The Challenges
- Fragmented Product Data
- MLO works with dozens of small parts vendors, each with their own unique and inconsistent data formats for parts, inventory and order sheets
- Product data was managed exclusively in Shopify’s backend, limiting its use for other platforms and tools.
- Poorly structured data made it impossible to implement a parts configurator
- Inefficient Data Management
- Editing or enhancing product information required MLO's employees to work inside Shopify’s interface.
- Lack of Suitable Off-the-Shelf Options
- Existing PIM solutions on the market lacked the user experience, customization, and Shopify alignment MLO required.
The Solutions
SchemIQ - Smart ETL with a simple, drag-and-drop interface
- Simplified UI
- After logging in, staff could drag and drop any file and see upload progress in a simple, easy-to-understand UI
- AI-Powered Sheet Mapping
- Pixelum built a custom AI engine that mapped any vendor sheet to the correct format, eliminating the need for manual mapping or ETL updates
- PixelPIM Integration
- SchemIQ added new data directly into PixelPIM for new products, and drafted updates to existing products
PixelPIM — A fully custom-built product information management platform:
- Simplified Front-End Experience
- Pixelum designed a simple, lightweight UI that allowed MLO's staff to use PixelPIM with little to no training
- Flexible Data Entry
- Supports adding and editing data directly in PIM, via SchemIQ portal upload, or via Shopify, with changes synced between systems both daily and upon each login to ensure data is always up to date
- One-to-One Categorization
- PixelPIM was configured to match MLO’s exact Shopify categories and taxonomy for seamless product integration
Implementation Highlights
- Business Requirements Spec: Created a detailed functional spec approved by MLO.
- Technical Architecture: Built to run in parallel with Shopify, ensuring data consistency.
- User Experience Design: Tailored to MLO’s workflow priorities, making product updates fast and intuitive.
The Results
- Massive Time Savings
- Reduced product data management from 30-60 hours to just a few hours per month, eliminating the need to hire a data entry technician.
- Improved Data Quality
- Easier editing and enrichment means staff can make more updates in less time and ensure all orders are entered properly
- Scalable
- MLO's PixelPIM implementation can be extended for future data needs and additional systems integration
- Future Proof
- SchemIQ's AI Ingest engine learns over time, preventing the need for updates and new mappings
