The problem
Product data drifts as catalogs grow: missing meta descriptions, empty alt text, inconsistent tags, weak titles. Fixing thousands of products one by one is impractical.
How Product Optimizer solves it
Product Optimizer scans your catalog, surfaces issues in a structured report and lets you apply fixes in bulk with previews and undo.
Core features
Catalog audit
Automated scan for missing SEO titles, meta descriptions, alt text, weights, barcodes and more.
Suggested fixes
Rule-based suggestions that respect your brand voice — never a black-box rewrite.
Bulk apply with preview
Approve suggestions in batches with a visible diff.
Tag normalization
Merge duplicates, enforce casing and clean up unused tags.
Continuous monitoring
Optional weekly reports flag new issues as products are added.
Use cases
Catalog cleanup before a migrationSEO baseline before content investmentPreparing a store for Google ShoppingPost-import data quality
Who it's for
- Growing brands
- Agencies
- Enterprise merchants
Comparison
| Capability | Manual editing | CSV import | ABAR |
|---|---|---|---|
| Preview before commit | — | — | Yes |
| Undo / rollback | — | — | Yes |
| Scheduling | — | — | Yes |
| Batch validation | Manual | Post-import | Pre-commit |
| Rate-limit handling | N/A | Manual retries | Automatic |
Frequently asked questions
Suggestions use rule-based templates by default. AI generation is opt-in per field type.