGroups sheet linking each SKU to the correct brand and filter-type folders for future automated image handling.
• Formatted files to BigCommerce import rules
  Structured image and product import rows to match BigCommerce's strict requirements, reducing upload failures and manual correction.
• Synced MYOB pricing and inventory
  Matched cleaned parts with MYOB inventory, flagged missing SKUs, and pushed pricing updates in bulk for faster reconciliation.

The Result

• Reduced manual data handling time by 90%
• Delivered a clean, searchable product catalogue
• Enabled seamless imports into both BigCommerce and MYOB
• Laid the foundation for future automation with Python and Excel

Why It Mattered

Messy product data is one of the biggest hidden blockers to growth. It slows teams down, breaks automation, creates friction for customers, and makes every system integration harder than it should be.

By turning a chaotic product list into a structured, SEO-friendly, platform-ready dataset, this wholesaler gained control of its catalogue and built a cleaner path to scale.

Implementation Snapshot

1. Extracted and consolidated raw product data from multiple sources.
2. Standardised naming, grouped related attributes, and cleaned duplicates.
3. Built import-ready BigCommerce product rows with SEO and image fields.
4. Matched and reconciled SKUs against MYOB pricing and inventory records.
5. Prepared the catalogue for repeatable bulk uploads and future automation.

Key Takeaways

• 10,000+ SKUs were cleaned, consolidated, and restructured.
• Product data was aligned across MYOB and BigCommerce.
• SEO-ready listings were built with meta and image data included.
• Pricing sync and bulk updates became faster and more reliable.
• Manual processing time was slashed, and future automation was unlocked.