F-06Data Quality
Measure the catalog. Review the changes. Restore the mistakes.
Every product carries a completeness score based on description, imagery, specifications, documents and SEO fields. Every change is captured field by field, and nothing reaches a channel without passing review.
- Score dimensions
- 5
- Change history
- Field-level
- Workflow states
- 6
- Any revision
- Restore
01Capabilities
What it does
Q-01
Completeness scoring
Description length, primary imagery, minimum attribute count, attached documents and SEO fields each contribute to a score recalculated automatically on every change.
Q-02
Missing-info alerts
The dashboard lists the products dragging the catalog down, so enrichment work is prioritised instead of guessed at.
Q-03
Approval workflow
Draft, in review, changes requested, approved, published, archived. Reviewers approve, reject or request changes with threaded comments.
Q-04
Version history and diff
Compare any two revisions of a product, see exactly which fields changed and who changed them, and restore an earlier state.
Q-05
Roles and tenant isolation
Six roles from platform admin to distributor user, enforced with row-level security so an organisation only ever sees its own data.
quality.panel
Descriptions88%
Imagery81%
Specifications92%
Documents64%
SEO fields47%
| Awaiting review | From | To |
|---|---|---|
| AX-410-AN | Draft | In review |
| TL-T2-CTRL | In review | Approved |
| BH-10-SET | Changes req. | In review |
Outcomes
- A number you can report on instead of a feeling about data quality.
- Incorrect torque figures never reach a published channel.
- Any accidental overwrite is one restore away.
Score your current catalog
Send an export and we will show you the completeness breakdown before you commit to anything.