Most supplier onboarding takes 30-45 days because teams review every field manually before publishing anything. Automate the mapping, normalize on ingest, validate at publish time, and fix what breaks in production.
A German circuit breaker manufacturer sends 2,000 SKUs in Excel. Column headers are in German: Nennspannung, Bemessungsstrom, Schutzart. Descriptions mix three languages in the same column. Some dimensions are mm, others cm. 43 records have no UPC. Images sit on an FTP server with filenames that don't match SKUs.
Every supplier file looks like this. The question is whether you spend 6 weeks cleaning it or 24 hours shipping it.
Hours 1-3: Map supplier columns to your schema
Match supplier columns to your catalog fields using keyword matching. Most fields map automatically. You verify 4-5 ambiguous cases by hand.
| Supplier column | Your field | ETIM attribute |
|---|---|---|
| Nennspannung | rated_voltage | EF000002 |
| Bemessungsstrom | rated_current | EF000004 |
| Schutzart | IP_rating | EF000012 |
That gets 85% coverage in 20 minutes. Save the mapping template. Next time this supplier sends an update, the whole step runs in under 60 seconds.
Column matches a standard electrical term: auto-map, confidence score above 0.8 Column holds product-specific data: keep as custom attribute, flag for ETIM review later Column is internal supplier metadata: discard, document in mapping template
Hours 4-6: Normalize units
Voltage values arrive in four formats from the same file.
Raw supplier data
- 240V
- 240 VAC
- 240V AC
- 240 V~
After normalization
- 240 V AC (all four collapsed)
- Validation flag: verify AC/DC from datasheet
Dimensions convert from mm to inches where your US buyers expect imperial. For enclosures and conduit, show both units in the description.
Hours 7-10: Match images to SKUs
Pull images from the supplier FTP. Filename CB-2401.jpg needs to match SKU MCB-240-10A. The matching logic strips prefixes, tries partial matches on the numeric portion, falls back to manufacturer part number.
Of 2,000 products, 1,847 images match automatically. The remaining 153 get a category placeholder and a flag. Do not block the publish waiting for perfect images.
- Minimum resolution 800x800px
- File size under 2MB
- Format is JPG or PNG (convert any TIFFs)
- Filename contains SKU or manufacturer part number
- Image shows product only, no marketing overlays
Hours 11-15: Validate before publishing
Run automated validation. Catch errors here, not during manual review.
Block publish if UPC, manufacturer, or category is missing. Result: 43 records blocked (no UPC).
Flag records where voltage falls outside 0-1000V. Result: 12 records flagged, probably typos (2400V instead of 240V).
Warn if description is under 20 characters. Result: 8 records flagged. Enrichment fixes this later.
Hours 16-20: Enrich from datasheets
For the 8 records with stub descriptions, pull structured data from manufacturer PDFs.
Before enrichment "Circuit breaker"
After datasheet extraction "Circuit breaker, breaking capacity 10kA at 240V AC, thermal-magnetic trip, DIN rail mount"
Source: manufacturer technical datasheet, cross-referenced against IEC 60898
After hour 20 you hit diminishing returns. Remaining records either have no datasheet or the PDF is a scanned image that OCR cannot parse reliably. Leave them flagged and move on.
Hours 21-24: Ship it
Push 1,957 products to staging. Smoke test: category filters work, search returns results, product pages render. Publish to production.
Within 30 minutes you spot 6 products in the wrong category. Miniature circuit breakers can map to two different ETIM classes depending on rated current. Remap 2 SKUs manually, leave 4 in the original class (technically correct for both).
| Metric | Count |
|---|---|
| Products live | 1,957 |
| Flagged for UPC follow-up | 43 |
| Remapped after publish | 6 |
This assumes you have automated field mapping with keyword matching, normalization rules for voltage formats and unit conversions, and validation rules that run before publish. You do not need a dedicated data team, perfect supplier data, or months of process documentation.