Our catalog is too big to clean up
Hundreds or thousands of products with thin titles, missing descriptions, and incomplete structured data — the cleanup never makes it off the backlog.
What we do about it
We do the heavy lifting: bulk structuring, AI-assisted titles, descriptions, and tags with human review, and structured-data completion across the full catalog.
How it starts
With evidence, not a pitch: the free scan reads your store the way an AI agent does and shows exactly where this problem lives — then the fix is scoped to those findings.
From backlog to done, in batches
Catalog cleanup fails as a side-project because it's ten minutes per product times four thousand products. It succeeds as a pipeline: prioritize by impact, draft with AI, review with humans, publish in batches, verify with a re-scan. That pipeline is the service.
- Audit the catalog: what's missing where, ranked by traffic and revenue impact — the top 200 products first, not alphabetical order.
- Draft titles, descriptions, tags, and structured data with AI, grounded in your existing copy and brand voice.
- Human review of every draft. Nothing touches the live store unreviewed.
- Publish in batches with a change log — every change visible, every change revertible.
- Re-scan: the before/after score is the proof the backlog actually closed.
Common questions
How long does a few-thousand-product cleanup take?
It ships in prioritized batches from week one rather than landing all at once — high-traffic products first. Total duration depends on catalog size and how much source material exists per product; the quote after the free scan includes a timeline.
Will we lose the copy we already wrote?
No. Existing copy is the raw material, not the casualty — drafts build on it, a human reviews every change, and the change log means anything can be reverted.
Other situations
Sound familiar?
The scan is free, reads only your public pages, and shows whether this is actually your problem — before anyone talks money.