Catalog management
Make bearings searchable and comparable across brands.
Import supplier exports, map them into one family-aware model, review every proposed change with its source, and export a catalog your filters and search can actually use.
Scoped assessments on request · workspace planned
The problem
Why bearing catalogs
stop being comparable
Every brand, supplier and legacy import brings its own columns. After a few years, the same field means three different things.
- 01
Same label, different meaning
A column called “B” or “Width” can hold ring width, total width or height depending on bearing type. Filters built on it quietly mix incomparable values.
- 02
Blank cells you cannot interpret
Is a missing contact angle unknown, or simply not applicable to a deep-groove ball bearing? Without a status, completeness reports are meaningless.
- 03
Duplicates and near-duplicates
Supplier imports create several rows for one product — while true variants that differ only by suffix get merged by over-eager cleanup.
Worked example
Before and after
one import
Three supplier rows for the same synthetic family, mapped into one model. Originals are preserved next to the normalized values.
| Row | Raw label / value | Normalized field | Value | Status |
|---|---|---|---|---|
| S1-0041 | “B” = 12 | ring_width | 12 mm | populated · rule: radial family |
| S2-1182 | “Width (mm)” = 12,0 | ring_width | 12 mm | populated · decimal comma parsed |
| S3-0007 | “H” = 9 | height | 9 mm | populated · rule: thrust family |
| S1-0041 | “Contact angle” = (blank) | contact_angle | — | not applicable |
| S2-1182 | “Origin” = (blank) | country_of_origin | — | not researched · lot-scoped |
| S3-0007 | “Seal” = “2RS?” | closure | — | conflicting · needs review |
Method
Import → map → review
→ export
The same sequence every time, so results are comparable between categories and suppliers.
Import and preserve
Keep each source file as received, with row IDs, so every later value can be traced back.
Profile and check
Structural checks: required identifiers, units, invalid values, duplicate candidates. The free checker does this step.
Map to family schemas
Map columns per bearing family, with applicability rules, instead of one global string-to-field table.
Review changes
Proposed values arrive with source, method and conflicts. Reviewers accept, reject or defer.
Export
A flat, consistent sheet per category — or the format your PIM imports — plus an exceptions list.
Outcome and limits
What you get — and what you don’t
A category in which every column means one thing, every blank has a reason, and every changed value can be traced to a source and a decision.
| Detail | |
|---|---|
| Included | Field mapping per family with documented rules |
| Included | Field status for every applicable attribute |
| Included | Duplicate candidate groups for review |
| Included | Flat export plus exceptions list |
| Not included | Self-serve workspace (planned) |
| Not included | Automatic merges or overwrites |
| Not included | Engineering substitution approval |
| Not included | Connectors to specific marketplaces or PIMs (scoped per engagement) |
Delivery options
How it is delivered today
- Available
Free structural check
Run the checker locally on any CSV export.
Open checker - On request
Scoped category assessment
One category, agreed sources and record count, delivered as reviewed files.
Request scope - Planned
Catalog workspace
Private import, review and export workflow with audit history.
Related
Keep reading
Do I need to send you my data to start?
No. The catalog checker runs in your browser and nothing is uploaded. Share data only once a scoped assessment and handling process are agreed.
Will you change our taxonomy?
Only if that is in scope. Mapping into family schemas can sit alongside your existing taxonomy; the scope of any taxonomy work is agreed explicitly per engagement.
Can you write back into our PIM or marketplace tool?
Today delivery is file-based. Specific integrations are scoped per engagement once the data work is proven; we do not advertise connectors that do not exist.
Start with one category.
See the gaps before you commit.
Run the free checker on an export, then tell us which category hurts most. We will propose a scoped assessment with clear inclusions.